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0 34s ``` At this point, it should be clear that the resources users create in one namespace are hidden from the other namespace. As the policy support in Kubernetes evolves, we will extend this scenario to show how you can provide different authorization rules for each namespace. ## Understanding the motivation for using namespaces A single cluster should be able to satisfy the needs of multiple users or groups of users (henceforth in this document a \_user community\_). Kubernetes \_namespaces\_ help different projects, teams, or customers to share a Kubernetes cluster. It does this by providing the following: 1. A scope for [names](/docs/concepts/overview/working-with-objects/names/). 1. A mechanism to attach authorization and policy to a subsection of the cluster. Use of multiple namespaces is optional. Each user community wants to be able to work in isolation from other communities. Each user community has its own: 1. resources (pods, services, replication controllers, etc.) 1. policies (who can or cannot perform actions in their community) 1. constraints (this community is allowed this much quota, etc.) A cluster operator may create a Namespace for each unique user community. The Namespace provides a unique scope for: 1. named resources (to avoid basic naming collisions) 1. delegated management authority to trusted users 1. ability to limit community resource consumption Use cases include: 1. As a cluster operator, I want to support multiple user communities on a single cluster. 1. As a cluster operator, I want to delegate authority to partitions of the cluster to trusted users in those communities. 1. As a cluster operator, I want to limit the amount of resources each community can consume in order to limit the impact to other communities using the cluster. 1. As a cluster user, I want to interact with resources that are pertinent to my user community in isolation of what other user communities are doing on the cluster. ## Understanding namespaces and DNS When you create a [Service](/docs/concepts/services-networking/service/), it creates a corresponding [DNS entry](/docs/concepts/services-networking/dns-pod-service/). This entry is of the form `..svc.cluster.local`, which means that if a container uses `` it will resolve to the service which is local to a namespace. This is useful for using the same configuration across multiple namespaces such as Development, Staging and Production. If you want to reach across namespaces, you need to use the fully qualified domain name (FQDN). ## {{% heading "whatsnext" %}} \* Learn more about [setting the namespace preference](/docs/concepts/overview/working-with-objects/namespaces/#setting-the-namespace-preference). \* Learn more about [setting the namespace for a request](/docs/concepts/overview/working-with-objects/namespaces/#setting-the-namespace-for-a-request) \* See [namespaces design](https://git.k8s.io/design-proposals-archive/architecture/namespaces.md).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/namespaces.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/namespaces.md
|
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|
This page shows how to configure and enable the `ip-masq-agent`. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## IP Masquerade Agent User Guide The `ip-masq-agent` configures iptables rules to hide a pod's IP address behind the cluster node's IP address. This is typically done when sending traffic to destinations outside the cluster's pod [CIDR](https://en.wikipedia.org/wiki/Classless\_Inter-Domain\_Routing) range. ### Key Terms \* \*\*NAT (Network Address Translation)\*\*: Is a method of remapping one IP address to another by modifying either the source and/or destination address information in the IP header. Typically performed by a device doing IP routing. \* \*\*Masquerading\*\*: A form of NAT that is typically used to perform a many to one address translation, where multiple source IP addresses are masked behind a single address, which is typically the device doing the IP routing. In Kubernetes this is the Node's IP address. \* \*\*CIDR (Classless Inter-Domain Routing)\*\*: Based on the variable-length subnet masking, allows specifying arbitrary-length prefixes. CIDR introduced a new method of representation for IP addresses, now commonly known as \*\*CIDR notation\*\*, in which an address or routing prefix is written with a suffix indicating the number of bits of the prefix, such as 192.168.2.0/24. \* \*\*Link Local\*\*: A link-local address is a network address that is valid only for communications within the network segment or the broadcast domain that the host is connected to. Link-local addresses for IPv4 are defined in the address block 169.254.0.0/16 in CIDR notation. The ip-masq-agent configures iptables rules to handle masquerading node/pod IP addresses when sending traffic to destinations outside the cluster node's IP and the Cluster IP range. This essentially hides pod IP addresses behind the cluster node's IP address. In some environments, traffic to "external" addresses must come from a known machine address. For example, in Google Cloud, any traffic to the internet must come from a VM's IP. When containers are used, as in Google Kubernetes Engine, the Pod IP will be rejected for egress. To avoid this, we must hide the Pod IP behind the VM's own IP address - generally known as "masquerade". By default, the agent is configured to treat the three private IP ranges specified by [RFC 1918](https://tools.ietf.org/html/rfc1918) as non-masquerade [CIDR](https://en.wikipedia.org/wiki/Classless\_Inter-Domain\_Routing). These ranges are `10.0.0.0/8`, `172.16.0.0/12`, and `192.168.0.0/16`. The agent will also treat link-local (169.254.0.0/16) as a non-masquerade CIDR by default. The agent is configured to reload its configuration from the location \*/etc/config/ip-masq-agent\* every 60 seconds, which is also configurable.  The agent configuration file must be written in YAML or JSON syntax, and may contain three optional keys: \* `nonMasqueradeCIDRs`: A list of strings in [CIDR](https://en.wikipedia.org/wiki/Classless\_Inter-Domain\_Routing) notation that specify the non-masquerade ranges. \* `masqLinkLocal`: A Boolean (true/false) which indicates whether to masquerade traffic to the link local prefix `169.254.0.0/16`. False by default. \* `resyncInterval`: A time interval at which the agent attempts to reload config from disk. For example: '30s', where 's' means seconds, 'ms' means milliseconds. Traffic to 10.0.0.0/8, 172.16.0.0/12 and 192.168.0.0/16 ranges will NOT be masqueraded. Any other traffic (assumed to be internet) will be masqueraded. An example of a local destination from a pod could be its Node's IP address as well as another node's address or one of the IP addresses in Cluster's IP range. Any other traffic will be masqueraded by default. The below entries show the default set of rules that are applied by the ip-masq-agent: ```shell iptables -t nat -L IP-MASQ-AGENT ``` ```none target prot opt source destination RETURN all -- anywhere 169.254.0.0/16 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL RETURN all -- anywhere 10.0.0.0/8 /\*
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/ip-masq-agent.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/ip-masq-agent.md
|
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|
the default set of rules that are applied by the ip-masq-agent: ```shell iptables -t nat -L IP-MASQ-AGENT ``` ```none target prot opt source destination RETURN all -- anywhere 169.254.0.0/16 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL RETURN all -- anywhere 10.0.0.0/8 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL RETURN all -- anywhere 172.16.0.0/12 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL RETURN all -- anywhere 192.168.0.0/16 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL MASQUERADE all -- anywhere anywhere /\* ip-masq-agent: outbound traffic should be subject to MASQUERADE (this match must come after cluster-local CIDR matches) \*/ ADDRTYPE match dst-type !LOCAL ``` By default, in GCE/Google Kubernetes Engine, if network policy is enabled or you are using a cluster CIDR not in the 10.0.0.0/8 range, the `ip-masq-agent` will run in your cluster. If you are running in another environment, you can add the `ip-masq-agent` [DaemonSet](/docs/concepts/workloads/controllers/daemonset/) to your cluster. ## Create an ip-masq-agent To create an ip-masq-agent, run the following kubectl command: ```shell kubectl apply -f https://raw.githubusercontent.com/kubernetes-sigs/ip-masq-agent/master/ip-masq-agent.yaml ``` You must also apply the appropriate node label to any nodes in your cluster that you want the agent to run on. ```shell kubectl label nodes my-node node.kubernetes.io/masq-agent-ds-ready=true ``` More information can be found in the ip-masq-agent documentation [here](https://github.com/kubernetes-sigs/ip-masq-agent). In most cases, the default set of rules should be sufficient; however, if this is not the case for your cluster, you can create and apply a [ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/) to customize the IP ranges that are affected. For example, to allow only 10.0.0.0/8 to be considered by the ip-masq-agent, you can create the following [ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/) in a file called "config". {{< note >}} It is important that the file is called config since, by default, that will be used as the key for lookup by the `ip-masq-agent`: ```yaml nonMasqueradeCIDRs: - 10.0.0.0/8 resyncInterval: 60s ``` {{< /note >}} Run the following command to add the configmap to your cluster: ```shell kubectl create configmap ip-masq-agent --from-file=config --namespace=kube-system ``` This will update a file located at `/etc/config/ip-masq-agent` which is periodically checked every `resyncInterval` and applied to the cluster node. After the resync interval has expired, you should see the iptables rules reflect your changes: ```shell iptables -t nat -L IP-MASQ-AGENT ``` ```none Chain IP-MASQ-AGENT (1 references) target prot opt source destination RETURN all -- anywhere 169.254.0.0/16 /\* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE \*/ ADDRTYPE match dst-type !LOCAL RETURN all -- anywhere 10.0.0.0/8 /\* ip-masq-agent: cluster-local MASQUERADE all -- anywhere anywhere /\* ip-masq-agent: outbound traffic should be subject to MASQUERADE (this match must come after cluster-local CIDR matches) \*/ ADDRTYPE match dst-type !LOCAL ``` By default, the link local range (169.254.0.0/16) is also handled by the ip-masq agent, which sets up the appropriate iptables rules. To have the ip-masq-agent ignore link local, you can set `masqLinkLocal` to true in the ConfigMap. ```yaml nonMasqueradeCIDRs: - 10.0.0.0/8 resyncInterval: 60s masqLinkLocal: true ```
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/ip-masq-agent.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/ip-masq-agent.md
|
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{{< feature-state for\_k8s\_version="v1.18" state="stable" >}} This page provides an overview of NodeLocal DNSCache feature in Kubernetes. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Introduction NodeLocal DNSCache improves Cluster DNS performance by running a DNS caching agent on cluster nodes as a DaemonSet. In today's architecture, Pods in 'ClusterFirst' DNS mode reach out to a kube-dns `serviceIP` for DNS queries. This is translated to a kube-dns/CoreDNS endpoint via iptables rules added by kube-proxy. With this new architecture, Pods will reach out to the DNS caching agent running on the same node, thereby avoiding iptables DNAT rules and connection tracking. The local caching agent will query kube-dns service for cache misses of cluster hostnames ("`cluster.local`" suffix by default). ## Motivation \* With the current DNS architecture, it is possible that Pods with the highest DNS QPS have to reach out to a different node, if there is no local kube-dns/CoreDNS instance. Having a local cache will help improve the latency in such scenarios. \* Skipping iptables DNAT and connection tracking will help reduce [conntrack races](https://github.com/kubernetes/kubernetes/issues/56903) and avoid UDP DNS entries filling up conntrack table. \* Connections from the local caching agent to kube-dns service can be upgraded to TCP. TCP conntrack entries will be removed on connection close in contrast with UDP entries that have to timeout ([default](https://www.kernel.org/doc/Documentation/networking/nf\_conntrack-sysctl.txt) `nf\_conntrack\_udp\_timeout` is 30 seconds) \* Upgrading DNS queries from UDP to TCP would reduce tail latency attributed to dropped UDP packets and DNS timeouts usually up to 30s (3 retries + 10s timeout). Since the nodelocal cache listens for UDP DNS queries, applications don't need to be changed. \* Metrics & visibility into DNS requests at a node level. \* Negative caching can be re-enabled, thereby reducing the number of queries for the kube-dns service. ## Architecture Diagram This is the path followed by DNS Queries after NodeLocal DNSCache is enabled: {{< figure src="/images/docs/nodelocaldns.svg" alt="NodeLocal DNSCache flow" title="Nodelocal DNSCache flow" caption="This image shows how NodeLocal DNSCache handles DNS queries." class="diagram-medium" >}} ## Configuration {{< note >}} The local listen IP address for NodeLocal DNSCache can be any address that can be guaranteed to not collide with any existing IP in your cluster. It's recommended to use an address with a local scope, for example, from the 'link-local' range '169.254.0.0/16' for IPv4 or from the 'Unique Local Address' range in IPv6 'fd00::/8'. {{< /note >}} This feature can be enabled using the following steps: \* Prepare a manifest similar to the sample [`nodelocaldns.yaml`](https://github.com/kubernetes/kubernetes/blob/master/cluster/addons/dns/nodelocaldns/nodelocaldns.yaml) and save it as `nodelocaldns.yaml`. \* If using IPv6, the CoreDNS configuration file needs to enclose all the IPv6 addresses into square brackets if used in 'IP:Port' format. If you are using the sample manifest from the previous point, this will require you to modify [the configuration line L70](https://github.com/kubernetes/kubernetes/blob/b2ecd1b3a3192fbbe2b9e348e095326f51dc43dd/cluster/addons/dns/nodelocaldns/nodelocaldns.yaml#L70) like this: "`health [\_\_PILLAR\_\_LOCAL\_\_DNS\_\_]:8080`" \* Substitute the variables in the manifest with the right values: ```shell kubedns=`kubectl get svc kube-dns -n kube-system -o jsonpath={.spec.clusterIP}` domain= localdns= ``` `` is "`cluster.local`" by default. `` is the local listen IP address chosen for NodeLocal DNSCache. \* If kube-proxy is running in IPTABLES mode: ``` bash sed -i "s/\_\_PILLAR\_\_LOCAL\_\_DNS\_\_/$localdns/g; s/\_\_PILLAR\_\_DNS\_\_DOMAIN\_\_/$domain/g; s/\_\_PILLAR\_\_DNS\_\_SERVER\_\_/$kubedns/g" nodelocaldns.yaml ``` `\_\_PILLAR\_\_CLUSTER\_\_DNS\_\_` and `\_\_PILLAR\_\_UPSTREAM\_\_SERVERS\_\_` will be populated by the `node-local-dns` pods. In this mode, the `node-local-dns` pods listen on both the kube-dns service IP as well as ``, so pods can look up DNS records using either IP address. \* If kube-proxy is running in IPVS mode: ``` bash sed -i "s/\_\_PILLAR\_\_LOCAL\_\_DNS\_\_/$localdns/g; s/\_\_PILLAR\_\_DNS\_\_DOMAIN\_\_/$domain/g; s/,\_\_PILLAR\_\_DNS\_\_SERVER\_\_//g; s/\_\_PILLAR\_\_CLUSTER\_\_DNS\_\_/$kubedns/g" nodelocaldns.yaml ``` In this mode, the `node-local-dns` pods listen only on ``. The `node-local-dns` interface cannot bind the kube-dns cluster IP since the
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/nodelocaldns.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/nodelocaldns.md
|
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] | 0.208145
|
so pods can look up DNS records using either IP address. \* If kube-proxy is running in IPVS mode: ``` bash sed -i "s/\_\_PILLAR\_\_LOCAL\_\_DNS\_\_/$localdns/g; s/\_\_PILLAR\_\_DNS\_\_DOMAIN\_\_/$domain/g; s/,\_\_PILLAR\_\_DNS\_\_SERVER\_\_//g; s/\_\_PILLAR\_\_CLUSTER\_\_DNS\_\_/$kubedns/g" nodelocaldns.yaml ``` In this mode, the `node-local-dns` pods listen only on ``. The `node-local-dns` interface cannot bind the kube-dns cluster IP since the interface used for IPVS loadbalancing already uses this address. `\_\_PILLAR\_\_UPSTREAM\_\_SERVERS\_\_` will be populated by the node-local-dns pods. \* Run `kubectl create -f nodelocaldns.yaml` \* If using kube-proxy in IPVS mode, `--cluster-dns` flag to kubelet needs to be modified to use `` that NodeLocal DNSCache is listening on. Otherwise, there is no need to modify the value of the `--cluster-dns` flag, since NodeLocal DNSCache listens on both the kube-dns service IP as well as ``. Once enabled, the `node-local-dns` Pods will run in the `kube-system` namespace on each of the cluster nodes. This Pod runs [CoreDNS](https://github.com/coredns/coredns) in cache mode, so all CoreDNS metrics exposed by the different plugins will be available on a per-node basis. You can disable this feature by removing the DaemonSet, using `kubectl delete -f `. You should also revert any changes you made to the kubelet configuration. ## StubDomains and Upstream server Configuration StubDomains and upstream servers specified in the `kube-dns` ConfigMap in the `kube-system` namespace are automatically picked up by `node-local-dns` pods. The ConfigMap contents need to follow the format shown in [the example](/docs/tasks/administer-cluster/dns-custom-nameservers/#example-1). The `node-local-dns` ConfigMap can also be modified directly with the stubDomain configuration in the Corefile format. Some cloud providers might not allow modifying `node-local-dns` ConfigMap directly. In those cases, the `kube-dns` ConfigMap can be updated. ## Setting memory limits The `node-local-dns` Pods use memory for storing cache entries and processing queries. Since they do not watch Kubernetes objects, the cluster size or the number of Services / EndpointSlices do not directly affect memory usage. Memory usage is influenced by the DNS query pattern. From [CoreDNS docs](https://github.com/coredns/deployment/blob/master/kubernetes/Scaling\_CoreDNS.md), > The default cache size is 10000 entries, which uses about 30 MB when completely filled. This would be the memory usage for each server block (if the cache gets completely filled). Memory usage can be reduced by specifying smaller cache sizes. The number of concurrent queries is linked to the memory demand, because each extra goroutine used for handling a query requires an amount of memory. You can set an upper limit using the `max\_concurrent` option in the forward plugin. If a `node-local-dns` Pod attempts to use more memory than is available (because of total system resources, or because of a configured [resource limit](/docs/concepts/configuration/manage-resources-containers/)), the operating system may shut down that pod's container. If this happens, the container that is terminated (“OOMKilled”) does not clean up the custom packet filtering rules that it previously added during startup. The `node-local-dns` container should get restarted (since managed as part of a DaemonSet), but this will lead to a brief DNS downtime each time that the container fails: the packet filtering rules direct DNS queries to a local Pod that is unhealthy. You can determine a suitable memory limit by running node-local-dns pods without a limit and measuring the peak usage. You can also set up and use a [VerticalPodAutoscaler](https://github.com/kubernetes/autoscaler/tree/master/vertical-pod-autoscaler) in \_recommender mode\_, and then check its recommendations.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/nodelocaldns.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/nodelocaldns.md
|
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] | 0.082326
|
{{< feature-state for\_k8s\_version="v1.22" state="alpha" >}} This document describes how to run Kubernetes Node components such as kubelet, CRI, OCI, and CNI without root privileges, by using a {{< glossary\_tooltip text="user namespace" term\_id="userns" >}}. This technique is also known as \_rootless mode\_. {{< note >}} This document describes how to run Kubernetes Node components (and hence pods) as a non-root user. If you are just looking for how to run a pod as a non-root user, see [SecurityContext](/docs/tasks/configure-pod-container/security-context/). {{< /note >}} ## {{% heading "prerequisites" %}} {{% version-check %}} \* [Enable Cgroup v2](https://rootlesscontaine.rs/getting-started/common/cgroup2/) \* [Enable systemd with user session](https://rootlesscontaine.rs/getting-started/common/login/) \* [Configure several sysctl values, depending on host Linux distribution](https://rootlesscontaine.rs/getting-started/common/sysctl/) \* [Ensure that your unprivileged user is listed in `/etc/subuid` and `/etc/subgid`](https://rootlesscontaine.rs/getting-started/common/subuid/) \* Enable the `KubeletInUserNamespace` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) ## Running Kubernetes inside Rootless Docker/Podman ### kind [kind](https://kind.sigs.k8s.io/) supports running Kubernetes inside Rootless Docker or Rootless Podman. See [Running kind with Rootless Docker](https://kind.sigs.k8s.io/docs/user/rootless/). ### minikube [minikube](https://minikube.sigs.k8s.io/) also supports running Kubernetes inside Rootless Docker or Rootless Podman. See the Minikube documentation: \* [Rootless Docker](https://minikube.sigs.k8s.io/docs/drivers/docker/) \* [Rootless Podman](https://minikube.sigs.k8s.io/docs/drivers/podman/) ## Running Kubernetes inside Unprivileged Containers {{% thirdparty-content %}} ### sysbox [Sysbox](https://github.com/nestybox/sysbox) is an open-source container runtime (similar to "runc") that supports running system-level workloads such as Docker and Kubernetes inside unprivileged containers isolated with the Linux user namespace. See [Sysbox Quick Start Guide: Kubernetes-in-Docker](https://github.com/nestybox/sysbox/blob/master/docs/quickstart/kind.md) for more info. Sysbox supports running Kubernetes inside unprivileged containers without requiring Cgroup v2 and without the `KubeletInUserNamespace` feature gate. It does this by exposing specially crafted `/proc` and `/sys` filesystems inside the container plus several other advanced OS virtualization techniques. ## Running Rootless Kubernetes directly on a host {{% thirdparty-content %}} ### K3s [K3s](https://k3s.io/) experimentally supports rootless mode. See [Running K3s with Rootless mode](https://rancher.com/docs/k3s/latest/en/advanced/#running-k3s-with-rootless-mode-experimental) for the usage. ### Usernetes [Usernetes](https://github.com/rootless-containers/usernetes) is a reference distribution of Kubernetes that can be installed under `$HOME` directory without the root privilege. Usernetes supports both containerd and CRI-O as CRI runtimes. Usernetes supports multi-node clusters using Flannel (VXLAN). See [the Usernetes repo](https://github.com/rootless-containers/usernetes) for the usage. ## Manually deploy a node that runs the kubelet in a user namespace {#userns-the-hard-way} This section provides hints for running Kubernetes in a user namespace manually. {{< note >}} This section is intended to be read by developers of Kubernetes distributions, not by end users. {{< /note >}} ### Creating a user namespace The first step is to create a {{< glossary\_tooltip text="user namespace" term\_id="userns" >}}. If you are trying to run Kubernetes in a user-namespaced container such as Rootless Docker/Podman or LXC/LXD, you are all set, and you can go to the next subsection. Otherwise you have to create a user namespace by yourself, by calling `unshare(2)` with `CLONE\_NEWUSER`. A user namespace can be also unshared by using command line tools such as: - [`unshare(1)`](https://man7.org/linux/man-pages/man1/unshare.1.html) - [RootlessKit](https://github.com/rootless-containers/rootlesskit) - [become-root](https://github.com/giuseppe/become-root) After unsharing the user namespace, you will also have to unshare other namespaces such as mount namespace. You do \*not\* need to call `chroot()` nor `pivot\_root()` after unsharing the mount namespace, however, you have to mount writable filesystems on several directories \*in\* the namespace. At least, the following directories need to be writable \*in\* the namespace (not \*outside\* the namespace): - `/etc` - `/run` - `/var/logs` - `/var/lib/kubelet` - `/var/lib/cni` - `/var/lib/containerd` (for containerd) - `/var/lib/containers` (for CRI-O) ### Creating a delegated cgroup tree In addition to the user namespace, you also need to have a writable cgroup tree with cgroup v2. {{< note >}} Kubernetes support for running Node components in user namespaces requires cgroup v2. Cgroup v1 is not supported. {{< /note >}} If you are trying to run Kubernetes in Rootless Docker/Podman or LXC/LXD on a systemd-based host,
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
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] | 0.118074
|
also need to have a writable cgroup tree with cgroup v2. {{< note >}} Kubernetes support for running Node components in user namespaces requires cgroup v2. Cgroup v1 is not supported. {{< /note >}} If you are trying to run Kubernetes in Rootless Docker/Podman or LXC/LXD on a systemd-based host, you are all set. Otherwise you have to create a systemd unit with `Delegate=yes` property to delegate a cgroup tree with writable permission. On your node, systemd must already be configured to allow delegation; for more details, see [cgroup v2](https://rootlesscontaine.rs/getting-started/common/cgroup2/) in the Rootless Containers documentation. ### Configuring network {{% thirdparty-content %}} The network namespace of the Node components has to have a non-loopback interface, which can be for example configured with [slirp4netns](https://github.com/rootless-containers/slirp4netns), [VPNKit](https://github.com/moby/vpnkit), or [lxc-user-nic(1)](https://www.man7.org/linux/man-pages/man1/lxc-user-nic.1.html). The network namespaces of the Pods can be configured with regular CNI plugins. For multi-node networking, Flannel (VXLAN, 8472/UDP) is known to work. Ports such as the kubelet port (10250/TCP) and `NodePort` service ports have to be exposed from the Node network namespace to the host with an external port forwarder, such as RootlessKit, slirp4netns, or [socat(1)](https://linux.die.net/man/1/socat). You can use the port forwarder from K3s. See [Running K3s in Rootless Mode](https://rancher.com/docs/k3s/latest/en/advanced/#known-issues-with-rootless-mode) for more details. The implementation can be found in [the `pkg/rootlessports` package](https://github.com/k3s-io/k3s/blob/v1.22.3+k3s1/pkg/rootlessports/controller.go) of k3s. ### Configuring CRI The kubelet relies on a container runtime. You should deploy a container runtime such as containerd or CRI-O and ensure that it is running within the user namespace before the kubelet starts. {{< tabs name="cri" >}} {{% tab name="containerd" %}} Running CRI plugin of containerd in a user namespace is supported since containerd 1.4. Running containerd within a user namespace requires the following configurations. ```toml version = 2 [plugins."io.containerd.grpc.v1.cri"] # Disable AppArmor disable\_apparmor = true # Ignore an error during setting oom\_score\_adj restrict\_oom\_score\_adj = true # Disable hugetlb cgroup v2 controller (because systemd does not support delegating hugetlb controller) disable\_hugetlb\_controller = true [plugins."io.containerd.grpc.v1.cri".containerd] # Using non-fuse overlayfs is also possible for kernel >= 5.11, but requires SELinux to be disabled snapshotter = "fuse-overlayfs" [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc.options] # We use cgroupfs that is delegated by systemd, so we do not use SystemdCgroup driver # (unless you run another systemd in the namespace) SystemdCgroup = false ``` The default path of the configuration file is `/etc/containerd/config.toml`. The path can be specified with `containerd -c /path/to/containerd/config.toml`. {{% /tab %}} {{% tab name="CRI-O" %}} Running CRI-O in a user namespace is supported since CRI-O 1.22. CRI-O requires an environment variable `\_CRIO\_ROOTLESS=1` to be set. The following configurations are also recommended: ```toml [crio] storage\_driver = "overlay" # Using non-fuse overlayfs is also possible for kernel >= 5.11, but requires SELinux to be disabled storage\_option = ["overlay.mount\_program=/usr/local/bin/fuse-overlayfs"] [crio.runtime] # We use cgroupfs that is delegated by systemd, so we do not use "systemd" driver # (unless you run another systemd in the namespace) cgroup\_manager = "cgroupfs" ``` The default path of the configuration file is `/etc/crio/crio.conf`. The path can be specified with `crio --config /path/to/crio/crio.conf`. {{% /tab %}} {{< /tabs >}} ### Configuring kubelet Running kubelet in a user namespace requires the following configuration: ```yaml apiVersion: kubelet.config.k8s.io/v1beta1 kind: KubeletConfiguration featureGates: KubeletInUserNamespace: true # We use cgroupfs that is delegated by systemd, so we do not use "systemd" driver # (unless you run another systemd in the namespace) cgroupDriver: "cgroupfs" ``` When the `KubeletInUserNamespace` feature gate is enabled, the kubelet ignores errors that may happen during setting the following sysctl values on the node. - `vm.overcommit\_memory` - `vm.panic\_on\_oom` - `kernel.panic` - `kernel.panic\_on\_oops` - `kernel.keys.root\_maxkeys` - `kernel.keys.root\_maxbytes`. Within a user namespace, the kubelet also ignores any error raised from trying to open `/dev/kmsg`. This feature gate also
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
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] | 0.009945
|
is enabled, the kubelet ignores errors that may happen during setting the following sysctl values on the node. - `vm.overcommit\_memory` - `vm.panic\_on\_oom` - `kernel.panic` - `kernel.panic\_on\_oops` - `kernel.keys.root\_maxkeys` - `kernel.keys.root\_maxbytes`. Within a user namespace, the kubelet also ignores any error raised from trying to open `/dev/kmsg`. This feature gate also allows kube-proxy to ignore an error during setting `RLIMIT\_NOFILE`. The `KubeletInUserNamespace` feature gate was introduced in Kubernetes v1.22 with "alpha" status. Running kubelet in a user namespace without using this feature gate is also possible by mounting a specially crafted proc filesystem (as done by [Sysbox](https://github.com/nestybox/sysbox)), but not officially supported. ### Configuring kube-proxy Running kube-proxy in a user namespace requires the following configuration: ```yaml apiVersion: kubeproxy.config.k8s.io/v1alpha1 kind: KubeProxyConfiguration mode: "iptables" # or "userspace" conntrack: # Skip setting sysctl value "net.netfilter.nf\_conntrack\_max" maxPerCore: 0 # Skip setting "net.netfilter.nf\_conntrack\_tcp\_timeout\_established" tcpEstablishedTimeout: 0s # Skip setting "net.netfilter.nf\_conntrack\_tcp\_timeout\_close" tcpCloseWaitTimeout: 0s ``` ## Caveats - Most of "non-local" volume drivers such as `nfs` and `iscsi` do not work. Local volumes like `local`, `hostPath`, `emptyDir`, `configMap`, `secret`, and `downwardAPI` are known to work. - Some CNI plugins may not work. Flannel (VXLAN) is known to work. For more on this, see the [Caveats and Future work](https://rootlesscontaine.rs/caveats/) page on the rootlesscontaine.rs website. ## {{% heading "seealso" %}} - [rootlesscontaine.rs](https://rootlesscontaine.rs/) - [Rootless Containers 2020 (KubeCon NA 2020)](https://www.slideshare.net/AkihiroSuda/kubecon-na-2020-containerd-rootless-containers-2020) - [Running kind with Rootless Docker](https://kind.sigs.k8s.io/docs/user/rootless/) - [Usernetes](https://github.com/rootless-containers/usernetes) - [Running K3s with rootless mode](https://rancher.com/docs/k3s/latest/en/advanced/#running-k3s-with-rootless-mode-experimental) - [KEP-2033: Kubelet-in-UserNS (aka Rootless mode)](https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/2033-kubelet-in-userns-aka-rootless)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-in-userns.md
|
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] | 0.132849
|
{{< glossary\_definition term\_id="etcd" length="all" prepend="etcd is a ">}} ## {{% heading "prerequisites" %}} Before you follow steps in this page to deploy, manage, back up or restore etcd, you need to understand the typical expectations for operating an etcd cluster. Refer to the [etcd documentation](https://etcd.io/docs/) for more context. Key details include: \* The minimum recommended etcd versions to run in production are `3.4.29+` and `3.5.11+`. \* etcd is a leader-based distributed system. Ensure that the leader periodically send heartbeats on time to all followers to keep the cluster stable. \* You should run etcd as a cluster with an odd number of members. \* Aim to ensure that no resource starvation occurs. Performance and stability of the cluster is sensitive to network and disk I/O. Any resource starvation can lead to heartbeat timeout, causing instability of the cluster. An unstable etcd indicates that no leader is elected. Under such circumstances, a cluster cannot make any changes to its current state, which implies no new pods can be scheduled. ### Resource requirements for etcd Operating etcd with limited resources is suitable only for testing purposes. For deploying in production, advanced hardware configuration is required. Before deploying etcd in production, see [resource requirement reference](https://etcd.io/docs/current/op-guide/hardware/#example-hardware-configurations). Keeping etcd clusters stable is critical to the stability of Kubernetes clusters. Therefore, run etcd clusters on dedicated machines or isolated environments for [guaranteed resource requirements](https://etcd.io/docs/current/op-guide/hardware/). ### Tools Depending on which specific outcome you're working on, you will need the `etcdctl` tool or the `etcdutl` tool (you may need both). ## Understanding etcdctl and etcdutl `etcdctl` and `etcdutl` are command-line tools used to interact with etcd clusters, but they serve different purposes: - `etcdctl`: This is the primary command-line client for interacting with etcd over a network. It is used for day-to-day operations such as managing keys and values, administering the cluster, checking health, and more. - `etcdutl`: This is an administration utility designed to operate directly on etcd data files, including migrating data between etcd versions, defragmenting the database, restoring snapshots, and validating data consistency. For network operations, `etcdctl` should be used. For more information on `etcdutl`, you can refer to the [etcd recovery documentation](https://etcd.io/docs/v3.5/op-guide/recovery/). ## Starting etcd clusters This section covers starting a single-node and multi-node etcd cluster. This guide assumes that `etcd` is already installed. ### Single-node etcd cluster Use a single-node etcd cluster only for testing purposes. 1. Run the following: ```sh etcd --listen-client-urls=http://$PRIVATE\_IP:2379 \ --advertise-client-urls=http://$PRIVATE\_IP:2379 ``` 2. Start the Kubernetes API server with the flag `--etcd-servers=$PRIVATE\_IP:2379`. Make sure `PRIVATE\_IP` is set to your etcd client IP. ### Multi-node etcd cluster For durability and high availability, run etcd as a multi-node cluster in production and back it up periodically. A five-member cluster is recommended in production. For more information, see [FAQ documentation](https://etcd.io/docs/current/faq/#what-is-failure-tolerance). As you're using Kubernetes, you have the option to run etcd as a container inside one or more Pods. The `kubeadm` tool sets up etcd {{< glossary\_tooltip text="static pods" term\_id="static-pod" >}} by default, or you can deploy a [separate cluster](/docs/setup/production-environment/tools/kubeadm/setup-ha-etcd-with-kubeadm/) and instruct kubeadm to use that etcd cluster as the control plane's backing store. You configure an etcd cluster either by static member information or by dynamic discovery. For more information on clustering, see [etcd clustering documentation](https://etcd.io/docs/current/op-guide/clustering/). For an example, consider a five-member etcd cluster running with the following client URLs: `http://$IP1:2379`, `http://$IP2:2379`, `http://$IP3:2379`, `http://$IP4:2379`, and `http://$IP5:2379`. To start a Kubernetes API server: 1. Run the following: ```shell etcd --listen-client-urls=http://$IP1:2379,http://$IP2:2379,http://$IP3:2379,http://$IP4:2379,http://$IP5:2379 --advertise-client-urls=http://$IP1:2379,http://$IP2:2379,http://$IP3:2379,http://$IP4:2379,http://$IP5:2379 ``` 2. Start the Kubernetes API servers with the flag `--etcd-servers=$IP1:2379,$IP2:2379,$IP3:2379,$IP4:2379,$IP5:2379`. Make sure the `IP` variables are set to your client IP addresses. ### Multi-node etcd cluster with load balancer To
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
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] | 0.09827
|
`http://$IP2:2379`, `http://$IP3:2379`, `http://$IP4:2379`, and `http://$IP5:2379`. To start a Kubernetes API server: 1. Run the following: ```shell etcd --listen-client-urls=http://$IP1:2379,http://$IP2:2379,http://$IP3:2379,http://$IP4:2379,http://$IP5:2379 --advertise-client-urls=http://$IP1:2379,http://$IP2:2379,http://$IP3:2379,http://$IP4:2379,http://$IP5:2379 ``` 2. Start the Kubernetes API servers with the flag `--etcd-servers=$IP1:2379,$IP2:2379,$IP3:2379,$IP4:2379,$IP5:2379`. Make sure the `IP` variables are set to your client IP addresses. ### Multi-node etcd cluster with load balancer To run a load balancing etcd cluster: 1. Set up an etcd cluster. 2. Configure a load balancer in front of the etcd cluster. For example, let the address of the load balancer be `$LB`. 3. Start Kubernetes API Servers with the flag `--etcd-servers=$LB:2379`. ## Securing etcd clusters Access to etcd is equivalent to root permission in the cluster so ideally only the API server should have access to it. Considering the sensitivity of the data, it is recommended to grant permission to only those nodes that require access to etcd clusters. To secure etcd, either set up firewall rules or use the security features provided by etcd. etcd security features depend on x509 Public Key Infrastructure (PKI). To begin, establish secure communication channels by generating a key and certificate pair. For example, use key pairs `peer.key` and `peer.cert` for securing communication between etcd members, and `client.key` and `client.cert` for securing communication between etcd and its clients. See the [example scripts](https://github.com/coreos/etcd/tree/master/hack/tls-setup) provided by the etcd project to generate key pairs and CA files for client authentication. ### Securing communication To configure etcd with secure peer communication, specify flags `--peer-key-file=peer.key` and `--peer-cert-file=peer.cert`, and use HTTPS as the URL schema. Similarly, to configure etcd with secure client communication, specify flags `--key=k8sclient.key` and `--cert=k8sclient.cert`, and use HTTPS as the URL schema. Here is an example on a client command that uses secure communication: ``` ETCDCTL\_API=3 etcdctl --endpoints 10.2.0.9:2379 \ --cert=/etc/kubernetes/pki/etcd/server.crt \ --key=/etc/kubernetes/pki/etcd/server.key \ --cacert=/etc/kubernetes/pki/etcd/ca.crt \ member list ``` ### Limiting access of etcd clusters After configuring secure communication, restrict the access of the etcd cluster to only the Kubernetes API servers using TLS authentication. For example, consider key pairs `k8sclient.key` and `k8sclient.cert` that are trusted by the CA `etcd.ca`. When etcd is configured with `--client-cert-auth` along with TLS, it verifies the certificates from clients by using system CAs or the CA passed in by `--trusted-ca-file` flag. Specifying flags `--client-cert-auth=true` and `--trusted-ca-file=etcd.ca` will restrict the access to clients with the certificate `k8sclient.cert`. Once etcd is configured correctly, only clients with valid certificates can access it. To give Kubernetes API servers the access, configure them with the flags `--etcd-certfile=k8sclient.cert`, `--etcd-keyfile=k8sclient.key` and `--etcd-cafile=ca.cert`. {{< note >}} etcd authentication is not planned for Kubernetes. {{< /note >}} ## Replacing a failed etcd member etcd cluster achieves high availability by tolerating minor member failures. However, to improve the overall health of the cluster, replace failed members immediately. When multiple members fail, replace them one by one. Replacing a failed member involves two steps: removing the failed member and adding a new member. Though etcd keeps unique member IDs internally, it is recommended to use a unique name for each member to avoid human errors. For example, consider a three-member etcd cluster. Let the URLs be, `member1=http://10.0.0.1`, `member2=http://10.0.0.2`, and `member3=http://10.0.0.3`. When `member1` fails, replace it with `member4=http://10.0.0.4`. 1. Get the member ID of the failed `member1`: ```shell etcdctl --endpoints=http://10.0.0.2,http://10.0.0.3 member list ``` The following message is displayed: ```console 8211f1d0f64f3269, started, member1, http://10.0.0.1:2380, http://10.0.0.1:2379 91bc3c398fb3c146, started, member2, http://10.0.0.2:2380, http://10.0.0.2:2379 fd422379fda50e48, started, member3, http://10.0.0.3:2380, http://10.0.0.3:2379 ``` 1. Do either of the following: 1. If each Kubernetes API server is configured to communicate with all etcd members, remove the failed member from the `--etcd-servers` flag, then restart each Kubernetes API server. 1. If each Kubernetes API server communicates with a single etcd member,
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
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|
member3, http://10.0.0.3:2380, http://10.0.0.3:2379 ``` 1. Do either of the following: 1. If each Kubernetes API server is configured to communicate with all etcd members, remove the failed member from the `--etcd-servers` flag, then restart each Kubernetes API server. 1. If each Kubernetes API server communicates with a single etcd member, then stop the Kubernetes API server that communicates with the failed etcd. 1. Stop the etcd server on the broken node. It is possible that other clients besides the Kubernetes API server are causing traffic to etcd and it is desirable to stop all traffic to prevent writes to the data directory. 1. Remove the failed member: ```shell etcdctl member remove 8211f1d0f64f3269 ``` The following message is displayed: ```console Removed member 8211f1d0f64f3269 from cluster ``` 1. Add the new member: ```shell etcdctl member add member4 --peer-urls=http://10.0.0.4:2380 ``` The following message is displayed: ```console Member 2be1eb8f84b7f63e added to cluster ef37ad9dc622a7c4 ``` 1. Start the newly added member on a machine with the IP `10.0.0.4`: ```shell export ETCD\_NAME="member4" export ETCD\_INITIAL\_CLUSTER="member2=http://10.0.0.2:2380,member3=http://10.0.0.3:2380,member4=http://10.0.0.4:2380" export ETCD\_INITIAL\_CLUSTER\_STATE=existing etcd [flags] ``` 1. Do either of the following: 1. If each Kubernetes API server is configured to communicate with all etcd members, add the newly added member to the `--etcd-servers` flag, then restart each Kubernetes API server. 1. If each Kubernetes API server communicates with a single etcd member, start the Kubernetes API server that was stopped in step 2. Then configure Kubernetes API server clients to again route requests to the Kubernetes API server that was stopped. This can often be done by configuring a load balancer. For more information on cluster reconfiguration, see [etcd reconfiguration documentation](https://etcd.io/docs/current/op-guide/runtime-configuration/#remove-a-member). ## Backing up an etcd cluster All Kubernetes objects are stored in etcd. Periodically backing up the etcd cluster data is important to recover Kubernetes clusters under disaster scenarios, such as losing all control plane nodes. The snapshot file contains all the Kubernetes state and critical information. In order to keep the sensitive Kubernetes data safe, encrypt the snapshot files. Backing up an etcd cluster can be accomplished in two ways: etcd built-in snapshot and volume snapshot. ### Built-in snapshot etcd supports built-in snapshot. A snapshot may either be created from a live member with the `etcdctl snapshot save` command or by copying the `member/snap/db` file from an etcd [data directory](https://etcd.io/docs/current/op-guide/configuration/#--data-dir) that is not currently used by an etcd process. Creating the snapshot will not affect the performance of the member. Below is an example for creating a snapshot of the keyspace served by `$ENDPOINT` to the file `snapshot.db`: ```shell ETCDCTL\_API=3 etcdctl --endpoints $ENDPOINT snapshot save snapshot.db ``` Verify the snapshot: {{< tabs name="etcd\_verify\_snapshot" >}} {{% tab name="Use etcdutl" %}} The below example depicts the usage of the `etcdutl` tool for verifying a snapshot: ```shell etcdutl --write-out=table snapshot status snapshot.db ``` This should generate an output resembling the example provided below: ```console +----------+----------+------------+------------+ | HASH | REVISION | TOTAL KEYS | TOTAL SIZE | +----------+----------+------------+------------+ | fe01cf57 | 10 | 7 | 2.1 MB | +----------+----------+------------+------------+ ``` {{% /tab %}} {{% tab name="Use etcdctl (Deprecated)" %}} {{< note >}} The usage of `etcdctl snapshot status` has been \*\*deprecated\*\* since etcd v3.5.x and is slated for removal from etcd v3.6. It is recommended to utilize [`etcdutl`](https://github.com/etcd-io/etcd/blob/main/etcdutl/README.md) instead. {{< /note >}} The below example depicts the usage of the `etcdctl` tool for verifying a snapshot: ```shell export ETCDCTL\_API=3 etcdctl --write-out=table snapshot status snapshot.db ``` This should generate an output resembling the example provided below: ```console Deprecated: Use `etcdutl snapshot status` instead. +----------+----------+------------+------------+ | HASH | REVISION | TOTAL KEYS | TOTAL SIZE | +----------+----------+------------+------------+ | fe01cf57 | 10 | 7 | 2.1 MB
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
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] | 0.014506
|
a snapshot: ```shell export ETCDCTL\_API=3 etcdctl --write-out=table snapshot status snapshot.db ``` This should generate an output resembling the example provided below: ```console Deprecated: Use `etcdutl snapshot status` instead. +----------+----------+------------+------------+ | HASH | REVISION | TOTAL KEYS | TOTAL SIZE | +----------+----------+------------+------------+ | fe01cf57 | 10 | 7 | 2.1 MB | +----------+----------+------------+------------+ ``` {{% /tab %}} {{< /tabs >}} ### Volume snapshot If etcd is running on a storage volume that supports backup, such as Amazon Elastic Block Store, back up etcd data by creating a snapshot of the storage volume. ### Snapshot using etcdctl options We can also create the snapshot using various options given by etcdctl. For example: ```shell ETCDCTL\_API=3 etcdctl -h ``` will list various options available from etcdctl. For example, you can create a snapshot by specifying the endpoint, certificates and key as shown below: ```shell ETCDCTL\_API=3 etcdctl --endpoints=https://127.0.0.1:2379 \ --cacert= --cert= --key= \ snapshot save ``` where `trusted-ca-file`, `cert-file` and `key-file` can be obtained from the description of the etcd Pod. ## Scaling out etcd clusters Scaling out etcd clusters increases availability by trading off performance. Scaling does not increase cluster performance nor capability. A general rule is not to scale out or in etcd clusters. Do not configure any auto scaling groups for etcd clusters. It is strongly recommended to always run a static five-member etcd cluster for production Kubernetes clusters at any officially supported scale. A reasonable scaling is to upgrade a three-member cluster to a five-member one, when more reliability is desired. See [etcd reconfiguration documentation](https://etcd.io/docs/current/op-guide/runtime-configuration/#remove-a-member) for information on how to add members into an existing cluster. ## Restoring an etcd cluster {{< caution >}} If any API servers are running in your cluster, you should not attempt to restore instances of etcd. Instead, follow these steps to restore etcd: - stop \*all\* API server instances - restore state in all etcd instances - restart all API server instances The Kubernetes project also recommends restarting Kubernetes components (`kube-scheduler`, `kube-controller-manager`, `kubelet`) to ensure that they don't rely on some stale data. In practice the restore takes a bit of time. During the restoration, critical components will lose leader lock and restart themselves. {{< /caution >}} etcd supports restoring from snapshots that are taken from an etcd process of the [major.minor](https://semver.org/) version. Restoring a version from a different patch version of etcd is also supported. A restore operation is employed to recover the data of a failed cluster. Before starting the restore operation, a snapshot file must be present. It can either be a snapshot file from a previous backup operation, or from a remaining [data directory](https://etcd.io/docs/current/op-guide/configuration/#--data-dir). {{< tabs name="etcd\_restore" >}} {{% tab name="Use etcdutl" %}} When restoring the cluster using [`etcdutl`](https://github.com/etcd-io/etcd/blob/main/etcdutl/README.md), use the `--data-dir` option to specify to which folder the cluster should be restored: ```shell etcdutl --data-dir snapshot restore snapshot.db ``` where `` is a directory that will be created during the restore process. {{% /tab %}} {{% tab name="Use etcdctl (Deprecated)" %}} {{< note >}} The usage of `etcdctl` for restoring has been \*\*deprecated\*\* since etcd v3.5.x and is slated for removal from etcd v3.6. It is recommended to utilize [`etcdutl`](https://github.com/etcd-io/etcd/blob/main/etcdutl/README.md) instead. {{< /note >}} The below example depicts the usage of the `etcdctl` tool for the restore operation: ```shell export ETCDCTL\_API=3 etcdctl --data-dir snapshot restore snapshot.db ``` If `` is the same folder as before, delete it and stop the etcd process before restoring the cluster. Otherwise, change etcd configuration and restart the etcd process after restoration to have it use the new data directory: first change `/etc/kubernetes/manifests/etcd.yaml`'s `volumes.hostPath.path` for `name: etcd-data` to ``, then execute `kubectl -n kube-system delete
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
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] | -0.039989
|
the same folder as before, delete it and stop the etcd process before restoring the cluster. Otherwise, change etcd configuration and restart the etcd process after restoration to have it use the new data directory: first change `/etc/kubernetes/manifests/etcd.yaml`'s `volumes.hostPath.path` for `name: etcd-data` to ``, then execute `kubectl -n kube-system delete pod ` or `systemctl restart kubelet.service` (or both). {{% /tab %}} {{< /tabs >}} For more information and examples on restoring a cluster from a snapshot file, see [etcd disaster recovery documentation](https://etcd.io/docs/current/op-guide/recovery/#restoring-a-cluster). If the access URLs of the restored cluster are changed from the previous cluster, the Kubernetes API server must be reconfigured accordingly. In this case, restart Kubernetes API servers with the flag `--etcd-servers=$NEW\_ETCD\_CLUSTER` instead of the flag `--etcd-servers=$OLD\_ETCD\_CLUSTER`. Replace `$NEW\_ETCD\_CLUSTER` and `$OLD\_ETCD\_CLUSTER` with the respective IP addresses. If a load balancer is used in front of an etcd cluster, you might need to update the load balancer instead. If the majority of etcd members have permanently failed, the etcd cluster is considered failed. In this scenario, Kubernetes cannot make any changes to its current state. Although the scheduled pods might continue to run, no new pods can be scheduled. In such cases, recover the etcd cluster and potentially reconfigure Kubernetes API servers to fix the issue. ## Upgrading etcd clusters {{< caution >}} Before you start an upgrade, back up your etcd cluster first. {{< /caution >}} For details on etcd upgrade, refer to the [etcd upgrades](https://etcd.io/docs/latest/upgrades/) documentation. ## Maintaining etcd clusters For more details on etcd maintenance, please refer to the [etcd maintenance](https://etcd.io/docs/latest/op-guide/maintenance/) documentation. ### Cluster defragmentation {{% thirdparty-content single="true" %}} Defragmentation is an expensive operation, so it should be executed as infrequently as possible. On the other hand, it's also necessary to make sure any etcd member will not exceed the storage quota. The Kubernetes project recommends that when you perform defragmentation, you use a tool such as [etcd-defrag](https://github.com/ahrtr/etcd-defrag). You can also run the defragmentation tool as a Kubernetes CronJob, to make sure that defragmentation happens regularly. See [`etcd-defrag-cronjob.yaml`](https://github.com/ahrtr/etcd-defrag/blob/main/doc/etcd-defrag-cronjob.yaml) for details.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/configure-upgrade-etcd.md
|
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] | 0.040164
|
This page explains how to configure your DNS {{< glossary\_tooltip text="Pod(s)" term\_id="pod" >}} and customize the DNS resolution process in your cluster. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} Your cluster must be running the CoreDNS add-on. {{% version-check %}} ## Introduction DNS is a built-in Kubernetes service launched automatically using the \_addon manager\_ [cluster add-on](https://github.com/kubernetes/kubernetes/blob/master/cluster/addons/addon-manager/README.md). {{< note >}} The CoreDNS Service is named `kube-dns` in the `metadata.name` field. The intent is to ensure greater interoperability with workloads that relied on the legacy `kube-dns` Service name to resolve addresses internal to the cluster. Using a Service named `kube-dns` abstracts away the implementation detail of which DNS provider is running behind that common name. {{< /note >}} If you are running CoreDNS as a Deployment, it will typically be exposed as a Kubernetes Service with a static IP address. The kubelet passes DNS resolver information to each container with the `--cluster-dns=` flag. DNS names also need domains. You configure the local domain in the kubelet with the flag `--cluster-domain=`. The DNS server supports forward lookups (A and AAAA records), port lookups (SRV records), reverse IP address lookups (PTR records), and more. For more information, see [DNS for Services and Pods](/docs/concepts/services-networking/dns-pod-service/). If a Pod's `dnsPolicy` is set to `default`, it inherits the name resolution configuration from the node that the Pod runs on. The Pod's DNS resolution should behave the same as the node. But see [Known issues](/docs/tasks/administer-cluster/dns-debugging-resolution/#known-issues). If you don't want this, or if you want a different DNS config for pods, you can use the kubelet's `--resolv-conf` flag. Set this flag to "" to prevent Pods from inheriting DNS. Set it to a valid file path to specify a file other than `/etc/resolv.conf` for DNS inheritance. ## CoreDNS CoreDNS is a general-purpose authoritative DNS server that can serve as cluster DNS, complying with the [DNS specifications](https://github.com/kubernetes/dns/blob/master/docs/specification.md). ### CoreDNS ConfigMap options CoreDNS is a DNS server that is modular and pluggable, with plugins adding new functionalities. The CoreDNS server can be configured by maintaining a [Corefile](https://coredns.io/2017/07/23/corefile-explained/), which is the CoreDNS configuration file. As a cluster administrator, you can modify the {{< glossary\_tooltip text="ConfigMap" term\_id="configmap" >}} for the CoreDNS Corefile to change how DNS service discovery behaves for that cluster. In Kubernetes, CoreDNS is installed with the following default Corefile configuration: ```yaml apiVersion: v1 kind: ConfigMap metadata: name: coredns namespace: kube-system data: Corefile: | .:53 { errors health { lameduck 5s } ready kubernetes cluster.local in-addr.arpa ip6.arpa { pods insecure fallthrough in-addr.arpa ip6.arpa ttl 30 } prometheus :9153 forward . /etc/resolv.conf cache 30 loop reload loadbalance } ``` The Corefile configuration includes the following [plugins](https://coredns.io/plugins/) of CoreDNS: \* [errors](https://coredns.io/plugins/errors/): Errors are logged to stdout. \* [health](https://coredns.io/plugins/health/): Health of CoreDNS is reported to `http://localhost:8080/health`. In this extended syntax `lameduck` will make the process unhealthy then wait for 5 seconds before the process is shut down. \* [ready](https://coredns.io/plugins/ready/): An HTTP endpoint on port 8181 will return 200 OK, when all plugins that are able to signal readiness have done so. \* [kubernetes](https://coredns.io/plugins/kubernetes/): CoreDNS will reply to DNS queries based on IP of the Services and Pods. You can find [more details](https://coredns.io/plugins/kubernetes/) about this plugin on the CoreDNS website. - `ttl` allows you to set a custom TTL for responses. The default is 5 seconds. The minimum TTL allowed is 0 seconds, and the maximum is capped at 3600 seconds. Setting TTL to 0 will prevent records from being cached. - The `pods insecure` option is provided for backward compatibility with `kube-dns`. - You can use the `pods verified` option, which returns an A record only if there exists a pod in the
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/dns-custom-nameservers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/dns-custom-nameservers.md
|
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] | 0.120153
|
the maximum is capped at 3600 seconds. Setting TTL to 0 will prevent records from being cached. - The `pods insecure` option is provided for backward compatibility with `kube-dns`. - You can use the `pods verified` option, which returns an A record only if there exists a pod in the same namespace with a matching IP. - The `pods disabled` option can be used if you don't use pod records. \* [prometheus](https://coredns.io/plugins/metrics/): Metrics of CoreDNS are available at `http://localhost:9153/metrics` in the [Prometheus](https://prometheus.io/) format (also known as OpenMetrics). \* [forward](https://coredns.io/plugins/forward/): Any queries that are not within the Kubernetes cluster domain are forwarded to predefined resolvers (/etc/resolv.conf). \* [cache](https://coredns.io/plugins/cache/): This enables a frontend cache. \* [loop](https://coredns.io/plugins/loop/): Detects simple forwarding loops and halts the CoreDNS process if a loop is found. \* [reload](https://coredns.io/plugins/reload): Allows automatic reload of a changed Corefile. After you edit the ConfigMap configuration, allow two minutes for your changes to take effect. \* [loadbalance](https://coredns.io/plugins/loadbalance): This is a round-robin DNS loadbalancer that randomizes the order of A, AAAA, and MX records in the answer. You can modify the default CoreDNS behavior by modifying the ConfigMap. ### Configuration of Stub-domain and upstream nameserver using CoreDNS CoreDNS has the ability to configure stub-domains and upstream nameservers using the [forward plugin](https://coredns.io/plugins/forward/). #### Example If a cluster operator has a [Consul](https://www.consul.io/) domain server located at "10.150.0.1", and all Consul names have the suffix ".consul.local". To configure it in CoreDNS, the cluster administrator creates the following stanza in the CoreDNS ConfigMap. ``` consul.local:53 { errors cache 30 forward . 10.150.0.1 } ``` To explicitly force all non-cluster DNS lookups to go through a specific nameserver at 172.16.0.1, point the `forward` to the nameserver instead of `/etc/resolv.conf` ``` forward . 172.16.0.1 ``` The final ConfigMap along with the default `Corefile` configuration looks like: ```yaml apiVersion: v1 kind: ConfigMap metadata: name: coredns namespace: kube-system data: Corefile: | .:53 { errors health kubernetes cluster.local in-addr.arpa ip6.arpa { pods insecure fallthrough in-addr.arpa ip6.arpa } prometheus :9153 forward . 172.16.0.1 cache 30 loop reload loadbalance } consul.local:53 { errors cache 30 forward . 10.150.0.1 } ``` {{< note >}} CoreDNS does not support FQDNs for stub-domains and nameservers (eg: "ns.foo.com"). During translation, all FQDN nameservers will be omitted from the CoreDNS config. {{< /note >}} ## {{% heading "whatsnext" %}} - Read [Debugging DNS Resolution](/docs/tasks/administer-cluster/dns-debugging-resolution/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/dns-custom-nameservers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/dns-custom-nameservers.md
|
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|
{{< feature-state feature\_gate\_name="MemoryManager" >}} The Kubernetes \*Memory Manager\* enables the feature of guaranteed memory (and hugepages) allocation for pods in the `Guaranteed` {{< glossary\_tooltip text="QoS class" term\_id="qos-class" >}}. The Memory Manager employs a hint generation protocol to yield the most suitable NUMA affinity for a pod. The Memory Manager feeds the central manager (\*Topology Manager\*) with these affinity hints. Based on both the hints and Topology Manager policy, the pod is rejected or admitted to the node. Moreover, the Memory Manager ensures that the memory which a pod requests is allocated from a minimum number of NUMA nodes. For background about memory resources for Pods, read [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/). ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} If you are running an older version of Kubernetes, check the documentation for the version of Kubernetes you are running. ### Resource alignment prerequisites To align memory resources with other requested resources in a Pod spec: - the CPU Manager should be enabled and proper CPU Manager policy should be configured on a Node. See [control CPU Management Policies](/docs/tasks/administer-cluster/cpu-management-policies/); - the Topology Manager should be enabled and proper Topology Manager policy should be configured on a Node. See [control Topology Management Policies](/docs/tasks/administer-cluster/topology-manager/). ### Windows support {{< feature-state feature\_gate\_name="WindowsCPUAndMemoryAffinity" >}} Windows support can be enabled via the `WindowsCPUAndMemoryAffinity` feature gate and it requires support in the container runtime. Only the [None](#policy-none) and [BestEffort](#policy-best-effort) policies are supported on Windows. ## How does the Memory Manager operate? For Linux nodes, the Memory Manager offers the guaranteed memory (and hugepages) allocation for Pods in Guaranteed QoS class. To immediately put the Memory Manager into operation follow the guidelines in the section [Memory Manager configuration](#memory-manager-configuration), and subsequently, prepare and deploy a `Guaranteed` Pod as illustrated in the section [Placing a Pod in the Guaranteed QoS class](#placing-a-pod-in-the-guaranteed-qos-class). The Memory Manager is a hint provider, and it provides topology hints for the Topology Manager which then aligns the requested resources according to these topology hints. On Linux, it also enforces `cgroups` (specifically, `cpuset.mems`) for Pods. The complete flow diagram concerning pod admission and deployment process is illustrated below:  During this process, the Memory Manager updates its internal counters stored in [Node Map and Memory Maps][2] to manage guaranteed memory allocation. The memory manager activates during kubelet startup if a node administrator configures `reservedMemory` for the kubelet (section [Reserved memory configuration](#reserved-memory-flag)). In this case, the kubelet updates its node map to reflect this reservation. When the `Static` policy is configured, you \*\*must\*\* configure reserved memory for the node (for example, with the `reservedMemory` configuration field in the kubelet configuration). An important topic in the context of Memory Manager operation is the management of NUMA groups. Each time pod's memory request is in excess of single NUMA node capacity, the Memory Manager attempts to create a group that comprises several NUMA nodes and that features extended memory capacity. ## Memory Manager configuration Other Managers should already be configured (see [resource alignment prerequisites](#resource-alignment-prerequisites). Set the `memoryManagerPolicy` configuration field within the [kubelet configuration]({{< relref "/docs/reference/config-api/kubelet-config.v1beta1" >}}), to the name of your chosen [policy](#policies). Optionally, some amount of memory can be reserved for system or kubelet processes to increase node stability (section [Reserved memory configuration](#reserved-memory-flag)). ### Policies Kubernetes' memory manager provides three policies. You can select a policy via the `memoryManagerPolicy` configuration field in the kubelet configuration; the values available in Kubernetes {{< skew currentVersion >}} are: \* [`None`](#policy-none) (default) \* [`Static`](#policy-static) (Linux only) \* [`BestEffort`](#policy-best-effort) (Windows only) #### None policy {#policy-none} This is the default policy and
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/memory-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/memory-manager.md
|
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0.026569241657853127
] | 0.270285
|
memory manager provides three policies. You can select a policy via the `memoryManagerPolicy` configuration field in the kubelet configuration; the values available in Kubernetes {{< skew currentVersion >}} are: \* [`None`](#policy-none) (default) \* [`Static`](#policy-static) (Linux only) \* [`BestEffort`](#policy-best-effort) (Windows only) #### None policy {#policy-none} This is the default policy and does not affect the memory allocation in any way. It acts the same as if the Memory Manager is not present at all. The `None` policy returns default topology hint. This special hint denotes that Hint Provider (Memory Manager in this case) has no preference for NUMA affinity with any resource. #### Static policy {#policy-static} {{< feature-state feature\_gate\_name="MemoryManager" >}} \*\*This policy is only supported on Linux.\*\* In the case of the `Guaranteed` pod, the `Static` Memory Manager policy returns topology hints relating to the set of NUMA nodes where the memory can be guaranteed, and reserves the memory through updating the internal [NodeMap][2] object. In the case of the `BestEffort` or `Burstable` pod, the `Static` Memory Manager policy sends back the default topology hint as there is no request for the guaranteed memory, and does not reserve the memory in the internal [NodeMap][2] object. This policy is only supported on Linux. #### BestEffort policy {#policy-best-effort} {{< feature-state feature\_gate\_name="WindowsCPUAndMemoryAffinity" >}} \*\*This policy is only supported on Windows.\*\* On Windows, NUMA node assignment works differently than Linux. There is no mechanism to ensure that Memory access only comes from a specific NUMA node. Instead the Windows operating system scheduler selects the most optimal NUMA node based on the CPU(s) assignments. It is possible that Windows might use other NUMA nodes if the Windows scheduler deems them optimal. The policy does track the amount of memory available and requested through the internal \_node map\_. The memory manager makes a best effort at ensuring that enough memory is available on a NUMA node before making a resource assignment. This means that in most cases memory assignment should function as specified. ## Reserved memory configuration {#reserved-memory-flag} As an administrator, you can configure the total amount of reserved memory for a node. This pre-configured value is subsequently utilized to calculate the real amount of [node allocatable](/docs/tasks/administer-cluster/reserve-compute-resources/#node-allocatable) memory available to pods. The Kubernetes scheduler incorporates allocatable memory information to optimise pod [scheduling](/docs/concepts/scheduling-eviction/). . The \_node allocatable\_ mechanism is commonly used by node administrators to reserve K8s node system resources for the kubelet or operating system processes to help assure node stability. The relevant kubelet settings include `kubeReserved`, `systemReserved` and `reservedMemory`. The `reservedMemory` setting allows you to split the total reserved memory and assign it across many NUMA nodes. You specify a comma-separated list of memory reservations, of different memory types, per NUMA node. You can also specify reservations that span multiple NUMA nodes, using a semicolon as separator. The Memory Manager will not use this reserved memory for running container workloads. For example, if you have a NUMA node "NUMA0" with 10GiB of memory available, and you configure `reservedMemory` to reserve `1Gi` (of memory) for NUMA0, the Memory Manager assumes that only 9GiB is available for pods. You can omit this parameter, however, you should be aware that the quantity of reserved memory from all NUMA nodes should be equal to the quantity of \_node allocatable\_ memory. If at least one node allocatable parameter is non-zero, you will need to specify `reservedMemory` for at least one NUMA node. In fact, the `evictionHard` threshold value is equal to `100Mi` by default, so if you use the `Static` policy, specifying `reservedMemory` is obligatory. ### Memory manager reserved memory syntax {#reserved-memory-syntax} Here are some examples of how to set the
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/memory-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/memory-manager.md
|
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|
will need to specify `reservedMemory` for at least one NUMA node. In fact, the `evictionHard` threshold value is equal to `100Mi` by default, so if you use the `Static` policy, specifying `reservedMemory` is obligatory. ### Memory manager reserved memory syntax {#reserved-memory-syntax} Here are some examples of how to set the `reservedMemory` configuration for the kubelet. ```yaml # Example 1 reservedMemory: - numaNode: 0 # NUMA node index limits: memory: "1Gi" # byte quantity - numaNode: 1 limits: memory: "2Gi" # byte quantity ``` ```yaml # Example 2 reservedMemory: - numaNode: 0 limits: "memory": "512Gi" - numaNode: 1 limits: "memory": "512Gi" "hugepages-1Gi": "2Gi" # only relevant on Linux ``` ### Constraints on NUMA memory reservation When you specify values for `reservedMemory`, this must be compatible with the `kubeReserved` and `systemReserved` values that are in effect, along with any `memory.available` setting you make as part of `evictionHard`. ```math \begin{equation\*} \sum\_{ \textnormal{i} = 0}^{ \textnormal{node count}} { \textit{reservedMemory} [ \textnormal{i} ]} = \textit{kubeReserved} + \textit{systemReserved} + \textit{evictionHard} \, \boxed{\textnormal{memory.available}} \end{equation\*}\\\ \text{where i is an index of a NUMA node} ``` If you do not follow the formula above, the Memory Manager will show an error on startup. In other words, the example 1 (above) illustrates that for the conventional memory (`type=memory`), Kubernetes reserves 3GiB in total; that is: ```math \begin{equation\*} \sum\_{ \textnormal{i} = 0}^{ \textnormal{node count}} \textit{reservedMemory}\_{ [ \textnormal{i} ] } = \underbrace{\textit{reservedMemory} [ 0 ] + \textit{reservedMemory} [ 1 ] }\_{\textnormal{type=memory}} = 1 \textnormal{GiB} + 2 \textnormal{GiB} = 3 \textnormal{GiB} \end{equation\*}\\\ \text{where i is an index of a NUMA node} ``` Some examples of kubelet configuration settings relevant to the node allocatable configuration: ```yaml kubeReserved: { cpu: "500m", memory: "50Mi" } # half a CPU, 50MiB of memory systemReserved: { cpu: "500m", memory: "256Mi" } # half a CPU, 256MiB of memory ``` {{< note >}} The default hard eviction threshold is 100MiB, and \*\*not\*\* zero. Remember to increase the quantity of memory that you reserve by setting `reservedMemory` by that hard eviction threshold. Otherwise, the kubelet will not start Memory Manager and display an error. Here is an example of a correct configuration that uses `reservedMemory`: ```yaml # this snippet relies on the default value of evictionHard memoryManagerPolicy: Static kubeReserved: { cpu: "4", memory: "4Gi" } systemReserved: { cpu: "1", memory: "1Gi" } reservedMemory: - numaNode: 0 limits: memory: "3Gi" - numaNode: 1 limits: memory: "2148Mi" # 3GiB minus 100MiB ``` {{< /note >}} ### Configurations to avoid {#reserved-memory-configurations-to-avoid} Avoid the following configurations: 1. duplicates: the same NUMA node or memory type, but with a different value; 1. setting a zero limit for any of memory types; 1. NUMA node IDs that do not exist in the machine hardware; 1. memory type names different than `memory` or `hugepages-` (hugepages of particular `` should also exist). ## Placing a Pod in the Guaranteed QoS class If the selected policy is anything other than `None`, the Memory Manager identifies pods that are in the `Guaranteed` QoS class. The Memory Manager provides specific topology hints to the Topology Manager for each `Guaranteed` pod. For pods in a QoS class other than `Guaranteed`, the Memory Manager provides default topology hints to the Topology Manager. The following excerpts from pod manifests assign a pod to the `Guaranteed` QoS class. A Pod with integer CPU(s) runs in the `Guaranteed` QoS class, when `requests` are equal to `limits`: ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" cpu: "2" example.com/device: "1" requests: memory: "200Mi" cpu: "2" example.com/device: "1" ``` Also, a pod sharing CPU(s) runs in the `Guaranteed` QoS class, when `requests` are equal to
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/memory-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/memory-manager.md
|
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] | 0.208929
|
the `Guaranteed` QoS class, when `requests` are equal to `limits`: ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" cpu: "2" example.com/device: "1" requests: memory: "200Mi" cpu: "2" example.com/device: "1" ``` Also, a pod sharing CPU(s) runs in the `Guaranteed` QoS class, when `requests` are equal to `limits`. ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" cpu: "300m" example.com/device: "1" requests: memory: "200Mi" cpu: "300m" example.com/device: "1" ``` Notice that both CPU and memory requests must be specified for a Pod to lend it to Guaranteed QoS class. ## {{% heading "whatsnext" %}} - Read [Troubleshooting Topology Management](/docs/tasks/debug/debug-cluster/topology/) - Read the [KEP](https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/1769-memory-manager) (Kubernetes enhancement proposal) for memory manager
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/memory-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/memory-manager.md
|
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{{< feature-state feature\_gate\_name="EventedPLEG" >}} This page shows how to migrate nodes to use event based updates for container status. The event-based implementation reduces node resource consumption by the kubelet, compared to the legacy approach that relies on polling. You may know this feature as \_evented Pod lifecycle event generator (PLEG)\_. That's the name used internally within the Kubernetes project for a key implementation detail. The polling based approach is referred to as \_generic PLEG\_. ## {{% heading "prerequisites" %}} \* You need to run a version of Kubernetes that provides this feature. Kubernetes v1.27 includes beta support for event-based container status updates. The feature is beta but is \_disabled\_ by default because it requires support from the container runtime. \* {{< version-check >}} If you are running a different version of Kubernetes, check the documentation for that release. \* The container runtime in use must support container lifecycle events. The kubelet automatically switches back to the legacy generic PLEG mechanism if the container runtime does not announce support for container lifecycle events, even if you have this feature gate enabled. ## Why switch to Evented PLEG? \* The \_Generic PLEG\_ incurs non-negligible overhead due to frequent polling of container statuses. \* This overhead is exacerbated by Kubelet's parallelized polling of container states, thus limiting its scalability and causing poor performance and reliability problems. \* The goal of \_Evented PLEG\_ is to reduce unnecessary work during inactivity by replacing periodic polling. ## Switching to Evented PLEG 1. Start the Kubelet with the [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) `EventedPLEG` enabled. You can manage the kubelet feature gates editing the kubelet [config file](/docs/tasks/administer-cluster/kubelet-config-file/) and restarting the kubelet service. You need to do this on each node where you are using this feature. 2. Make sure the node is [drained](/docs/tasks/administer-cluster/safely-drain-node/) before proceeding. 3. Start the container runtime with the container event generation enabled. {{< tabs name="tab\_with\_code" >}} {{% tab name="Containerd" %}} Version 1.7+ {{% /tab %}} {{% tab name="CRI-O" %}} Version 1.26+ Check if the CRI-O is already configured to emit CRI events by verifying the configuration, ```shell crio config | grep enable\_pod\_events ``` If it is enabled, the output should be similar to the following: ```none enable\_pod\_events = true ``` To enable it, start the CRI-O daemon with the flag `--enable-pod-events=true` or use a dropin config with the following lines: ```toml [crio.runtime] enable\_pod\_events: true ``` {{% /tab %}} {{< /tabs >}} {{< version-check >}} 4. Verify that the kubelet is using event-based container stage change monitoring. To check, look for the term `EventedPLEG` in the kubelet logs. The output should be similar to this: ```console I0314 11:10:13.909915 1105457 feature\_gate.go:249] feature gates: &{map[EventedPLEG:true]} ``` If you have set `--v` to 4 and above, you might see more entries that indicate that the kubelet is using event-based container state monitoring. ```console I0314 11:12:42.009542 1110177 evented.go:238] "Evented PLEG: Generated pod status from the received event" podUID=3b2c6172-b112-447a-ba96-94e7022912dc I0314 11:12:44.623326 1110177 evented.go:238] "Evented PLEG: Generated pod status from the received event" podUID=b3fba5ea-a8c5-4b76-8f43-481e17e8ec40 I0314 11:12:44.714564 1110177 evented.go:238] "Evented PLEG: Generated pod status from the received event" podUID=b3fba5ea-a8c5-4b76-8f43-481e17e8ec40 ``` ## {{% heading "whatsnext" %}} \* Learn more about the design in the Kubernetes Enhancement Proposal (KEP): [Kubelet Evented PLEG for Better Performance](https://github.com/kubernetes/enhancements/blob/5b258a990adabc2ffdc9d84581ea6ed696f7ce6c/keps/sig-node/3386-kubelet-evented-pleg/README.md).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/switch-to-evented-pleg.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/switch-to-evented-pleg.md
|
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] | 0.159003
|
{{< feature-state state="beta" for\_k8s\_version="v1.26" >}} ## {{% heading "prerequisites" %}} You will need to have the following tools installed: - `cosign` ([install guide](https://docs.sigstore.dev/cosign/system\_config/installation/)) - `curl` (often provided by your operating system) - `jq` ([download jq](https://jqlang.github.io/jq/download/)) ## Verifying binary signatures The Kubernetes release process signs all binary artifacts (tarballs, SPDX files, standalone binaries) by using cosign's keyless signing. To verify a particular binary, retrieve it together with its signature and certificate: ```bash URL=https://dl.k8s.io/release/v{{< skew currentPatchVersion >}}/bin/linux/amd64 BINARY=kubectl FILES=( "$BINARY" "$BINARY.sig" "$BINARY.cert" ) for FILE in "${FILES[@]}"; do curl -sSfL --retry 3 --retry-delay 3 "$URL/$FILE" -o "$FILE" done ``` Then verify the blob by using `cosign verify-blob`: ```shell cosign verify-blob "$BINARY" \ --signature "$BINARY".sig \ --certificate "$BINARY".cert \ --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \ --certificate-oidc-issuer https://accounts.google.com ``` {{< note >}} Cosign 2.0 requires the `--certificate-identity` and `--certificate-oidc-issuer` options. To learn more about keyless signing, please refer to [Keyless Signatures](https://docs.sigstore.dev/cosign/signing/overview/). Previous versions of Cosign required that you set `COSIGN\_EXPERIMENTAL=1`. For additional information, please refer to the [sigstore Blog](https://blog.sigstore.dev/cosign-2-0-released/) {{< /note >}} ## Verifying image signatures For a complete list of images that are signed please refer to [Releases](/releases/download/). Pick one image from this list and verify its signature using the `cosign verify` command: ```shell cosign verify registry.k8s.io/kube-apiserver-amd64:v{{< skew currentPatchVersion >}} \ --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \ --certificate-oidc-issuer https://accounts.google.com \ | jq . ``` ### Verifying images for all control plane components To verify all signed control plane images for the latest stable version (v{{< skew currentPatchVersion >}}), please run the following commands: ```shell curl -Ls "https://sbom.k8s.io/$(curl -Ls https://dl.k8s.io/release/stable.txt)/release" \ | grep "SPDXID: SPDXRef-Package-registry.k8s.io" \ | grep -v sha256 | cut -d- -f3- | sed 's/-/\//' | sed 's/-v1/:v1/' \ | sort > images.txt input=images.txt while IFS= read -r image do cosign verify "$image" \ --certificate-identity krel-trust@k8s-releng-prod.iam.gserviceaccount.com \ --certificate-oidc-issuer https://accounts.google.com \ | jq . done < "$input" ``` Once you have verified an image, you can specify the image by its digest in your Pod manifests as per this example: ```console registry-url/image-name@sha256:45b23dee08af5e43a7fea6c4cf9c25ccf269ee113168c19722f87876677c5cb2 ``` For more information, please refer to the [Image Pull Policy](/docs/concepts/containers/images/#image-pull-policy) section. ## Verifying Image Signatures with Admission Controller For non-control plane images (for example [conformance image](https://github.com/kubernetes/kubernetes/blob/master/test/conformance/image/README.md)), signatures can also be verified at deploy time using [sigstore policy-controller](https://docs.sigstore.dev/policy-controller/overview) admission controller. Here are some helpful resources to get started with `policy-controller`: - [Installation](https://github.com/sigstore/helm-charts/tree/main/charts/policy-controller) - [Configuration Options](https://github.com/sigstore/policy-controller/tree/main/config) ## Verify the Software Bill Of Materials You can verify the Kubernetes Software Bill of Materials (SBOM) by using the sigstore certificate and signature, or the corresponding SHA files: ```shell # Retrieve the latest available Kubernetes release version VERSION=$(curl -Ls https://dl.k8s.io/release/stable.txt) # Verify the SHA512 sum curl -Ls "https://sbom.k8s.io/$VERSION/release" -o "$VERSION.spdx" echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha512") $VERSION.spdx" | sha512sum --check # Verify the SHA256 sum echo "$(curl -Ls "https://sbom.k8s.io/$VERSION/release.sha256") $VERSION.spdx" | sha256sum --check # Retrieve sigstore signature and certificate curl -Ls "https://sbom.k8s.io/$VERSION/release.sig" -o "$VERSION.spdx.sig" curl -Ls "https://sbom.k8s.io/$VERSION/release.cert" -o "$VERSION.spdx.cert" # Verify the sigstore signature cosign verify-blob \ --certificate "$VERSION.spdx.cert" \ --signature "$VERSION.spdx.sig" \ --certificate-identity krel-staging@k8s-releng-prod.iam.gserviceaccount.com \ --certificate-oidc-issuer https://accounts.google.com \ "$VERSION.spdx" ```
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/verify-signed-artifacts.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/verify-signed-artifacts.md
|
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] | 0.130115
|
{{< feature-state for\_k8s\_version="v1.11" state="beta" >}} {{< glossary\_definition term\_id="cloud-controller-manager" length="all" prepend="The cloud-controller-manager is">}} ## Background Since cloud providers develop and release at a different pace compared to the Kubernetes project, abstracting the provider-specific code to the `cloud-controller-manager` binary allows cloud vendors to evolve independently from the core Kubernetes code. The Kubernetes project provides skeleton cloud-controller-manager code with Go interfaces to allow you (or your cloud provider) to plug in your own implementations. This means that a cloud provider can implement a cloud-controller-manager by importing packages from Kubernetes core; each cloudprovider will register their own code by calling `cloudprovider.RegisterCloudProvider` to update a global variable of available cloud providers. ## Developing ### Out of tree To build an out-of-tree cloud-controller-manager for your cloud: 1. Create a go package with an implementation that satisfies [cloudprovider.Interface](https://github.com/kubernetes/cloud-provider/blob/master/cloud.go). 2. Use [`main.go` in cloud-controller-manager](https://github.com/kubernetes/kubernetes/blob/master/cmd/cloud-controller-manager/main.go) from Kubernetes core as a template for your `main.go`. As mentioned above, the only difference should be the cloud package that will be imported. 3. Import your cloud package in `main.go`, ensure your package has an `init` block to run [`cloudprovider.RegisterCloudProvider`](https://github.com/kubernetes/cloud-provider/blob/master/plugins.go). Many cloud providers publish their controller manager code as open source. If you are creating a new cloud-controller-manager from scratch, you could take an existing out-of-tree cloud controller manager as your starting point. ### In tree For in-tree cloud providers, you can run the in-tree cloud controller manager as a {{< glossary\_tooltip term\_id="daemonset" >}} in your cluster. See [Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/) for more details.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/developing-cloud-controller-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/developing-cloud-controller-manager.md
|
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] | 0.061161
|
This page provides hints on diagnosing DNS problems. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} Your cluster must be configured to use the CoreDNS {{< glossary\_tooltip text="addon" term\_id="addons" >}} or its precursor, kube-dns. {{% version-check %}} ### Create a simple Pod to use as a test environment {{% code\_sample file="admin/dns/dnsutils.yaml" %}} {{< note >}} This example creates a pod in the `default` namespace. DNS name resolution for services depends on the namespace of the pod. For more information, review [DNS for Services and Pods](/docs/concepts/services-networking/dns-pod-service/#what-things-get-dns-names). {{< /note >}} Use that manifest to create a Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/dns/dnsutils.yaml ``` ``` pod/dnsutils created ``` …and verify its status: ```shell kubectl get pods dnsutils ``` ``` NAME READY STATUS RESTARTS AGE dnsutils 1/1 Running 0 ``` Once that Pod is running, you can exec `nslookup` in that environment. If you see something like the following, DNS is working correctly. ```shell kubectl exec -i -t dnsutils -- nslookup kubernetes.default ``` ``` Server: 10.0.0.10 Address 1: 10.0.0.10 Name: kubernetes.default Address 1: 10.0.0.1 ``` If the `nslookup` command fails, check the following: ### Check the local DNS configuration first Take a look inside the resolv.conf file. (See [Customizing DNS Service](/docs/tasks/administer-cluster/dns-custom-nameservers) and [Known issues](#known-issues) below for more information) ```shell kubectl exec -ti dnsutils -- cat /etc/resolv.conf ``` Verify that the search path and name server are set up like the following (note that search path may vary for different cloud providers): ``` search default.svc.cluster.local svc.cluster.local cluster.local google.internal c.gce\_project\_id.internal nameserver 10.0.0.10 options ndots:5 ``` Errors such as the following indicate a problem with the CoreDNS (or kube-dns) add-on or with associated Services: ```shell kubectl exec -i -t dnsutils -- nslookup kubernetes.default ``` ``` Server: 10.0.0.10 Address 1: 10.0.0.10 nslookup: can't resolve 'kubernetes.default' ``` or ```shell kubectl exec -i -t dnsutils -- nslookup kubernetes.default ``` ``` Server: 10.0.0.10 Address 1: 10.0.0.10 kube-dns.kube-system.svc.cluster.local nslookup: can't resolve 'kubernetes.default' ``` ### Check if the DNS pod is running Use the `kubectl get pods` command to verify that the DNS pod is running. ```shell kubectl get pods --namespace=kube-system -l k8s-app=kube-dns ``` ``` NAME READY STATUS RESTARTS AGE ... coredns-7b96bf9f76-5hsxb 1/1 Running 0 1h coredns-7b96bf9f76-mvmmt 1/1 Running 0 1h ... ``` {{< note >}} The value for label `k8s-app` is `kube-dns` for both CoreDNS and kube-dns deployments. {{< /note >}} If you see that no CoreDNS Pod is running or that the Pod has failed/completed, the DNS add-on may not be deployed by default in your current environment and you will have to deploy it manually. ### Check for errors in the DNS pod Use the `kubectl logs` command to see logs for the DNS containers. For CoreDNS: ```shell kubectl logs --namespace=kube-system -l k8s-app=kube-dns ``` Here is an example of a healthy CoreDNS log: ``` .:53 2018/08/15 14:37:17 [INFO] CoreDNS-1.2.2 2018/08/15 14:37:17 [INFO] linux/amd64, go1.10.3, 2e322f6 CoreDNS-1.2.2 linux/amd64, go1.10.3, 2e322f6 2018/08/15 14:37:17 [INFO] plugin/reload: Running configuration MD5 = 24e6c59e83ce706f07bcc82c31b1ea1c ``` See if there are any suspicious or unexpected messages in the logs. ### Is DNS service up? Verify that the DNS service is up by using the `kubectl get service` command. ```shell kubectl get svc --namespace=kube-system ``` ``` NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE ... kube-dns ClusterIP 10.0.0.10 53/UDP,53/TCP 1h ... ``` {{< note >}} The service name is `kube-dns` for both CoreDNS and kube-dns deployments. {{< /note >}} If you have created the Service or in the case it should be created by default but it does not appear, see [debugging Services](/docs/tasks/debug/debug-application/debug-service/) for more information. ### Are DNS endpoints exposed? You can verify that DNS endpoints are exposed by using the `kubectl get endpointslice` command. ```shell kubectl get endpointslice
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
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] | 0.111212
|
you have created the Service or in the case it should be created by default but it does not appear, see [debugging Services](/docs/tasks/debug/debug-application/debug-service/) for more information. ### Are DNS endpoints exposed? You can verify that DNS endpoints are exposed by using the `kubectl get endpointslice` command. ```shell kubectl get endpointslice -l k8s.io/service-name=kube-dns --namespace=kube-system ``` ``` NAME ADDRESSTYPE PORTS ENDPOINTS AGE kube-dns-zxoja IPv4 53 10.180.3.17,10.180.3.17 1h ``` If you do not see the endpoints, see the endpoints section in the [debugging Services](/docs/tasks/debug/debug-application/debug-service/) documentation. ### Are DNS queries being received/processed? You can verify if queries are being received by CoreDNS by adding the `log` plugin to the CoreDNS configuration (aka Corefile). The CoreDNS Corefile is held in a {{< glossary\_tooltip text="ConfigMap" term\_id="configmap" >}} named `coredns`. To edit it, use the command: ``` kubectl -n kube-system edit configmap coredns ``` Then add `log` in the Corefile section per the example below: ```yaml apiVersion: v1 kind: ConfigMap metadata: name: coredns namespace: kube-system data: Corefile: | .:53 { log errors health kubernetes cluster.local in-addr.arpa ip6.arpa { pods insecure upstream fallthrough in-addr.arpa ip6.arpa } prometheus :9153 forward . /etc/resolv.conf cache 30 loop reload loadbalance } ``` After saving the changes, it may take up to minute or two for Kubernetes to propagate these changes to the CoreDNS pods. Next, make some queries and view the logs per the sections above in this document. If CoreDNS pods are receiving the queries, you should see them in the logs. Here is an example of a query in the log: ``` .:53 2018/08/15 14:37:15 [INFO] CoreDNS-1.2.0 2018/08/15 14:37:15 [INFO] linux/amd64, go1.10.3, 2e322f6 CoreDNS-1.2.0 linux/amd64, go1.10.3, 2e322f6 2018/09/07 15:29:04 [INFO] plugin/reload: Running configuration MD5 = 162475cdf272d8aa601e6fe67a6ad42f 2018/09/07 15:29:04 [INFO] Reloading complete 172.17.0.18:41675 - [07/Sep/2018:15:29:11 +0000] 59925 "A IN kubernetes.default.svc.cluster.local. udp 54 false 512" NOERROR qr,aa,rd,ra 106 0.000066649s ``` ### Does CoreDNS have sufficient permissions? CoreDNS must be able to list {{< glossary\_tooltip text="service" term\_id="service" >}} and {{< glossary\_tooltip text="endpointslice" term\_id="endpoint-slice" >}} related resources to properly resolve service names. Sample error message: ``` 2022-03-18T07:12:15.699431183Z [INFO] 10.96.144.227:52299 - 3686 "A IN serverproxy.contoso.net.cluster.local. udp 52 false 512" SERVFAIL qr,aa,rd 145 0.000091221s ``` First, get the current ClusterRole of `system:coredns`: ```shell kubectl describe clusterrole system:coredns -n kube-system ``` Expected output: ``` PolicyRule: Resources Non-Resource URLs Resource Names Verbs --------- ----------------- -------------- ----- endpoints [] [] [list watch] namespaces [] [] [list watch] pods [] [] [list watch] services [] [] [list watch] endpointslices.discovery.k8s.io [] [] [list watch] ``` If any permissions are missing, edit the ClusterRole to add them: ```shell kubectl edit clusterrole system:coredns -n kube-system ``` Example insertion of EndpointSlices permissions: ``` ... - apiGroups: - discovery.k8s.io resources: - endpointslices verbs: - list - watch ... ``` ### Are you in the right namespace for the service? DNS queries that don't specify a namespace are limited to the pod's namespace. If the namespace of the pod and service differ, the DNS query must include the namespace of the service. This query is limited to the pod's namespace: ```shell kubectl exec -i -t dnsutils -- nslookup ``` This query specifies the namespace: ```shell kubectl exec -i -t dnsutils -- nslookup . ``` To learn more about name resolution, see [DNS for Services and Pods](/docs/concepts/services-networking/dns-pod-service/#what-things-get-dns-names). ## Known issues Some Linux distributions (e.g. Ubuntu) use a local DNS resolver by default (systemd-resolved). Systemd-resolved moves and replaces `/etc/resolv.conf` with a stub file that can cause a fatal forwarding loop when resolving names in upstream servers. This can be fixed manually by using kubelet's `--resolv-conf` flag to point to the correct `resolv.conf` (With `systemd-resolved`, this is `/run/systemd/resolve/resolv.conf`). kubeadm automatically detects `systemd-resolved`, and adjusts the kubelet flags accordingly. Kubernetes
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
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0.05127376690506935
] | 0.122184
|
`/etc/resolv.conf` with a stub file that can cause a fatal forwarding loop when resolving names in upstream servers. This can be fixed manually by using kubelet's `--resolv-conf` flag to point to the correct `resolv.conf` (With `systemd-resolved`, this is `/run/systemd/resolve/resolv.conf`). kubeadm automatically detects `systemd-resolved`, and adjusts the kubelet flags accordingly. Kubernetes installs do not configure the nodes' `resolv.conf` files to use the cluster DNS by default, because that process is inherently distribution-specific. This should probably be implemented eventually. Linux's libc (a.k.a. glibc) has a limit for the DNS `nameserver` records to 3 by default and Kubernetes needs to consume 1 `nameserver` record. This means that if a local installation already uses 3 `nameserver`s, some of those entries will be lost. To work around this limit, the node can run `dnsmasq`, which will provide more `nameserver` entries. You can also use kubelet's `--resolv-conf` flag. If you are using Alpine version 3.17 or earlier as your base image, DNS may not work properly due to a design issue with Alpine. Until musl version 1.24 didn't include TCP fallback to the DNS stub resolver meaning any DNS call above 512 bytes would fail. Please upgrade your images to Alpine version 3.18 or above. ## {{% heading "whatsnext" %}} - See [Autoscaling the DNS Service in a Cluster](/docs/tasks/administer-cluster/dns-horizontal-autoscaling/). - Read [DNS for Services and Pods](/docs/concepts/services-networking/dns-pod-service/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/dns-debugging-resolution.md
|
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] | 0.074455
|
{{< feature-state for\_k8s\_version="v1.26" state="stable" >}} Starting from Kubernetes v1.20, the kubelet can dynamically retrieve credentials for a container image registry using exec plugins. The kubelet and the exec plugin communicate through stdio (stdin, stdout, and stderr) using Kubernetes versioned APIs. These plugins allow the kubelet to request credentials for a container registry dynamically as opposed to storing static credentials on disk. For example, the plugin may talk to a local metadata server to retrieve short-lived credentials for an image that is being pulled by the kubelet. You may be interested in using this capability if any of the below are true: \* API calls to a cloud provider service are required to retrieve authentication information for a registry. \* Credentials have short expiration times and requesting new credentials frequently is required. \* Storing registry credentials on disk or in imagePullSecrets is not acceptable. This guide demonstrates how to configure the kubelet's image credential provider plugin mechanism. ## Service Account Token for Image Pulls {{< feature-state feature\_gate\_name="KubeletServiceAccountTokenForCredentialProviders" >}} Starting from Kubernetes v1.33, the kubelet can be configured to send a service account token bound to the pod for which the image pull is being performed to the credential provider plugin. This allows the plugin to exchange the token for credentials to access the image registry. To enable this feature, the `KubeletServiceAccountTokenForCredentialProviders` feature gate must be enabled on the kubelet, and the `tokenAttributes` field must be set in the `CredentialProviderConfig` file for the plugin. The `tokenAttributes` field contains information about the service account token that will be passed to the plugin, including the intended audience for the token and whether the plugin requires the pod to have a service account. Using service account token credentials can enable the following use-cases: \* Avoid needing a kubelet/node-based identity to pull images from a registry. \* Allow workloads to pull images based on their own runtime identity without long-lived/persisted secrets. ## {{% heading "prerequisites" %}} \* You need a Kubernetes cluster with nodes that support kubelet credential provider plugins. This support is available in Kubernetes {{< skew currentVersion >}}; Kubernetes v1.24 and v1.25 included this as a beta feature, enabled by default. \* If you are configuring a credential provider plugin that requires the service account token, you need a Kubernetes cluster with nodes running Kubernetes v1.33 or later and the `KubeletServiceAccountTokenForCredentialProviders` feature gate enabled on the kubelet. \* A working implementation of a credential provider exec plugin. You can build your own plugin or use one provided by cloud providers. {{< version-check >}} ## Installing Plugins on Nodes A credential provider plugin is an executable binary that will be run by the kubelet. Ensure that the plugin binary exists on every node in your cluster and stored in a known directory. The directory will be required later when configuring kubelet flags. ## Configuring the Kubelet In order to use this feature, the kubelet expects two flags to be set: \* `--image-credential-provider-config` - the path to the credential provider plugin config file. \* `--image-credential-provider-bin-dir` - the path to the directory where credential provider plugin binaries are located. ### Configure a kubelet credential provider The configuration file passed into `--image-credential-provider-config` is read by the kubelet to determine which exec plugins should be invoked for which container images. Here's an example configuration file you may end up using if you are using the [ECR-based plugin](https://github.com/kubernetes/cloud-provider-aws/tree/master/cmd/ecr-credential-provider): ```yaml apiVersion: kubelet.config.k8s.io/v1 kind: CredentialProviderConfig # providers is a list of credential provider helper plugins that will be enabled by the kubelet. # Multiple providers may match against a single image, in which case credentials # from all providers will be returned
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
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] | 0.08625
|
using if you are using the [ECR-based plugin](https://github.com/kubernetes/cloud-provider-aws/tree/master/cmd/ecr-credential-provider): ```yaml apiVersion: kubelet.config.k8s.io/v1 kind: CredentialProviderConfig # providers is a list of credential provider helper plugins that will be enabled by the kubelet. # Multiple providers may match against a single image, in which case credentials # from all providers will be returned to the kubelet. If multiple providers are called # for a single image, the results are combined. If providers return overlapping # auth keys, the value from the provider earlier in this list is used. providers: # name is the required name of the credential provider. It must match the name of the # provider executable as seen by the kubelet. The executable must be in the kubelet's # bin directory (set by the --image-credential-provider-bin-dir flag). - name: ecr-credential-provider # matchImages is a required list of strings used to match against images in order to # determine if this provider should be invoked. If one of the strings matches the # requested image from the kubelet, the plugin will be invoked and given a chance # to provide credentials. Images are expected to contain the registry domain # and URL path. # # Each entry in matchImages is a pattern which can optionally contain a port and a path. # Globs can be used in the domain, but not in the port or the path. Globs are supported # as subdomains like '\*.k8s.io' or 'k8s.\*.io', and top-level-domains such as 'k8s.\*'. # Matching partial subdomains like 'app\*.k8s.io' is also supported. Each glob can only match # a single subdomain segment, so `\*.io` does \*\*not\*\* match `\*.k8s.io`. # # A match exists between an image and a matchImage when all of the below are true: # - Both contain the same number of domain parts and each part matches. # - The URL path of an matchImages must be a prefix of the target image URL path. # - If the matchImages contains a port, then the port must match in the image as well. # # Example values of matchImages: # - 123456789.dkr.ecr.us-east-1.amazonaws.com # - \*.azurecr.io # - gcr.io # - \*.\*.registry.io # - registry.io:8080/path matchImages: - "\*.dkr.ecr.\*.amazonaws.com" - "\*.dkr.ecr.\*.amazonaws.com.cn" - "\*.dkr.ecr-fips.\*.amazonaws.com" - "\*.dkr.ecr.us-iso-east-1.c2s.ic.gov" - "\*.dkr.ecr.us-isob-east-1.sc2s.sgov.gov" # defaultCacheDuration is the default duration the plugin will cache credentials in-memory # if a cache duration is not provided in the plugin response. This field is required. defaultCacheDuration: "12h" # Required input version of the exec CredentialProviderRequest. The returned CredentialProviderResponse # MUST use the same encoding version as the input. Current supported values are: # - credentialprovider.kubelet.k8s.io/v1 apiVersion: credentialprovider.kubelet.k8s.io/v1 # Arguments to pass to the command when executing it. # +optional # args: # - --example-argument # Env defines additional environment variables to expose to the process. These # are unioned with the host's environment, as well as variables client-go uses # to pass argument to the plugin. # +optional env: - name: AWS\_PROFILE value: example\_profile # tokenAttributes is the configuration for the service account token that will be passed to the plugin. # The credential provider opts in to using service account tokens for image pull by setting this field. # if this field is set without the `KubeletServiceAccountTokenForCredentialProviders` feature gate enabled, # kubelet will fail to start with invalid configuration error. # +optional tokenAttributes: # serviceAccountTokenAudience is the intended audience for the projected service account token. # +required serviceAccountTokenAudience: "" # cacheType indicates the type of cache key use for caching the credentials returned by the plugin # when the service account token is used. # The most conservative option is to set this to "Token", which means the kubelet will cache
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
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] | 0.045103
|
projected service account token. # +required serviceAccountTokenAudience: "" # cacheType indicates the type of cache key use for caching the credentials returned by the plugin # when the service account token is used. # The most conservative option is to set this to "Token", which means the kubelet will cache # returned credentials on a per-token basis. This should be set if the returned credential's # lifetime is limited to the service account token's lifetime. # If the plugin's credential retrieval logic depends only on the service account and not on # pod-specific claims, then the plugin can set this to "ServiceAccount". In this case, the # kubelet will cache returned credentials on a per-serviceaccount basis. Use this when the # returned credential is valid for all pods using the same service account. # +required cacheType: "" # requireServiceAccount indicates whether the plugin requires the pod to have a service account. # If set to true, kubelet will only invoke the plugin if the pod has a service account. # If set to false, kubelet will invoke the plugin even if the pod does not have a service account # and will not include a token in the CredentialProviderRequest. This is useful for plugins # that are used to pull images for pods without service accounts (e.g., static pods). # +required requireServiceAccount: true # requiredServiceAccountAnnotationKeys is the list of annotation keys that the plugin is interested in # and that are required to be present in the service account. # The keys defined in this list will be extracted from the corresponding service account and passed # to the plugin as part of the CredentialProviderRequest. If any of the keys defined in this list # are not present in the service account, kubelet will not invoke the plugin and will return an error. # This field is optional and may be empty. Plugins may use this field to extract additional information # required to fetch credentials or allow workloads to opt in to using service account tokens for image pull. # If non-empty, requireServiceAccount must be set to true. # The keys defined in this list must be unique and not overlap with the keys defined in the # optionalServiceAccountAnnotationKeys list. # +optional requiredServiceAccountAnnotationKeys: - "example.com/required-annotation-key-1" - "example.com/required-annotation-key-2" # optionalServiceAccountAnnotationKeys is the list of annotation keys that the plugin is interested in # and that are optional to be present in the service account. # The keys defined in this list will be extracted from the corresponding service account and passed # to the plugin as part of the CredentialProviderRequest. The plugin is responsible for validating the # existence of annotations and their values. This field is optional and may be empty. # Plugins may use this field to extract additional information required to fetch credentials. # The keys defined in this list must be unique and not overlap with the keys defined in the # requiredServiceAccountAnnotationKeys list. # +optional optionalServiceAccountAnnotationKeys: - "example.com/optional-annotation-key-1" - "example.com/optional-annotation-key-2" ``` The `providers` field is a list of enabled plugins used by the kubelet. Each entry has a few required fields: \* `name`: the name of the plugin which MUST match the name of the executable binary that exists in the directory passed into `--image-credential-provider-bin-dir`. \* `matchImages`: a list of strings used to match against images in order to determine if this provider should be invoked. More on this below. \* `defaultCacheDuration`: the default duration the kubelet will cache credentials in-memory if a cache duration was not specified by the plugin. \* `apiVersion`: the API version that the kubelet and the exec plugin will use
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
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] | 0.152385
|
images in order to determine if this provider should be invoked. More on this below. \* `defaultCacheDuration`: the default duration the kubelet will cache credentials in-memory if a cache duration was not specified by the plugin. \* `apiVersion`: the API version that the kubelet and the exec plugin will use when communicating. Each credential provider can also be given optional args and environment variables as well. Consult the plugin implementors to determine what set of arguments and environment variables are required for a given plugin. If you are using the KubeletServiceAccountTokenForCredentialProviders feature gate and configuring the plugin to use the service account token by setting the tokenAttributes field, the following fields are required: \* `serviceAccountTokenAudience`: the intended audience for the projected service account token. This cannot be the empty string. \* `cacheType`: the type of cache key used for caching the credentials returned by the plugin when the service account token is used. The most conservative option is to set this to `Token`, which means the kubelet will cache returned credentials on a per-token basis. This should be set if the returned credential's lifetime is limited to the service account token's lifetime. If the plugin's credential retrieval logic depends only on the service account and not on pod-specific claims, then the plugin can set this to `ServiceAccount`. In this case, the kubelet will cache returned credentials on a per-service account basis. Use this when the returned credential is valid for all pods using the same service account. \* `requireServiceAccount`: whether the plugin requires the pod to have a service account. \* If set to `true`, kubelet will only invoke the plugin if the pod has a service account. \* If set to `false`, kubelet will invoke the plugin even if the pod does not have a service account and will not include a token in the `CredentialProviderRequest`. This is useful for plugins that are used to pull images for pods without service accounts (e.g., static pods). #### Configure image matching The `matchImages` field for each credential provider is used by the kubelet to determine whether a plugin should be invoked for a given image that a Pod is using. Each entry in `matchImages` is an image pattern which can optionally contain a port and a path. Globs can be used in the domain, but not in the port or the path. Globs are supported as subdomains like `\*.k8s.io` or `k8s.\*.io`, and top-level domains such as `k8s.\*`. Matching partial subdomains like `app\*.k8s.io` is also supported. Each glob can only match a single subdomain segment, so `\*.io` does NOT match `\*.k8s.io`. A match exists between an image name and a `matchImage` entry when all of the below are true: \* Both contain the same number of domain parts and each part matches. \* The URL path of match image must be a prefix of the target image URL path. \* If the matchImages contains a port, then the port must match in the image as well. Some example values of `matchImages` patterns are: \* `123456789.dkr.ecr.us-east-1.amazonaws.com` \* `\*.azurecr.io` \* `gcr.io` \* `\*.\*.registry.io` \* `foo.registry.io:8080/path` ## {{% heading "whatsnext" %}} \* Read the details about `CredentialProviderConfig` in the [kubelet configuration API (v1) reference](/docs/reference/config-api/kubelet-config.v1/). \* Read the [kubelet credential provider API reference (v1)](/docs/reference/config-api/kubelet-credentialprovider.v1/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubelet-credential-provider.md
|
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] | 0.106135
|
This page shows how to enable or disable an API version from your cluster's {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}}. Specific API versions can be turned on or off by passing `--runtime-config=api/` as a command line argument to the API server. The values for this argument are a comma-separated list of API versions. Later values override earlier values. The `runtime-config` command line argument also supports 2 special keys: - `api/all`, representing all known APIs - `api/legacy`, representing only legacy APIs. Legacy APIs are any APIs that have been explicitly [deprecated](/docs/reference/using-api/deprecation-policy/). For example, to turn off all API versions except v1, pass `--runtime-config=api/all=false,api/v1=true` to the `kube-apiserver`. ## {{% heading "whatsnext" %}} Read the [full documentation](/docs/reference/command-line-tools-reference/kube-apiserver/) for the `kube-apiserver` component.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/enable-disable-api.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/enable-disable-api.md
|
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] | 0.058902
|
When using client certificate authentication, you can generate certificates manually through [`easyrsa`](https://github.com/OpenVPN/easy-rsa), [`openssl`](https://github.com/openssl/openssl) or [`cfssl`](https://github.com/cloudflare/cfssl). ### easyrsa \*\*easyrsa\*\* can manually generate certificates for your cluster. 1. Download, unpack, and initialize the patched version of `easyrsa3`. ```shell curl -LO https://dl.k8s.io/easy-rsa/easy-rsa.tar.gz tar xzf easy-rsa.tar.gz cd easy-rsa-master/easyrsa3 ./easyrsa init-pki ``` 1. Generate a new certificate authority (CA). `--batch` sets automatic mode; `--req-cn` specifies the Common Name (CN) for the CA's new root certificate. ```shell ./easyrsa --batch "--req-cn=${MASTER\_IP}@`date +%s`" build-ca nopass ``` 1. Generate server certificate and key. The argument `--subject-alt-name` sets the possible IPs and DNS names the API server will be accessed with. The `MASTER\_CLUSTER\_IP` is usually the first IP from the service CIDR that is specified as the `--service-cluster-ip-range` argument for both the API server and the controller manager component. The argument `--days` is used to set the number of days after which the certificate expires. The sample below also assumes that you are using `cluster.local` as the default DNS domain name. ```shell ./easyrsa --subject-alt-name="IP:${MASTER\_IP},"\ "IP:${MASTER\_CLUSTER\_IP},"\ "DNS:kubernetes,"\ "DNS:kubernetes.default,"\ "DNS:kubernetes.default.svc,"\ "DNS:kubernetes.default.svc.cluster,"\ "DNS:kubernetes.default.svc.cluster.local" \ --days=10000 \ build-server-full server nopass ``` 1. Copy `pki/ca.crt`, `pki/issued/server.crt`, and `pki/private/server.key` to your directory. 1. Fill in and add the following parameters into the API server start parameters: ```shell --client-ca-file=/yourdirectory/ca.crt --tls-cert-file=/yourdirectory/server.crt --tls-private-key-file=/yourdirectory/server.key ``` ### openssl \*\*openssl\*\* can manually generate certificates for your cluster. 1. Generate a ca.key with 2048bit: ```shell openssl genrsa -out ca.key 2048 ``` 1. According to the ca.key generate a ca.crt (use `-days` to set the certificate effective time): ```shell openssl req -x509 -new -nodes -key ca.key -subj "/CN=${MASTER\_IP}" -days 10000 -out ca.crt ``` 1. Generate a server.key with 2048bit: ```shell openssl genrsa -out server.key 2048 ``` 1. Create a config file for generating a Certificate Signing Request (CSR). Be sure to substitute the values marked with angle brackets (e.g. ``) with real values before saving this to a file (e.g. `csr.conf`). Note that the value for `MASTER\_CLUSTER\_IP` is the service cluster IP for the API server as described in previous subsection. The sample below also assumes that you are using `cluster.local` as the default DNS domain name. ```ini [ req ] default\_bits = 2048 prompt = no default\_md = sha256 req\_extensions = req\_ext distinguished\_name = dn [ dn ] C = ST = L = O = OU = CN = [ req\_ext ] subjectAltName = @alt\_names [ alt\_names ] DNS.1 = kubernetes DNS.2 = kubernetes.default DNS.3 = kubernetes.default.svc DNS.4 = kubernetes.default.svc.cluster DNS.5 = kubernetes.default.svc.cluster.local IP.1 = IP.2 = [ v3\_ext ] authorityKeyIdentifier=keyid,issuer:always basicConstraints=CA:FALSE keyUsage=keyEncipherment,dataEncipherment extendedKeyUsage=serverAuth,clientAuth subjectAltName=@alt\_names ``` 1. Generate the certificate signing request based on the config file: ```shell openssl req -new -key server.key -out server.csr -config csr.conf ``` 1. Generate the server certificate using the ca.key, ca.crt and server.csr: ```shell openssl x509 -req -in server.csr -CA ca.crt -CAkey ca.key \ -CAcreateserial -out server.crt -days 10000 \ -extensions v3\_ext -extfile csr.conf -sha256 ``` 1. View the certificate signing request: ```shell openssl req -noout -text -in ./server.csr ``` 1. View the certificate: ```shell openssl x509 -noout -text -in ./server.crt ``` Finally, add the same parameters into the API server start parameters. ### cfssl \*\*cfssl\*\* is another tool for certificate generation. 1. Download, unpack and prepare the command line tools as shown below. Note that you may need to adapt the sample commands based on the hardware architecture and cfssl version you are using. ```shell curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssl\_1.5.0\_linux\_amd64 -o cfssl chmod +x cfssl curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssljson\_1.5.0\_linux\_amd64 -o cfssljson chmod +x cfssljson curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssl-certinfo\_1.5.0\_linux\_amd64 -o cfssl-certinfo chmod +x cfssl-certinfo ``` 1. Create a directory to hold the artifacts and initialize cfssl: ```shell mkdir cert cd cert ../cfssl print-defaults config > config.json ../cfssl print-defaults csr >
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/certificates.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/certificates.md
|
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] | -0.020122
|
curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssl\_1.5.0\_linux\_amd64 -o cfssl chmod +x cfssl curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssljson\_1.5.0\_linux\_amd64 -o cfssljson chmod +x cfssljson curl -L https://github.com/cloudflare/cfssl/releases/download/v1.5.0/cfssl-certinfo\_1.5.0\_linux\_amd64 -o cfssl-certinfo chmod +x cfssl-certinfo ``` 1. Create a directory to hold the artifacts and initialize cfssl: ```shell mkdir cert cd cert ../cfssl print-defaults config > config.json ../cfssl print-defaults csr > csr.json ``` 1. Create a JSON config file for generating the CA file, for example, `ca-config.json`: ```json { "signing": { "default": { "expiry": "8760h" }, "profiles": { "kubernetes": { "usages": [ "signing", "key encipherment", "server auth", "client auth" ], "expiry": "8760h" } } } } ``` 1. Create a JSON config file for CA certificate signing request (CSR), for example, `ca-csr.json`. Be sure to replace the values marked with angle brackets with real values you want to use. ```json { "CN": "kubernetes", "key": { "algo": "rsa", "size": 2048 }, "names":[{ "C": "", "ST": "", "L": "", "O": "", "OU": "" }] } ``` 1. Generate CA key (`ca-key.pem`) and certificate (`ca.pem`): ```shell ../cfssl gencert -initca ca-csr.json | ../cfssljson -bare ca ``` 1. Create a JSON config file for generating keys and certificates for the API server, for example, `server-csr.json`. Be sure to replace the values in angle brackets with real values you want to use. The `` is the service cluster IP for the API server as described in previous subsection. The sample below also assumes that you are using `cluster.local` as the default DNS domain name. ```json { "CN": "kubernetes", "hosts": [ "127.0.0.1", "", "", "kubernetes", "kubernetes.default", "kubernetes.default.svc", "kubernetes.default.svc.cluster", "kubernetes.default.svc.cluster.local" ], "key": { "algo": "rsa", "size": 2048 }, "names": [{ "C": "", "ST": "", "L": "", "O": "", "OU": "" }] } ``` 1. Generate the key and certificate for the API server, which are by default saved into file `server-key.pem` and `server.pem` respectively: ```shell ../cfssl gencert -ca=ca.pem -ca-key=ca-key.pem \ --config=ca-config.json -profile=kubernetes \ server-csr.json | ../cfssljson -bare server ``` ## Distributing Self-Signed CA Certificate A client node may refuse to recognize a self-signed CA certificate as valid. For a non-production deployment, or for a deployment that runs behind a company firewall, you can distribute a self-signed CA certificate to all clients and refresh the local list for valid certificates. On each client, perform the following operations: ```shell sudo cp ca.crt /usr/local/share/ca-certificates/kubernetes.crt sudo update-ca-certificates ``` ```none Updating certificates in /etc/ssl/certs... 1 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d.... done. ``` ## Certificates API You can use the `certificates.k8s.io` API to provision x509 certificates to use for authentication as documented in the [Managing TLS in a cluster](/docs/tasks/tls/managing-tls-in-a-cluster) task page.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/certificates.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/certificates.md
|
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] | 0.014084
|
Kubernetes core components such as the API server, scheduler, and controller-manager run on a control plane node. However, add-ons must run on a regular cluster node. Some of these add-ons are critical to a fully functional cluster, such as metrics-server, DNS, and UI. A cluster may stop working properly if a critical add-on is evicted (either manually or as a side effect of another operation like upgrade) and becomes pending (for example when the cluster is highly utilized and either there are other pending pods that schedule into the space vacated by the evicted critical add-on pod or the amount of resources available on the node changed for some other reason). Note that marking a pod as critical is not meant to prevent evictions entirely; it only prevents the pod from becoming permanently unavailable. A static pod marked as critical can't be evicted. However, non-static pods marked as critical are always rescheduled. ### Marking pod as critical To mark a Pod as critical, set priorityClassName for that Pod to `system-cluster-critical` or `system-node-critical`. `system-node-critical` is the highest available priority, even higher than `system-cluster-critical`.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods.md
|
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|
{{< feature-state state="stable" for\_k8s\_version="v1.27" >}} An increasing number of systems leverage a combination of CPUs and hardware accelerators to support latency-critical execution and high-throughput parallel computation. These include workloads in fields such as telecommunications, scientific computing, machine learning, financial services and data analytics. Such hybrid systems comprise a high performance environment. In order to extract the best performance, optimizations related to CPU isolation, memory and device locality are required. However, in Kubernetes, these optimizations are handled by a disjoint set of components. \_Topology Manager\_ is a kubelet component that aims to coordinate the set of components that are responsible for these optimizations. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## How topology manager works Prior to the introduction of Topology Manager, the CPU and Device Manager in Kubernetes make resource allocation decisions independently of each other. This can result in undesirable allocations on multiple-socketed systems, and performance/latency sensitive applications will suffer due to these undesirable allocations. Undesirable in this case meaning, for example, CPUs and devices being allocated from different NUMA Nodes, thus incurring additional latency. The Topology Manager is a kubelet component, which acts as a source of truth so that other kubelet components can make topology aligned resource allocation choices. The Topology Manager provides an interface for components, called \*Hint Providers\*, to send and receive topology information. The Topology Manager has a set of node level policies which are explained below. The Topology Manager receives topology information from the \*Hint Providers\* as a bitmask denoting NUMA Nodes available and a preferred allocation indication. The Topology Manager policies perform a set of operations on the hints provided and converge on the hint determined by the policy to give the optimal result. If an undesirable hint is stored, the preferred field for the hint will be set to false. In the current policies preferred is the narrowest preferred mask. The selected hint is stored as part of the Topology Manager. Depending on the policy configured, the pod can be accepted or rejected from the node based on the selected hint. The hint is then stored in the Topology Manager for use by the \*Hint Providers\* when making the resource allocation decisions. The flow can be seen in the following diagram.  ## Windows Support {{< feature-state feature\_gate\_name="WindowsCPUAndMemoryAffinity" >}} The Topology Manager support can be enabled on Windows by using the `WindowsCPUAndMemoryAffinity` feature gate and it requires support in the container runtime. ## Topology manager scopes and policies The Topology Manager currently: - aligns Pods of all QoS classes. - aligns the requested resources that Hint Provider provides topology hints for. If these conditions are met, the Topology Manager will align the requested resources. In order to customize how this alignment is carried out, the Topology Manager provides two distinct options: `scope` and `policy`. The `scope` defines the granularity at which you would like resource alignment to be performed, for example, at the `pod` or `container` level. And the `policy` defines the actual policy used to carry out the alignment, for example, `best-effort`, `restricted`, and `single-numa-node`. Details on the various `scopes` and `policies` available today can be found below. {{< note >}} To align CPU resources with other requested resources in a Pod spec, the CPU Manager should be enabled and proper CPU Manager policy should be configured on a Node. See [Control CPU Management Policies on the Node](/docs/tasks/administer-cluster/cpu-management-policies/). {{< /note >}} {{< note >}} To align memory (and hugepages) resources with other requested resources in a Pod spec, the Memory Manager should be enabled and proper Memory Manager policy should be configured on a Node.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/topology-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/topology-manager.md
|
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|
be configured on a Node. See [Control CPU Management Policies on the Node](/docs/tasks/administer-cluster/cpu-management-policies/). {{< /note >}} {{< note >}} To align memory (and hugepages) resources with other requested resources in a Pod spec, the Memory Manager should be enabled and proper Memory Manager policy should be configured on a Node. Refer to [Memory Manager](/docs/tasks/administer-cluster/memory-manager/) documentation. {{< /note >}} ## Topology manager scopes The Topology Manager can deal with the alignment of resources in a couple of distinct scopes: \* `container` (default) \* `pod` Either option can be selected at a time of the kubelet startup, by setting the `topologyManagerScope` in the [kubelet configuration file](/docs/tasks/administer-cluster/kubelet-config-file/). ### `container` scope The `container` scope is used by default. You can also explicitly set the `topologyManagerScope` to `container` in the [kubelet configuration file](/docs/tasks/administer-cluster/kubelet-config-file/). Within this scope, the Topology Manager performs a number of sequential resource alignments, i.e., for each container (in a pod) a separate alignment is computed. In other words, there is no notion of grouping the containers to a specific set of NUMA nodes, for this particular scope. In effect, the Topology Manager performs an arbitrary alignment of individual containers to NUMA nodes. The notion of grouping the containers was endorsed and implemented on purpose in the following scope, for example the `pod` scope. ### `pod` scope To select the `pod` scope, set `topologyManagerScope` in the [kubelet configuration file](/docs/tasks/administer-cluster/kubelet-config-file/) to `pod`. This scope allows for grouping all containers in a pod to a common set of NUMA nodes. That is, the Topology Manager treats a pod as a whole and attempts to allocate the entire pod (all containers) to either a single NUMA node or a common set of NUMA nodes. The following examples illustrate the alignments produced by the Topology Manager on different occasions: \* all containers can be and are allocated to a single NUMA node; \* all containers can be and are allocated to a shared set of NUMA nodes. The total amount of particular resource demanded for the entire pod is calculated according to [effective requests/limits](/docs/concepts/workloads/pods/init-containers/#resource-sharing-within-containers) formula, and thus, this total value is equal to the maximum of: \* the sum of all app container requests, \* the maximum of init container requests, for a resource. Using the `pod` scope in tandem with `single-numa-node` Topology Manager policy is specifically valuable for workloads that are latency sensitive or for high-throughput applications that perform IPC. By combining both options, you are able to place all containers in a pod onto a single NUMA node; hence, the inter-NUMA communication overhead can be eliminated for that pod. In the case of `single-numa-node` policy, a pod is accepted only if a suitable set of NUMA nodes is present among possible allocations. Reconsider the example above: \* a set containing only a single NUMA node - it leads to pod being admitted, \* whereas a set containing more NUMA nodes - it results in pod rejection (because instead of one NUMA node, two or more NUMA nodes are required to satisfy the allocation). To recap, the Topology Manager first computes a set of NUMA nodes and then tests it against the Topology Manager policy, which either leads to the rejection or admission of the pod. ## Topology manager policies The Topology Manager supports four allocation policies. You can set a policy via a kubelet flag, `--topology-manager-policy`. There are four supported policies: \* `none` (default) \* `best-effort` \* `restricted` \* `single-numa-node` {{< note >}} If the Topology Manager is configured with the \*\*pod\*\* scope, the container, which is considered by the policy, is reflecting requirements of the entire pod, and thus each container from the pod
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/topology-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/topology-manager.md
|
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|
`--topology-manager-policy`. There are four supported policies: \* `none` (default) \* `best-effort` \* `restricted` \* `single-numa-node` {{< note >}} If the Topology Manager is configured with the \*\*pod\*\* scope, the container, which is considered by the policy, is reflecting requirements of the entire pod, and thus each container from the pod will result with \*\*the same\*\* topology alignment decision. {{< /note >}} ### `none` policy {#policy-none} This is the default policy and does not perform any topology alignment. ### `best-effort` policy {#policy-best-effort} For each container in a Pod, the kubelet, with `best-effort` topology management policy, calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager stores the preferred NUMA Node affinity for that container. If the affinity is not preferred, the Topology Manager will store this and admit the pod to the node anyway. The \*Hint Providers\* can then use this information when making the resource allocation decision. ### `restricted` policy {#policy-restricted} For each container in a Pod, the kubelet, with `restricted` topology management policy, calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager stores the preferred NUMA Node affinity for that container. If the affinity is not preferred, the Topology Manager will reject this pod from the node. This will result in a pod entering a `Terminated` state with a pod admission failure. Once the pod is in a `Terminated` state, the Kubernetes scheduler will \*\*not\*\* attempt to reschedule the pod. It is recommended to use a ReplicaSet or Deployment to trigger a redeployment of the pod. An external control loop could be also implemented to trigger a redeployment of pods that have the `Topology Affinity` error. If the pod is admitted, the \*Hint Providers\* can then use this information when making the resource allocation decision. ### `single-numa-node` policy {#policy-single-numa-node} For each container in a Pod, the kubelet, with `single-numa-node` topology management policy, calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager determines if a single NUMA Node affinity is possible. If it is, Topology Manager will store this and the \*Hint Providers\* can then use this information when making the resource allocation decision. If, however, this is not possible then the Topology Manager will reject the pod from the node. This will result in a pod in a `Terminated` state with a pod admission failure. Once the pod is in a `Terminated` state, the Kubernetes scheduler will \*\*not\*\* attempt to reschedule the pod. It is recommended to use a Deployment with replicas to trigger a redeployment of the Pod. An external control loop could be also implemented to trigger a redeployment of pods that have the `Topology Affinity` error. ## Topology manager policy options Support for the Topology Manager policy options requires `TopologyManagerPolicyOptions` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) to be enabled (it is enabled by default). You can toggle groups of options on and off based upon their maturity level using the following feature gates: \* `TopologyManagerPolicyBetaOptions` default enabled. Enable to show beta-level options. \* `TopologyManagerPolicyAlphaOptions` default disabled. Enable to show alpha-level options. You will still have to enable each option using the `TopologyManagerPolicyOptions` kubelet option. ### `prefer-closest-numa-nodes` {#policy-option-prefer-closest-numa-nodes} The `prefer-closest-numa-nodes` option is GA since Kubernetes 1.32. In Kubernetes {{< skew currentVersion >}} this policy option is visible by default provided that the `TopologyManagerPolicyOptions` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) is enabled. The Topology Manager is not aware by default of NUMA distances, and does not take them into account when making Pod admission decisions. This limitation surfaces in multi-socket, as well as single-socket multi NUMA systems, and can cause significant performance degradation in latency-critical execution and high-throughput applications
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/topology-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/topology-manager.md
|
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] | 0.164469
|
gate](/docs/reference/command-line-tools-reference/feature-gates/) is enabled. The Topology Manager is not aware by default of NUMA distances, and does not take them into account when making Pod admission decisions. This limitation surfaces in multi-socket, as well as single-socket multi NUMA systems, and can cause significant performance degradation in latency-critical execution and high-throughput applications if the Topology Manager decides to align resources on non-adjacent NUMA nodes. If you specify the `prefer-closest-numa-nodes` policy option, the `best-effort` and `restricted` policies favor sets of NUMA nodes with shorter distance between them when making admission decisions. You can enable this option by adding `prefer-closest-numa-nodes=true` to the Topology Manager policy options. By default (without this option), the Topology Manager aligns resources on either a single NUMA node or, in the case where more than one NUMA node is required, using the minimum number of NUMA nodes. ### `max-allowable-numa-nodes` {#policy-option-max-allowable-numa-nodes} The `max-allowable-numa-nodes` option is GA since Kubernetes 1.35. In Kubernetes {{< skew currentVersion >}}, this policy option is visible by default provided that the `TopologyManagerPolicyOptions` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) is enabled. The time to admit a pod is tied to the number of NUMA nodes on the physical machine. By default, Kubernetes does not run a kubelet with the Topology Manager enabled, on any (Kubernetes) node where more than 8 NUMA nodes are detected. {{< note >}} If you select the `max-allowable-numa-nodes` policy option, nodes with more than 8 NUMA nodes can be allowed to run with the Topology Manager enabled. The Kubernetes project only has limited data on the impact of using the Topology Manager on (Kubernetes) nodes with more than 8 NUMA nodes. Because of that lack of data, using this policy option with Kubernetes {{< skew currentVersion >}} is \*\*not\*\* recommended and is at your own risk. {{< /note >}} You can enable this option by adding `max-allowable-numa-nodes=true` to the Topology Manager policy options. Setting a value of `max-allowable-numa-nodes` does not (in and of itself) affect the latency of pod admission, but binding a Pod to a (Kubernetes) node with many NUMA does have an impact. Future, potential improvements to Kubernetes may improve Pod admission performance and the high latency that happens as the number of NUMA nodes increases. ## Pod interactions with topology manager policies Consider the containers in the following Pod manifest: ```yaml spec: containers: - name: nginx image: nginx ``` This pod runs in the `BestEffort` QoS class because no resource `requests` or `limits` are specified. ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" requests: memory: "100Mi" ``` This pod runs in the `Burstable` QoS class because requests are less than limits. If the selected policy is anything other than `none`, the Topology Manager would consider these Pod specifications. The Topology Manager would consult the Hint Providers to get topology hints. In the case of the `static`, the CPU Manager policy would return default topology hint, because these Pods do not explicitly request CPU resources. ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" cpu: "2" example.com/device: "1" requests: memory: "200Mi" cpu: "2" example.com/device: "1" ``` This pod with integer CPU request runs in the `Guaranteed` QoS class because `requests` are equal to `limits`. ```yaml spec: containers: - name: nginx image: nginx resources: limits: memory: "200Mi" cpu: "300m" example.com/device: "1" requests: memory: "200Mi" cpu: "300m" example.com/device: "1" ``` This pod with sharing CPU request runs in the `Guaranteed` QoS class because `requests` are equal to `limits`. ```yaml spec: containers: - name: nginx image: nginx resources: limits: example.com/deviceA: "1" example.com/deviceB: "1" requests: example.com/deviceA: "1" example.com/deviceB: "1" ``` This pod runs in the `BestEffort` QoS class because there are no CPU
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/topology-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/topology-manager.md
|
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] | 0.195637
|
pod with sharing CPU request runs in the `Guaranteed` QoS class because `requests` are equal to `limits`. ```yaml spec: containers: - name: nginx image: nginx resources: limits: example.com/deviceA: "1" example.com/deviceB: "1" requests: example.com/deviceA: "1" example.com/deviceB: "1" ``` This pod runs in the `BestEffort` QoS class because there are no CPU and memory requests. The Topology Manager would consider the above pods. The Topology Manager would consult the Hint Providers, which are CPU and Device Manager to get topology hints for the pods. In the case of the `Guaranteed` pod with integer CPU request, the `static` CPU Manager policy would return topology hints relating to the exclusive CPU and the Device Manager would send back hints for the requested device. In the case of the `Guaranteed` pod with sharing CPU request, the `static` CPU Manager policy would return default topology hint as there is no exclusive CPU request and the Device Manager would send back hints for the requested device. In the above two cases of the `Guaranteed` pod, the `none` CPU Manager policy would return default topology hint. In the case of the `BestEffort` pod, the `static` CPU Manager policy would send back the default topology hint as there is no CPU request and the Device Manager would send back the hints for each of the requested devices. Using this information the Topology Manager calculates the optimal hint for the pod and stores this information, which will be used by the Hint Providers when they are making their resource assignments. ## Known limitations 1. The maximum number of NUMA nodes that Topology Manager allows is 8. With more than 8 NUMA nodes, there will be a state explosion when trying to enumerate the possible NUMA affinities and generating their hints. See [`max-allowable-numa-nodes`](#policy-option-max-allowable-numa-nodes) (beta) for more options. 1. The scheduler is not topology-aware, so it is possible to be scheduled on a node and then fail on the node due to the Topology Manager.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/topology-manager.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/topology-manager.md
|
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This page shows how to change the default Storage Class that is used to provision volumes for PersistentVolumeClaims that have no special requirements. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Why change the default storage class? Depending on the installation method, your Kubernetes cluster may be deployed with an existing StorageClass that is marked as default. This default StorageClass is then used to dynamically provision storage for PersistentVolumeClaims that do not require any specific storage class. See [PersistentVolumeClaim documentation](/docs/concepts/storage/persistent-volumes/#persistentvolumeclaims) for details. The pre-installed default StorageClass may not fit well with your expected workload; for example, it might provision storage that is too expensive. If this is the case, you can either change the default StorageClass or disable it completely to avoid dynamic provisioning of storage. Deleting the default StorageClass may not work, as it may be re-created automatically by the addon manager running in your cluster. Please consult the docs for your installation for details about addon manager and how to disable individual addons. ## Changing the default StorageClass 1. List the StorageClasses in your cluster: ```bash kubectl get storageclass ``` The output is similar to this: ```bash NAME PROVISIONER AGE standard (default) kubernetes.io/gce-pd 1d gold kubernetes.io/gce-pd 1d ``` The default StorageClass is marked by `(default)`. 1. Mark the default StorageClass as non-default: The default StorageClass has an annotation `storageclass.kubernetes.io/is-default-class` set to `true`. Any other value or absence of the annotation is interpreted as `false`. To mark a StorageClass as non-default, you need to change its value to `false`: ```bash kubectl patch storageclass standard -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"false"}}}' ``` where `standard` is the name of your chosen StorageClass. 1. Mark a StorageClass as default: Similar to the previous step, you need to add/set the annotation `storageclass.kubernetes.io/is-default-class=true`. ```bash kubectl patch storageclass gold -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true"}}}' ``` Please note you can have multiple `StorageClass` marked as default. If more than one `StorageClass` is marked as default, a `PersistentVolumeClaim` without an explicitly defined `storageClassName` will be created using the most recently created default `StorageClass`. When a `PersistentVolumeClaim` is created with a specified `volumeName`, it remains in a pending state if the static volume's `storageClassName` does not match the `StorageClass` on the `PersistentVolumeClaim`. 1. Verify that your chosen StorageClass is default: ```bash kubectl get storageclass ``` The output is similar to this: ```bash NAME PROVISIONER AGE standard kubernetes.io/gce-pd 1d gold (default) kubernetes.io/gce-pd 1d ``` ## {{% heading "whatsnext" %}} \* Learn more about [PersistentVolumes](/docs/concepts/storage/persistent-volumes/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/change-default-storage-class.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/change-default-storage-class.md
|
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|
{{< feature-state for\_k8s\_version="v1.21" state="stable" >}} This document describes how to configure and use kernel parameters within a Kubernetes cluster using the {{< glossary\_tooltip term\_id="sysctl" >}} interface. {{< note >}} Starting from Kubernetes version 1.23, the kubelet supports the use of either `/` or `.` as separators for sysctl names. Starting from Kubernetes version 1.25, setting Sysctls for a Pod supports setting sysctls with slashes. For example, you can represent the same sysctl name as `kernel.shm\_rmid\_forced` using a period as the separator, or as `kernel/shm\_rmid\_forced` using a slash as a separator. For more sysctl parameter conversion method details, please refer to the page [sysctl.d(5)](https://man7.org/linux/man-pages/man5/sysctl.d.5.html) from the Linux man-pages project. {{< /note >}} ## {{% heading "prerequisites" %}} {{< note >}} `sysctl` is a Linux-specific command-line tool used to configure various kernel parameters and it is not available on non-Linux operating systems. {{< /note >}} {{< include "task-tutorial-prereqs.md" >}} For some steps, you also need to be able to reconfigure the command line options for the kubelets running on your cluster. ## Listing all Sysctl Parameters In Linux, the sysctl interface allows an administrator to modify kernel parameters at runtime. Parameters are available via the `/proc/sys/` virtual process file system. The parameters cover various subsystems such as: - kernel (common prefix: `kernel.`) - networking (common prefix: `net.`) - virtual memory (common prefix: `vm.`) - MDADM (common prefix: `dev.`) - More subsystems are described in [Kernel docs](https://www.kernel.org/doc/Documentation/sysctl/README). To get a list of all parameters, you can run ```shell sudo sysctl -a ``` ## Safe and Unsafe Sysctls Kubernetes classes sysctls as either \_safe\_ or \_unsafe\_. In addition to proper namespacing, a \_safe\_ sysctl must be properly \_isolated\_ between pods on the same node. This means that setting a \_safe\_ sysctl for one pod - must not have any influence on any other pod on the node - must not allow to harm the node's health - must not allow to gain CPU or memory resources outside of the resource limits of a pod. By far, most of the \_namespaced\_ sysctls are not necessarily considered \_safe\_. The following sysctls are supported in the \_safe\_ set: - `kernel.shm\_rmid\_forced`; - `net.ipv4.ip\_local\_port\_range`; - `net.ipv4.tcp\_syncookies`; - `net.ipv4.ping\_group\_range` (since Kubernetes 1.18); - `net.ipv4.ip\_unprivileged\_port\_start` (since Kubernetes 1.22); - `net.ipv4.ip\_local\_reserved\_ports` (since Kubernetes 1.27, needs kernel 3.16+); - `net.ipv4.tcp\_keepalive\_time` (since Kubernetes 1.29, needs kernel 4.5+); - `net.ipv4.tcp\_fin\_timeout` (since Kubernetes 1.29, needs kernel 4.6+); - `net.ipv4.tcp\_keepalive\_intvl` (since Kubernetes 1.29, needs kernel 4.5+); - `net.ipv4.tcp\_keepalive\_probes` (since Kubernetes 1.29, needs kernel 4.5+). - `net.ipv4.tcp\_rmem` (since Kubernetes 1.32, needs kernel 4.15+). - `net.ipv4.tcp\_wmem` (since Kubernetes 1.32, needs kernel 4.15+). {{< note >}} There are some exceptions to the set of safe sysctls: - The `net.\*` sysctls are not allowed with host networking enabled. - The `net.ipv4.tcp\_syncookies` sysctl is not namespaced on Linux kernel version 4.5 or lower. {{< /note >}} This list will be extended in future Kubernetes versions when the kubelet supports better isolation mechanisms. ### Enabling Unsafe Sysctls All \_safe\_ sysctls are enabled by default. All \_unsafe\_ sysctls are disabled by default and must be allowed manually by the cluster admin on a per-node basis. Pods with disabled unsafe sysctls will be scheduled, but will fail to launch. With the warning above in mind, the cluster admin can allow certain \_unsafe\_ sysctls for very special situations such as high-performance or real-time application tuning. \_Unsafe\_ sysctls are enabled on a node-by-node basis with a flag of the kubelet; for example: ```shell kubelet --allowed-unsafe-sysctls \ 'kernel.msg\*,net.core.somaxconn' ... ``` For {{< glossary\_tooltip term\_id="minikube" >}}, this can be done via the `extra-config` flag: ```shell minikube start --extra-config="kubelet.allowed-unsafe-sysctls=kernel.msg\*,net.core.somaxconn"... ``` Only \_namespaced\_ sysctls can be enabled this way. ## Setting
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/sysctl-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/sysctl-cluster.md
|
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] | 0.118178
|
sysctls are enabled on a node-by-node basis with a flag of the kubelet; for example: ```shell kubelet --allowed-unsafe-sysctls \ 'kernel.msg\*,net.core.somaxconn' ... ``` For {{< glossary\_tooltip term\_id="minikube" >}}, this can be done via the `extra-config` flag: ```shell minikube start --extra-config="kubelet.allowed-unsafe-sysctls=kernel.msg\*,net.core.somaxconn"... ``` Only \_namespaced\_ sysctls can be enabled this way. ## Setting Sysctls for a Pod A number of sysctls are \_namespaced\_ in today's Linux kernels. This means that they can be set independently for each pod on a node. Only namespaced sysctls are configurable via the pod securityContext within Kubernetes. The following sysctls are known to be namespaced. This list could change in future versions of the Linux kernel. - `kernel.shm\*`, - `kernel.msg\*`, - `kernel.sem`, - `fs.mqueue.\*`, - Those `net.\*` that can be set in container networking namespace. However, there are exceptions (e.g., `net.netfilter.nf\_conntrack\_max` and `net.netfilter.nf\_conntrack\_expect\_max` can be set in container networking namespace but are unnamespaced before Linux 5.12.2). Sysctls with no namespace are called \_node-level\_ sysctls. If you need to set them, you must manually configure them on each node's operating system, or by using a DaemonSet with privileged containers. Use the pod securityContext to configure namespaced sysctls. The securityContext applies to all containers in the same pod. This example uses the pod securityContext to set a safe sysctl `kernel.shm\_rmid\_forced` and two unsafe sysctls `net.core.somaxconn` and `kernel.msgmax`. There is no distinction between \_safe\_ and \_unsafe\_ sysctls in the specification. {{< warning >}} Only modify sysctl parameters after you understand their effects, to avoid destabilizing your operating system. {{< /warning >}} ```yaml apiVersion: v1 kind: Pod metadata: name: sysctl-example spec: securityContext: sysctls: - name: kernel.shm\_rmid\_forced value: "0" - name: net.core.somaxconn value: "1024" - name: kernel.msgmax value: "65536" ... ``` {{< warning >}} Due to their nature of being \_unsafe\_, the use of \_unsafe\_ sysctls is at-your-own-risk and can lead to severe problems like wrong behavior of containers, resource shortage or complete breakage of a node. {{< /warning >}} It is good practice to consider nodes with special sysctl settings as \_tainted\_ within a cluster, and only schedule pods onto them which need those sysctl settings. It is suggested to use the Kubernetes [\_taints and toleration\_ feature](/docs/reference/generated/kubectl/kubectl-commands/#taint) to implement this. A pod with the \_unsafe\_ sysctls will fail to launch on any node which has not enabled those two \_unsafe\_ sysctls explicitly. As with \_node-level\_ sysctls it is recommended to use [\_taints and toleration\_ feature](/docs/reference/generated/kubectl/kubectl-commands/#taint) or [taints on nodes](/docs/concepts/scheduling-eviction/taint-and-toleration/) to schedule those pods onto the right nodes.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/sysctl-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/sysctl-cluster.md
|
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|
This page provides an overview of the steps you should follow to upgrade a Kubernetes cluster. The Kubernetes project recommends upgrading to the latest patch releases promptly, and to ensure that you are running a supported minor release of Kubernetes. Following this recommendation helps you to stay secure. The way that you upgrade a cluster depends on how you initially deployed it and on any subsequent changes. At a high level, the steps you perform are: - Upgrade the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} - Upgrade the nodes in your cluster - Upgrade clients such as {{< glossary\_tooltip text="kubectl" term\_id="kubectl" >}} - Adjust manifests and other resources based on the API changes that accompany the new Kubernetes version ## {{% heading "prerequisites" %}} You must have an existing cluster. This page is about upgrading from Kubernetes {{< skew currentVersionAddMinor -1 >}} to Kubernetes {{< skew currentVersion >}}. If your cluster is not currently running Kubernetes {{< skew currentVersionAddMinor -1 >}} then please check the documentation for the version of Kubernetes that you plan to upgrade to. {{< note >}} On Linux nodes, the kubelet defaults to supporting only cgroups v2. For Kubernetes {{< skew currentVersion >}} the `FailCgroupV1` kubelet configuration option is set to `true` by default. To learn more, refer to the [Kubernetes cgroup v1 deprecation documentation](/docs/concepts/architecture/cgroups/#deprecation-of-cgroup-v1). {{}} ## Upgrade approaches ### kubeadm {#upgrade-kubeadm} If your cluster was deployed using the `kubeadm` tool, refer to [Upgrading kubeadm clusters](/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) for detailed information on how to upgrade the cluster. Once you have upgraded the cluster, remember to [install the latest version of `kubectl`](/docs/tasks/tools/). ### Manual deployments {{< caution >}} These steps do not account for third-party extensions such as network and storage plugins. {{< /caution >}} You should manually update the control plane following this sequence: - etcd (all instances) - kube-apiserver (all control plane hosts) - kube-controller-manager - kube-scheduler - cloud controller manager, if you use one At this point you should [install the latest version of `kubectl`](/docs/tasks/tools/). For each node in your cluster, [drain](/docs/tasks/administer-cluster/safely-drain-node/) that node and then either replace it with a new node that uses the {{< skew currentVersion >}} kubelet, or upgrade the kubelet on that node and bring the node back into service. {{< caution >}} Draining nodes before upgrading kubelet ensures that pods are re-admitted and containers are re-created, which may be necessary to resolve some security issues or other important bugs. {{}} ### Other deployments {#upgrade-other} Refer to the documentation for your cluster deployment tool to learn the recommended set up steps for maintenance. ## Post-upgrade tasks ### Switch your cluster's storage API version The objects that are serialized into etcd for a cluster's internal representation of the Kubernetes resources active in the cluster are written using a particular version of the API. When the supported API changes, these objects may need to be rewritten in the newer API. Failure to do this will eventually result in resources that are no longer decodable or usable by the Kubernetes API server. For each affected object, fetch it using the latest supported API and then write it back also using the latest supported API. ### Update manifests Upgrading to a new Kubernetes version can provide new APIs. You can use `kubectl convert` command to convert manifests between different API versions. For example: ```shell kubectl convert -f pod.yaml --output-version v1 ``` The `kubectl` tool replaces the contents of `pod.yaml` with a manifest that sets `kind` to Pod (unchanged), but with a revised `apiVersion`. ### Device Plugins If your cluster is running device plugins and the node needs to be upgraded to a Kubernetes release with
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/cluster-upgrade.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/cluster-upgrade.md
|
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] | 0.044604
|
convert -f pod.yaml --output-version v1 ``` The `kubectl` tool replaces the contents of `pod.yaml` with a manifest that sets `kind` to Pod (unchanged), but with a revised `apiVersion`. ### Device Plugins If your cluster is running device plugins and the node needs to be upgraded to a Kubernetes release with a newer device plugin API version, device plugins must be upgraded to support both version before the node is upgraded in order to guarantee that device allocations continue to complete successfully during the upgrade. Refer to [API compatibility](/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/#api-compatibility) and [Kubelet Device Manager API Versions](/docs/reference/node/device-plugin-api-versions/) for more details.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/cluster-upgrade.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/cluster-upgrade.md
|
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|
This document covers topics related to protecting a cluster from accidental or malicious access and provides recommendations on overall security. ## {{% heading "prerequisites" %}} \* {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Controlling access to the Kubernetes API As Kubernetes is entirely API-driven, controlling and limiting who can access the cluster and what actions they are allowed to perform is the first line of defense. ### Use Transport Layer Security (TLS) for all API traffic Kubernetes expects that all API communication in the cluster is encrypted by default with TLS, and the majority of installation methods will allow the necessary certificates to be created and distributed to the cluster components. Note that some components and installation methods may enable local ports over HTTP and administrators should familiarize themselves with the settings of each component to identify potentially unsecured traffic. ### API Authentication Choose an authentication mechanism for the API servers to use that matches the common access patterns when you install a cluster. For instance, small, single-user clusters may wish to use a simple certificate or static Bearer token approach. Larger clusters may wish to integrate an existing OIDC or LDAP server that allow users to be subdivided into groups. All API clients must be authenticated, even those that are part of the infrastructure like nodes, proxies, the scheduler, and volume plugins. These clients are typically [service accounts](/docs/reference/access-authn-authz/service-accounts-admin/) or use x509 client certificates, and they are created automatically at cluster startup or are setup as part of the cluster installation. Consult the [authentication reference document](/docs/reference/access-authn-authz/authentication/) for more information. ### API Authorization Once authenticated, every API call is also expected to pass an authorization check. Kubernetes ships an integrated [Role-Based Access Control (RBAC)](/docs/reference/access-authn-authz/rbac/) component that matches an incoming user or group to a set of permissions bundled into roles. These permissions combine verbs (get, create, delete) with resources (pods, services, nodes) and can be namespace-scoped or cluster-scoped. A set of out-of-the-box roles are provided that offer reasonable default separation of responsibility depending on what actions a client might want to perform. It is recommended that you use the [Node](/docs/reference/access-authn-authz/node/) and [RBAC](/docs/reference/access-authn-authz/rbac/) authorizers together, in combination with the [NodeRestriction](/docs/reference/access-authn-authz/admission-controllers/#noderestriction) admission plugin. As with authentication, simple and broad roles may be appropriate for smaller clusters, but as more users interact with the cluster, it may become necessary to separate teams into separate {{< glossary\_tooltip text="namespaces" term\_id="namespace" >}} with more limited roles. With authorization, it is important to understand how updates on one object may cause actions in other places. For instance, a user may not be able to create pods directly, but allowing them to create a deployment, which creates pods on their behalf, will let them create those pods indirectly. Likewise, deleting a node from the API will result in the pods scheduled to that node being terminated and recreated on other nodes. The out-of-the box roles represent a balance between flexibility and common use cases, but more limited roles should be carefully reviewed to prevent accidental escalation. You can make roles specific to your use case if the out-of-box ones don't meet your needs. Consult the [authorization reference section](/docs/reference/access-authn-authz/authorization/) for more information. ## Controlling access to the Kubelet Kubelets expose HTTPS endpoints which grant powerful control over the node and containers. By default Kubelets allow unauthenticated access to this API. Production clusters should enable Kubelet authentication and authorization. Consult the [Kubelet authentication/authorization reference](/docs/reference/access-authn-authz/kubelet-authn-authz/) for more information. ## Controlling the capabilities of a workload or user at runtime Authorization in Kubernetes is intentionally high level, focused on coarse actions on resources. More powerful controls exist as \*\*policies\*\* to limit by
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
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] | 0.17471
|
API. Production clusters should enable Kubelet authentication and authorization. Consult the [Kubelet authentication/authorization reference](/docs/reference/access-authn-authz/kubelet-authn-authz/) for more information. ## Controlling the capabilities of a workload or user at runtime Authorization in Kubernetes is intentionally high level, focused on coarse actions on resources. More powerful controls exist as \*\*policies\*\* to limit by use case how those objects act on the cluster, themselves, and other resources. ### Limiting resource usage on a cluster [Resource quota](/docs/concepts/policy/resource-quotas/) limits the number or capacity of resources granted to a namespace. This is most often used to limit the amount of CPU, memory, or persistent disk a namespace can allocate, but can also control how many pods, services, or volumes exist in each namespace. [Limit ranges](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) restrict the maximum or minimum size of some of the resources above, to prevent users from requesting unreasonably high or low values for commonly reserved resources like memory, or to provide default limits when none are specified. ### Controlling what privileges containers run with A pod definition contains a [security context](/docs/tasks/configure-pod-container/security-context/) that allows it to request access to run as a specific Linux user on a node (like root), access to run privileged or access the host network, and other controls that would otherwise allow it to run unfettered on a hosting node. You can configure [Pod security admission](/docs/concepts/security/pod-security-admission/) to enforce use of a particular [Pod Security Standard](/docs/concepts/security/pod-security-standards/) in a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}, or to detect breaches. Generally, most application workloads need limited access to host resources so they can successfully run as a root process (uid 0) without access to host information. However, considering the privileges associated with the root user, you should write application containers to run as a non-root user. Similarly, administrators who wish to prevent client applications from escaping their containers should apply the \*\*Baseline\*\* or \*\*Restricted\*\* Pod Security Standard. ### Preventing containers from loading unwanted kernel modules The Linux kernel automatically loads kernel modules from disk if needed in certain circumstances, such as when a piece of hardware is attached or a filesystem is mounted. Of particular relevance to Kubernetes, even unprivileged processes can cause certain network-protocol-related kernel modules to be loaded, just by creating a socket of the appropriate type. This may allow an attacker to exploit a security hole in a kernel module that the administrator assumed was not in use. To prevent specific modules from being automatically loaded, you can uninstall them from the node, or add rules to block them. On most Linux distributions, you can do that by creating a file such as `/etc/modprobe.d/kubernetes-blacklist.conf` with contents like: ``` # DCCP is unlikely to be needed, has had multiple serious # vulnerabilities, and is not well-maintained. blacklist dccp # SCTP is not used in most Kubernetes clusters, and has also had # vulnerabilities in the past. blacklist sctp ``` To block module loading more generically, you can use a Linux Security Module (such as SELinux) to completely deny the `module\_request` permission to containers, preventing the kernel from loading modules for containers under any circumstances. (Pods would still be able to use modules that had been loaded manually, or modules that were loaded by the kernel on behalf of some more-privileged process.) ### Restricting network access The [network policies](/docs/tasks/administer-cluster/declare-network-policy/) for a namespace allows application authors to restrict which pods in other namespaces may access pods and ports within their namespaces. Many of the supported [Kubernetes networking providers](/docs/concepts/cluster-administration/networking/) now respect network policy. Quota and limit ranges can also be used to control whether users may request node ports or load-balanced services, which on many clusters can control whether those users applications are visible
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
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] | 0.237202
|
may access pods and ports within their namespaces. Many of the supported [Kubernetes networking providers](/docs/concepts/cluster-administration/networking/) now respect network policy. Quota and limit ranges can also be used to control whether users may request node ports or load-balanced services, which on many clusters can control whether those users applications are visible outside of the cluster. Additional protections may be available that control network rules on a per-plugin or per- environment basis, such as per-node firewalls, physically separating cluster nodes to prevent cross talk, or advanced networking policy. ### Restricting cloud metadata API access Cloud platforms (AWS, Azure, GCE, etc.) often expose metadata services locally to instances. By default these APIs are accessible by pods running on an instance and can contain cloud credentials for that node, or provisioning data such as kubelet credentials. These credentials can be used to escalate within the cluster or to other cloud services under the same account. When running Kubernetes on a cloud platform, limit permissions given to instance credentials, use [network policies](/docs/tasks/administer-cluster/declare-network-policy/) to restrict pod access to the metadata API, and avoid using provisioning data to deliver secrets. ### Controlling which nodes pods may access By default, there are no restrictions on which nodes may run a pod. Kubernetes offers a [rich set of policies for controlling placement of pods onto nodes](/docs/concepts/scheduling-eviction/assign-pod-node/) and the [taint-based pod placement and eviction](/docs/concepts/scheduling-eviction/taint-and-toleration/) that are available to end users. For many clusters use of these policies to separate workloads can be a convention that authors adopt or enforce via tooling. As an administrator, a beta admission plugin `PodNodeSelector` can be used to force pods within a namespace to default or require a specific node selector, and if end users cannot alter namespaces, this can strongly limit the placement of all of the pods in a specific workload. ## Protecting cluster components from compromise This section describes some common patterns for protecting clusters from compromise. ### Restrict access to etcd Write access to the etcd backend for the API is equivalent to gaining root on the entire cluster, and read access can be used to escalate fairly quickly. Administrators should always use strong credentials from the API servers to their etcd server, such as mutual auth via TLS client certificates, and it is often recommended to isolate the etcd servers behind a firewall that only the API servers may access. {{< caution >}} Allowing other components within the cluster to access the master etcd instance with read or write access to the full keyspace is equivalent to granting cluster-admin access. Using separate etcd instances for non-master components or using etcd ACLs to restrict read and write access to a subset of the keyspace is strongly recommended. {{< /caution >}} ### Enable audit logging The [audit logger](/docs/tasks/debug/debug-cluster/audit/) is a beta feature that records actions taken by the API for later analysis in the event of a compromise. It is recommended to enable audit logging and archive the audit file on a secure server. ### Restrict access to alpha or beta features Alpha and beta Kubernetes features are in active development and may have limitations or bugs that result in security vulnerabilities. Always assess the value an alpha or beta feature may provide against the possible risk to your security posture. When in doubt, disable features you do not use. ### Rotate infrastructure credentials frequently The shorter the lifetime of a secret or credential the harder it is for an attacker to make use of that credential. Set short lifetimes on certificates and automate their rotation. Use an authentication provider that can control how long issued tokens are available and use short
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
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] | 0.142015
|
infrastructure credentials frequently The shorter the lifetime of a secret or credential the harder it is for an attacker to make use of that credential. Set short lifetimes on certificates and automate their rotation. Use an authentication provider that can control how long issued tokens are available and use short lifetimes where possible. If you use service-account tokens in external integrations, plan to rotate those tokens frequently. For example, once the bootstrap phase is complete, a bootstrap token used for setting up nodes should be revoked or its authorization removed. ### Review third party integrations before enabling them Many third party integrations to Kubernetes may alter the security profile of your cluster. When enabling an integration, always review the permissions that an extension requests before granting it access. For example, many security integrations may request access to view all secrets on your cluster which is effectively making that component a cluster admin. When in doubt, restrict the integration to functioning in a single namespace if possible. Components that create pods may also be unexpectedly powerful if they can do so inside namespaces like the `kube-system` namespace, because those pods can gain access to service account secrets or run with elevated permissions if those service accounts are granted access to permissive [PodSecurityPolicies](/docs/concepts/security/pod-security-policy/). If you use [Pod Security admission](/docs/concepts/security/pod-security-admission/) and allow any component to create Pods within a namespace that permits privileged Pods, those Pods may be able to escape their containers and use this widened access to elevate their privileges. You should not allow untrusted components to create Pods in any system namespace (those with names that start with `kube-`) nor in any namespace where that access grant allows the possibility of privilege escalation. ### Encrypt secrets at rest In general, the etcd database will contain any information accessible via the Kubernetes API and may grant an attacker significant visibility into the state of your cluster. Always encrypt your backups using a well reviewed backup and encryption solution, and consider using full disk encryption where possible. Kubernetes supports optional [encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) for information in the Kubernetes API. This lets you ensure that when Kubernetes stores data for objects (for example, `Secret` or `ConfigMap` objects), the API server writes an encrypted representation of the object. That encryption means that even someone who has access to etcd backup data is unable to view the content of those objects. In Kubernetes {{< skew currentVersion >}} you can also encrypt custom resources; encryption-at-rest for extension APIs defined in CustomResourceDefinitions was added to Kubernetes as part of the v1.26 release. ### Receiving alerts for security updates and reporting vulnerabilities Join the [kubernetes-announce](https://groups.google.com/forum/#!forum/kubernetes-announce) group for emails about security announcements. See the [security reporting](/docs/reference/issues-security/security/) page for more on how to report vulnerabilities. ## What's next - [Security Checklist](/docs/concepts/security/security-checklist/) for additional information on Kubernetes security guidance. - [Seccomp Node Reference](/docs/reference/node/seccomp/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/securing-a-cluster.md
|
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|
All of the APIs in Kubernetes that let you write persistent API resource data support at-rest encryption. For example, you can enable at-rest encryption for {{< glossary\_tooltip text="Secrets" term\_id="secret" >}}. This at-rest encryption is additional to any system-level encryption for the etcd cluster or for the filesystem(s) on hosts where you are running the kube-apiserver. This page shows how to switch from encryption of API data at rest, so that API data are stored unencrypted. You might want to do this to improve performance; usually, though, if it was a good idea to encrypt some data, it's also a good idea to leave them encrypted. {{< note >}} This task covers encryption for resource data stored using the {{< glossary\_tooltip text="Kubernetes API" term\_id="kubernetes-api" >}}. For example, you can encrypt Secret objects, including the key-value data they contain. If you wanted to manage encryption for data in filesystems that are mounted into containers, you instead need to either: - use a storage integration that provides encrypted {{< glossary\_tooltip text="volumes" term\_id="volume" >}} - encrypt the data within your own application {{< /note >}} ## {{% heading "prerequisites" %}} \* {{< include "task-tutorial-prereqs.md" >}} \* This task assumes that you are running the Kubernetes API server as a {{< glossary\_tooltip text="static pod" term\_id="static-pod" >}} on each control plane node. \* Your cluster's control plane \*\*must\*\* use etcd v3.x (major version 3, any minor version). \* To encrypt a custom resource, your cluster must be running Kubernetes v1.26 or newer. \* You should have some API data that are already encrypted. {{< version-check >}} ## Determine whether encryption at rest is already enabled By default, the API server uses an `identity` provider that stores plain-text representations of resources. \*\*The default `identity` provider does not provide any confidentiality protection.\*\* The `kube-apiserver` process accepts an argument `--encryption-provider-config` that specifies a path to a configuration file. The contents of that file, if you specify one, control how Kubernetes API data is encrypted in etcd. If it is not specified, you do not have encryption at rest enabled. The format of that configuration file is YAML, representing a configuration API kind named [`EncryptionConfiguration`](/docs/reference/config-api/apiserver-config.v1/). You can see an example configuration in [Encryption at rest configuration](/docs/tasks/administer-cluster/encrypt-data/#understanding-the-encryption-at-rest-configuration). If `--encryption-provider-config` is set, check which resources (such as `secrets`) are configured for encryption, and what provider is used. Make sure that the preferred provider for that resource type is \*\*not\*\* `identity`; you only set `identity` (\_no encryption\_) as default when you want to disable encryption at rest. Verify that the first-listed provider for a resource is something \*\*other\*\* than `identity`, which means that any new information written to resources of that type will be encrypted as configured. If you do see `identity` as the first-listed provider for any resource, this means that those resources are being written out to etcd without encryption. ## Decrypt all data {#decrypting-all-data} This example shows how to stop encrypting the Secret API at rest. If you are encrypting other API kinds, adjust the steps to match. ### Locate the encryption configuration file First, find the API server configuration files. On each control plane node, static Pod manifest for the kube-apiserver specifies a command line argument, `--encryption-provider-config`. You are likely to find that this file is mounted into the static Pod using a [`hostPath`](/docs/concepts/storage/volumes/#hostpath) volume mount. Once you locate the volume you can find the file on the node filesystem and inspect it. ### Configure the API server to decrypt objects To disable encryption at rest, place the `identity` provider as the first entry in your encryption configuration file. For example, if your existing EncryptionConfiguration file reads: ```yaml ---
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/decrypt-data.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/decrypt-data.md
|
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|
the volume you can find the file on the node filesystem and inspect it. ### Configure the API server to decrypt objects To disable encryption at rest, place the `identity` provider as the first entry in your encryption configuration file. For example, if your existing EncryptionConfiguration file reads: ```yaml --- apiVersion: apiserver.config.k8s.io/v1 kind: EncryptionConfiguration resources: - resources: - secrets providers: - aescbc: keys: # Do not use this (invalid) example key for encryption - name: example secret: 2KfZgdiq2K0g2YrYpyDYs9mF2LPZhQ== ``` then change it to: ```yaml --- apiVersion: apiserver.config.k8s.io/v1 kind: EncryptionConfiguration resources: - resources: - secrets providers: - identity: {} # add this line - aescbc: keys: - name: example secret: 2KfZgdiq2K0g2YrYpyDYs9mF2LPZhQ== ``` and restart the kube-apiserver Pod on this node. ### Reconfigure other control plane hosts {#api-server-config-update-more-1} If you have multiple API servers in your cluster, you should deploy the changes in turn to each API server. Make sure that you use the same encryption configuration on each control plane host. ### Force decryption Then run the following command to force decryption of all Secrets: ```shell # If you are decrypting a different kind of object, change "secrets" to match. kubectl get secrets --all-namespaces -o json | kubectl replace -f - ``` Once you have replaced \*\*all\*\* existing encrypted resources with backing data that don't use encryption, you can remove the encryption settings from the `kube-apiserver`. The command line options to remove are: - `--encryption-provider-config` - `--encryption-provider-config-automatic-reload` Restart the kube-apiserver Pod again to apply the new configuration. ### Reconfigure other control plane hosts {#api-server-config-update-more-2} If you have multiple API servers in your cluster, you should again deploy the changes in turn to each API server. Make sure that you use the same encryption configuration on each control plane host. ## {{% heading "whatsnext" %}} \* Learn more about the [EncryptionConfiguration configuration API (v1)](/docs/reference/config-api/apiserver-config.v1/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/decrypt-data.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/decrypt-data.md
|
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] | -0.003178
|
This example demonstrates how to limit the amount of storage consumed in a namespace. The following resources are used in the demonstration: [ResourceQuota](/docs/concepts/policy/resource-quotas/), [LimitRange](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/), and [PersistentVolumeClaim](/docs/concepts/storage/persistent-volumes/). ## {{% heading "prerequisites" %}} \* {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Scenario: Limiting Storage Consumption The cluster-admin is operating a cluster on behalf of a user population and the admin wants to control how much storage a single namespace can consume in order to control cost. The admin would like to limit: 1. The number of persistent volume claims in a namespace 2. The amount of storage each claim can request 3. The amount of cumulative storage the namespace can have ## LimitRange to limit requests for storage Adding a `LimitRange` to a namespace enforces storage request sizes to a minimum and maximum. Storage is requested via `PersistentVolumeClaim`. The admission controller that enforces limit ranges will reject any PVC that is above or below the values set by the admin. In this example, a PVC requesting 10Gi of storage would be rejected because it exceeds the 2Gi max. ```yaml apiVersion: v1 kind: LimitRange metadata: name: storagelimits spec: limits: - type: PersistentVolumeClaim max: storage: 2Gi min: storage: 1Gi ``` Minimum storage requests are used when the underlying storage provider requires certain minimums. For example, AWS EBS volumes have a 1Gi minimum requirement. ## ResourceQuota to limit PVC count and cumulative storage capacity Admins can limit the number of PVCs in a namespace as well as the cumulative capacity of those PVCs. New PVCs that exceed either maximum value will be rejected. In this example, a 6th PVC in the namespace would be rejected because it exceeds the maximum count of 5. Alternatively, a 5Gi maximum quota when combined with the 2Gi max limit above, cannot have 3 PVCs where each has 2Gi. That would be 6Gi requested for a namespace capped at 5Gi. ```yaml apiVersion: v1 kind: ResourceQuota metadata: name: storagequota spec: hard: persistentvolumeclaims: "5" requests.storage: "5Gi" ``` ## Summary A limit range can put a ceiling on how much storage is requested while a resource quota can effectively cap the storage consumed by a namespace through claim counts and cumulative storage capacity. The allows a cluster-admin to plan their cluster's storage budget without risk of any one project going over their allotment.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/limit-storage-consumption.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/limit-storage-consumption.md
|
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|
This page shows how to change the reclaim policy of a Kubernetes PersistentVolume. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Why change reclaim policy of a PersistentVolume PersistentVolumes can have various reclaim policies, including "Retain", "Recycle", and "Delete". For dynamically provisioned PersistentVolumes, the default reclaim policy is "Delete". This means that a dynamically provisioned volume is automatically deleted when a user deletes the corresponding PersistentVolumeClaim. This automatic behavior might be inappropriate if the volume contains precious data. In that case, it is more appropriate to use the "Retain" policy. With the "Retain" policy, if a user deletes a PersistentVolumeClaim, the corresponding PersistentVolume will not be deleted. Instead, it is moved to the Released phase, where all of its data can be manually recovered. ## Changing the reclaim policy of a PersistentVolume 1. List the PersistentVolumes in your cluster: ```shell kubectl get pv ``` The output is similar to this: ```none NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 10s pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 6s pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim3 manual 3s ``` This list also includes the name of the claims that are bound to each volume for easier identification of dynamically provisioned volumes. 1. Choose one of your PersistentVolumes and change its reclaim policy: ```shell kubectl patch pv -p '{"spec":{"persistentVolumeReclaimPolicy":"Retain"}}' ``` where `` is the name of your chosen PersistentVolume. {{< note >}} On Windows, you must \_double\_ quote any JSONPath template that contains spaces (not single quote as shown above for bash). This in turn means that you must use a single quote or escaped double quote around any literals in the template. For example: ```cmd kubectl patch pv -p "{\"spec\":{\"persistentVolumeReclaimPolicy\":\"Retain\"}}" ``` {{< /note >}} 1. Verify that your chosen PersistentVolume has the right policy: ```shell kubectl get pv ``` The output is similar to this: ```none NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 40s pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 36s pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Retain Bound default/claim3 manual 33s ``` In the preceding output, you can see that the volume bound to claim `default/claim3` has reclaim policy `Retain`. It will not be automatically deleted when a user deletes claim `default/claim3`. ## {{% heading "whatsnext" %}} \* Learn more about [PersistentVolumes](/docs/concepts/storage/persistent-volumes/). \* Learn more about [PersistentVolumeClaims](/docs/concepts/storage/persistent-volumes/#persistentvolumeclaims). ### References {#reference} \* {{< api-reference page="config-and-storage-resources/persistent-volume-v1" >}} \* Pay attention to the `.spec.persistentVolumeReclaimPolicy` [field](/docs/reference/kubernetes-api/config-and-storage-resources/persistent-volume-v1/#PersistentVolumeSpec) of PersistentVolume. \* {{< api-reference page="config-and-storage-resources/persistent-volume-claim-v1" >}}
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/change-pv-reclaim-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/change-pv-reclaim-policy.md
|
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|
{{< glossary\_definition term\_id="cloud-controller-manager" length="all" prepend="The cloud-controller-manager is">}} ## Background As part of the [cloud provider extraction effort](/blog/2019/04/17/the-future-of-cloud-providers-in-kubernetes/), all cloud specific controllers must be moved out of the `kube-controller-manager`. All existing clusters that run cloud controllers in the `kube-controller-manager` must migrate to instead run the controllers in a cloud provider specific `cloud-controller-manager`. Leader Migration provides a mechanism in which HA clusters can safely migrate "cloud specific" controllers between the `kube-controller-manager` and the `cloud-controller-manager` via a shared resource lock between the two components while upgrading the replicated control plane. For a single-node control plane, or if unavailability of controller managers can be tolerated during the upgrade, Leader Migration is not needed and this guide can be ignored. Leader Migration can be enabled by setting `--enable-leader-migration` on `kube-controller-manager` or `cloud-controller-manager`. Leader Migration only applies during the upgrade and can be safely disabled or left enabled after the upgrade is complete. This guide walks you through the manual process of upgrading the control plane from `kube-controller-manager` with built-in cloud provider to running both `kube-controller-manager` and `cloud-controller-manager`. If you use a tool to deploy and manage the cluster, please refer to the documentation of the tool and the cloud provider for specific instructions of the migration. ## {{% heading "prerequisites" %}} It is assumed that the control plane is running Kubernetes version N and to be upgraded to version N + 1. Although it is possible to migrate within the same version, ideally the migration should be performed as part of an upgrade so that changes of configuration can be aligned to each release. The exact versions of N and N + 1 depend on each cloud provider. For example, if a cloud provider builds a `cloud-controller-manager` to work with Kubernetes 1.24, then N can be 1.23 and N + 1 can be 1.24. The control plane nodes should run `kube-controller-manager` with Leader Election enabled, which is the default. As of version N, an in-tree cloud provider must be set with `--cloud-provider` flag and `cloud-controller-manager` should not yet be deployed. The out-of-tree cloud provider must have built a `cloud-controller-manager` with Leader Migration implementation. If the cloud provider imports `k8s.io/cloud-provider` and `k8s.io/controller-manager` of version v0.21.0 or later, Leader Migration will be available. However, for version before v0.22.0, Leader Migration is alpha and requires feature gate `ControllerManagerLeaderMigration` to be enabled in `cloud-controller-manager`. This guide assumes that kubelet of each control plane node starts `kube-controller-manager` and `cloud-controller-manager` as static pods defined by their manifests. If the components run in a different setting, please adjust the steps accordingly. For authorization, this guide assumes that the cluster uses RBAC. If another authorization mode grants permissions to `kube-controller-manager` and `cloud-controller-manager` components, please grant the needed access in a way that matches the mode. ### Grant access to Migration Lease The default permissions of the controller manager allow only accesses to their main Lease. In order for the migration to work, accesses to another Lease are required. You can grant `kube-controller-manager` full access to the leases API by modifying the `system::leader-locking-kube-controller-manager` role. This task guide assumes that the name of the migration lease is `cloud-provider-extraction-migration`. ```shell kubectl patch -n kube-system role 'system::leader-locking-kube-controller-manager' -p '{"rules": [ {"apiGroups":[ "coordination.k8s.io"], "resources": ["leases"], "resourceNames": ["cloud-provider-extraction-migration"], "verbs": ["create", "list", "get", "update"] } ]}' --type=merge` ``` Do the same to the `system::leader-locking-cloud-controller-manager` role. ```shell kubectl patch -n kube-system role 'system::leader-locking-cloud-controller-manager' -p '{"rules": [ {"apiGroups":[ "coordination.k8s.io"], "resources": ["leases"], "resourceNames": ["cloud-provider-extraction-migration"], "verbs": ["create", "list", "get", "update"] } ]}' --type=merge` ``` ### Initial Leader Migration configuration Leader Migration optionally takes a configuration file representing the state of controller-to-manager assignment. At this moment, with in-tree cloud provider, `kube-controller-manager` runs `route`, `service`, and
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
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] | 0.035936
|
role 'system::leader-locking-cloud-controller-manager' -p '{"rules": [ {"apiGroups":[ "coordination.k8s.io"], "resources": ["leases"], "resourceNames": ["cloud-provider-extraction-migration"], "verbs": ["create", "list", "get", "update"] } ]}' --type=merge` ``` ### Initial Leader Migration configuration Leader Migration optionally takes a configuration file representing the state of controller-to-manager assignment. At this moment, with in-tree cloud provider, `kube-controller-manager` runs `route`, `service`, and `cloud-node-lifecycle`. The following example configuration shows the assignment. Leader Migration can be enabled without a configuration. Please see [Default Configuration](#default-configuration) for details. ```yaml kind: LeaderMigrationConfiguration apiVersion: controllermanager.config.k8s.io/v1 leaderName: cloud-provider-extraction-migration resourceLock: leases controllerLeaders: - name: route component: kube-controller-manager - name: service component: kube-controller-manager - name: cloud-node-lifecycle component: kube-controller-manager ``` Alternatively, because the controllers can run under either controller managers, setting `component` to `\*` for both sides makes the configuration file consistent between both parties of the migration. ```yaml # wildcard version kind: LeaderMigrationConfiguration apiVersion: controllermanager.config.k8s.io/v1 leaderName: cloud-provider-extraction-migration resourceLock: leases controllerLeaders: - name: route component: \* - name: service component: \* - name: cloud-node-lifecycle component: \* ``` On each control plane node, save the content to `/etc/leadermigration.conf`, and update the manifest of `kube-controller-manager` so that the file is mounted inside the container at the same location. Also, update the same manifest to add the following arguments: - `--enable-leader-migration` to enable Leader Migration on the controller manager - `--leader-migration-config=/etc/leadermigration.conf` to set configuration file Restart `kube-controller-manager` on each node. At this moment, `kube-controller-manager` has leader migration enabled and is ready for the migration. ### Deploy Cloud Controller Manager In version N + 1, the desired state of controller-to-manager assignment can be represented by a new configuration file, shown as follows. Please note `component` field of each `controllerLeaders` changing from `kube-controller-manager` to `cloud-controller-manager`. Alternatively, use the wildcard version mentioned above, which has the same effect. ```yaml kind: LeaderMigrationConfiguration apiVersion: controllermanager.config.k8s.io/v1 leaderName: cloud-provider-extraction-migration resourceLock: leases controllerLeaders: - name: route component: cloud-controller-manager - name: service component: cloud-controller-manager - name: cloud-node-lifecycle component: cloud-controller-manager ``` When creating control plane nodes of version N + 1, the content should be deployed to `/etc/leadermigration.conf`. The manifest of `cloud-controller-manager` should be updated to mount the configuration file in the same manner as `kube-controller-manager` of version N. Similarly, add `--enable-leader-migration` and `--leader-migration-config=/etc/leadermigration.conf` to the arguments of `cloud-controller-manager`. Create a new control plane node of version N + 1 with the updated `cloud-controller-manager` manifest, and with the `--cloud-provider` flag set to `external` for `kube-controller-manager`. `kube-controller-manager` of version N + 1 MUST NOT have Leader Migration enabled because, with an external cloud provider, it does not run the migrated controllers anymore, and thus it is not involved in the migration. Please refer to [Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/) for more detail on how to deploy `cloud-controller-manager`. ### Upgrade Control Plane The control plane now contains nodes of both version N and N + 1. The nodes of version N run `kube-controller-manager` only, and these of version N + 1 run both `kube-controller-manager` and `cloud-controller-manager`. The migrated controllers, as specified in the configuration, are running under either `kube-controller-manager` of version N or `cloud-controller-manager` of version N + 1 depending on which controller manager holds the migration lease. No controller will ever be running under both controller managers at any time. In a rolling manner, create a new control plane node of version N + 1 and bring down one of version N until the control plane contains only nodes of version N + 1. If a rollback from version N + 1 to N is required, add nodes of version N with Leader Migration enabled for `kube-controller-manager` back to the control plane, replacing one of version N + 1 each time until there are only nodes of version N. ### (Optional) Disable Leader Migration {#disable-leader-migration} Now that
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
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] | 0.024674
|
from version N + 1 to N is required, add nodes of version N with Leader Migration enabled for `kube-controller-manager` back to the control plane, replacing one of version N + 1 each time until there are only nodes of version N. ### (Optional) Disable Leader Migration {#disable-leader-migration} Now that the control plane has been upgraded to run both `kube-controller-manager` and `cloud-controller-manager` of version N + 1, Leader Migration has finished its job and can be safely disabled to save one Lease resource. It is safe to re-enable Leader Migration for the rollback in the future. In a rolling manager, update manifest of `cloud-controller-manager` to unset both `--enable-leader-migration` and `--leader-migration-config=` flag, also remove the mount of `/etc/leadermigration.conf`, and finally remove `/etc/leadermigration.conf`. To re-enable Leader Migration, recreate the configuration file and add its mount and the flags that enable Leader Migration back to `cloud-controller-manager`. ### Default Configuration Starting Kubernetes 1.22, Leader Migration provides a default configuration suitable for the default controller-to-manager assignment. The default configuration can be enabled by setting `--enable-leader-migration` but without `--leader-migration-config=`. For `kube-controller-manager` and `cloud-controller-manager`, if there are no flags that enable any in-tree cloud provider or change ownership of controllers, the default configuration can be used to avoid manual creation of the configuration file. ### Special case: migrating the Node IPAM controller {#node-ipam-controller-migration} If your cloud provider provides an implementation of Node IPAM controller, you should switch to the implementation in `cloud-controller-manager`. Disable Node IPAM controller in `kube-controller-manager` of version N + 1 by adding `--controllers=\*,-nodeipam` to its flags. Then add `nodeipam` to the list of migrated controllers. ```yaml # wildcard version, with nodeipam kind: LeaderMigrationConfiguration apiVersion: controllermanager.config.k8s.io/v1 leaderName: cloud-provider-extraction-migration resourceLock: leases controllerLeaders: - name: route component: \* - name: service component: \* - name: cloud-node-lifecycle component: \* - name: nodeipam - component: \* ``` ## {{% heading "whatsnext" %}} - Read the [Controller Manager Leader Migration](https://github.com/kubernetes/enhancements/tree/master/keps/sig-cloud-provider/2436-controller-manager-leader-migration) enhancement proposal.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/controller-manager-leader-migration.md
|
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|
{{< feature-state for\_k8s\_version="v1.26" state="stable" >}} Kubernetes keeps many aspects of how pods execute on nodes abstracted from the user. This is by design. However, some workloads require stronger guarantees in terms of latency and/or performance in order to operate acceptably. The kubelet provides methods to enable more complex workload placement policies while keeping the abstraction free from explicit placement directives. For detailed information on resource management, please refer to the [Resource Management for Pods and Containers](/docs/concepts/configuration/manage-resources-containers) documentation. For detailed information on how the kubelet implements resource management, please refer to the [Node ResourceManagers](/docs/concepts/policy/node-resource-managers) documentation. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} If you are running an older version of Kubernetes, please look at the documentation for the version you are actually running. ## Configuring CPU management policies By default, the kubelet uses [CFS quota](https://en.wikipedia.org/wiki/Completely\_Fair\_Scheduler) to enforce pod CPU limits. When the node runs many CPU-bound pods, the workload can move to different CPU cores depending on whether the pod is throttled and which CPU cores are available at scheduling time. Many workloads are not sensitive to this migration and thus work fine without any intervention. However, in workloads where CPU cache affinity and scheduling latency significantly affect workload performance, the kubelet allows alternative CPU management policies to determine some placement preferences on the node. ## Windows Support {{< feature-state feature\_gate\_name="WindowsCPUAndMemoryAffinity" >}} CPU Manager support can be enabled on Windows by using the `WindowsCPUAndMemoryAffinity` feature gate and it requires support in the container runtime. Once the feature gate is enabled, follow the steps below to configure the [CPU manager policy](#configuration). ## Configuration The CPU Manager policy is set with the `--cpu-manager-policy` kubelet flag or the `cpuManagerPolicy` field in [KubeletConfiguration](/docs/reference/config-api/kubelet-config.v1beta1/). There are two supported policies: \* [`none`](#none-policy): the default policy. \* [`static`](#static-policy): allows pods with certain resource characteristics to be granted increased CPU affinity and exclusivity on the node. The CPU manager periodically writes resource updates through the CRI in order to reconcile in-memory CPU assignments with cgroupfs. The reconcile frequency is set through a new Kubelet configuration value `--cpu-manager-reconcile-period`. If not specified, it defaults to the same duration as `--node-status-update-frequency`. The behavior of the static policy can be fine-tuned using the `--cpu-manager-policy-options` flag. The flag takes a comma-separated list of `key=value` policy options. If you disable the `CPUManagerPolicyOptions` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) then you cannot fine-tune CPU manager policies. In that case, the CPU manager operates only using its default settings. In addition to the top-level `CPUManagerPolicyOptions` feature gate, the policy options are split into two groups: alpha quality (hidden by default) and beta quality (visible by default). The groups are guarded respectively by the `CPUManagerPolicyAlphaOptions` and `CPUManagerPolicyBetaOptions` feature gates. Diverging from the Kubernetes standard, these feature gates guard groups of options, because it would have been too cumbersome to add a feature gate for each individual option. ## Changing the CPU Manager Policy Since the CPU manager policy can only be applied when kubelet spawns new pods, simply changing from "none" to "static" won't apply to existing pods. So in order to properly change the CPU manager policy on a node, perform the following steps: 1. [Drain](/docs/tasks/administer-cluster/safely-drain-node) the node. 2. Stop kubelet. 3. Remove the old CPU manager state file. The path to this file is `/var/lib/kubelet/cpu\_manager\_state` by default. This clears the state maintained by the CPUManager so that the cpu-sets set up by the new policy won’t conflict with it. 4. Edit the kubelet configuration to change the CPU manager policy to the desired value. 5. Start kubelet. Repeat this process for every node that needs its CPU manager policy changed. Skipping this process will result
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
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|
so that the cpu-sets set up by the new policy won’t conflict with it. 4. Edit the kubelet configuration to change the CPU manager policy to the desired value. 5. Start kubelet. Repeat this process for every node that needs its CPU manager policy changed. Skipping this process will result in kubelet crashlooping with the following error: ``` could not restore state from checkpoint: configured policy "static" differs from state checkpoint policy "none", please drain this node and delete the CPU manager checkpoint file "/var/lib/kubelet/cpu\_manager\_state" before restarting Kubelet ``` {{< note >}} if the set of online CPUs changes on the node, the node must be drained and CPU manager manually reset by deleting the state file `cpu\_manager\_state` in the kubelet root directory. {{< /note >}} ### `none` policy configuration This policy has no extra configuration items. ### `static` policy configuration This policy manages a shared pool of CPUs that initially contains all CPUs in the node. The amount of exclusively allocatable CPUs is equal to the total number of CPUs in the node minus any CPU reservations by the kubelet `--kube-reserved` or `--system-reserved` options. From 1.17, the CPU reservation list can be specified explicitly by kubelet `--reserved-cpus` option. The explicit CPU list specified by `--reserved-cpus` takes precedence over the CPU reservation specified by `--kube-reserved` and `--system-reserved`. CPUs reserved by these options are taken, in integer quantity, from the initial shared pool in ascending order by physical core ID. This shared pool is the set of CPUs on which any containers in `BestEffort` and `Burstable` pods run. Containers in `Guaranteed` pods with fractional CPU `requests` also run on CPUs in the shared pool. Only containers that are both part of a `Guaranteed` pod and have integer CPU `requests` are assigned exclusive CPUs. {{< note >}} The kubelet requires a CPU reservation greater than zero be made using either `--kube-reserved` and/or `--system-reserved` or `--reserved-cpus` when the static policy is enabled. This is because zero CPU reservation would allow the shared pool to become empty. {{< /note >}} ### Static policy options {#cpu-policy-static--options} You can toggle groups of options on and off based upon their maturity level using the following feature gates: \* `CPUManagerPolicyBetaOptions` default enabled. Disable to hide beta-level options. \* `CPUManagerPolicyAlphaOptions` default disabled. Enable to show alpha-level options. You will still have to enable each option using the `CPUManagerPolicyOptions` kubelet option. The following policy options exist for the static `CPUManager` policy: \* `full-pcpus-only` (GA, visible by default) (1.33 or higher) \* `distribute-cpus-across-numa` (beta, visible by default) (1.33 or higher) \* `align-by-socket` (alpha, hidden by default) (1.25 or higher) \* `distribute-cpus-across-cores` (alpha, hidden by default) (1.31 or higher) \* `strict-cpu-reservation` (GA, visible by default) (1.35 or higher) \* `prefer-align-cpus-by-uncorecache` (beta, visible by default) (1.34 or higher) The `full-pcpus-only` option can be enabled by adding `full-pcpus-only=true` to the CPUManager policy options. Likewise, the `distribute-cpus-across-numa` option can be enabled by adding `distribute-cpus-across-numa=true` to the CPUManager policy options. When both are set, they are "additive" in the sense that CPUs will be distributed across NUMA nodes in chunks of full-pcpus rather than individual cores. The `align-by-socket` policy option can be enabled by adding `align-by-socket=true` to the `CPUManager` policy options. It is also additive to the `full-pcpus-only` and `distribute-cpus-across-numa` policy options. The `distribute-cpus-across-cores` option can be enabled by adding `distribute-cpus-across-cores=true` to the `CPUManager` policy options. It cannot be used with `full-pcpus-only` or `distribute-cpus-across-numa` policy options together at this moment. The `strict-cpu-reservation` option can be enabled by adding `strict-cpu-reservation=true` to the CPUManager policy options followed by removing the `/var/lib/kubelet/cpu\_manager\_state` file and restart kubelet. The `prefer-align-cpus-by-uncorecache` option can be enabled by adding the `prefer-align-cpus-by-uncorecache` to the `CPUManager`
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
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] | 0.121815
|
It cannot be used with `full-pcpus-only` or `distribute-cpus-across-numa` policy options together at this moment. The `strict-cpu-reservation` option can be enabled by adding `strict-cpu-reservation=true` to the CPUManager policy options followed by removing the `/var/lib/kubelet/cpu\_manager\_state` file and restart kubelet. The `prefer-align-cpus-by-uncorecache` option can be enabled by adding the `prefer-align-cpus-by-uncorecache` to the `CPUManager` policy options. If incompatible options are used, the kubelet will fail to start with the error explained in the logs. For mode detail about the behavior of the individual options you can configure, please refer to the [Node ResourceManagers](/docs/concepts/policy/node-resource-managers) documentation.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/cpu-management-policies.md
|
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] | 0.129683
|
{{< feature-state state="beta" for\_k8s\_version="v1.11" >}} Since cloud providers develop and release at a different pace compared to the Kubernetes project, abstracting the provider-specific code to the `{{< glossary\_tooltip text="cloud-controller-manager" term\_id="cloud-controller-manager" >}}` binary allows cloud vendors to evolve independently from the core Kubernetes code. The `cloud-controller-manager` can be linked to any cloud provider that satisfies [cloudprovider.Interface](https://github.com/kubernetes/cloud-provider/blob/master/cloud.go). For backwards compatibility, the [cloud-controller-manager](https://github.com/kubernetes/kubernetes/tree/master/cmd/cloud-controller-manager) provided in the core Kubernetes project uses the same cloud libraries as `kube-controller-manager`. Cloud providers already supported in Kubernetes core are expected to use the in-tree cloud-controller-manager to transition out of Kubernetes core. ## Administration ### Requirements Every cloud has their own set of requirements for running their own cloud provider integration, it should not be too different from the requirements when running `kube-controller-manager`. As a general rule of thumb you'll need: \* cloud authentication/authorization: your cloud may require a token or IAM rules to allow access to their APIs \* kubernetes authentication/authorization: cloud-controller-manager may need RBAC rules set to speak to the kubernetes apiserver \* high availability: like kube-controller-manager, you may want a high available setup for cloud controller manager using leader election (on by default). ### Running cloud-controller-manager Successfully running cloud-controller-manager requires some changes to your cluster configuration. \* `kubelet`, `kube-apiserver`, and `kube-controller-manager` must be set according to the user's usage of external CCM. If the user has an external CCM (not the internal cloud controller loops in the Kubernetes Controller Manager), then `--cloud-provider=external` must be specified. Otherwise, it should not be specified. Keep in mind that setting up your cluster to use cloud controller manager will change your cluster behaviour in a few ways: \* Components that specify `--cloud-provider=external` will add a taint `node.cloudprovider.kubernetes.io/uninitialized` with an effect `NoSchedule` during initialization. This marks the node as needing a second initialization from an external controller before it can be scheduled work. Note that in the event that cloud controller manager is not available, new nodes in the cluster will be left unschedulable. The taint is important since the scheduler may require cloud specific information about nodes such as their region or type (high cpu, gpu, high memory, spot instance, etc). \* cloud information about nodes in the cluster will no longer be retrieved using local metadata, but instead all API calls to retrieve node information will go through cloud controller manager. This may mean you can restrict access to your cloud API on the kubelets for better security. For larger clusters you may want to consider if cloud controller manager will hit rate limits since it is now responsible for almost all API calls to your cloud from within the cluster. The cloud controller manager can implement: \* Node controller - responsible for updating kubernetes nodes using cloud APIs and deleting kubernetes nodes that were deleted on your cloud. \* Service controller - responsible for loadbalancers on your cloud against services of type LoadBalancer. \* Route controller - responsible for setting up network routes on your cloud \* any other features you would like to implement if you are running an out-of-tree provider. ## Examples If you are using a cloud that is currently supported in Kubernetes core and would like to adopt cloud controller manager, see the [cloud controller manager in kubernetes core](https://github.com/kubernetes/kubernetes/tree/master/cmd/cloud-controller-manager). For cloud controller managers not in Kubernetes core, you can find the respective projects in repositories maintained by cloud vendors or by SIGs. For providers already in Kubernetes core, you can run the in-tree cloud controller manager as a DaemonSet in your cluster, use the following as a guideline: {{% code\_sample file="admin/cloud/ccm-example.yaml" %}} ## Limitations Running cloud controller manager comes with a few possible limitations.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/running-cloud-controller.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/running-cloud-controller.md
|
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] | 0.058626
|
repositories maintained by cloud vendors or by SIGs. For providers already in Kubernetes core, you can run the in-tree cloud controller manager as a DaemonSet in your cluster, use the following as a guideline: {{% code\_sample file="admin/cloud/ccm-example.yaml" %}} ## Limitations Running cloud controller manager comes with a few possible limitations. Although these limitations are being addressed in upcoming releases, it's important that you are aware of these limitations for production workloads. ### Support for Volumes Cloud controller manager does not implement any of the volume controllers found in `kube-controller-manager` as the volume integrations also require coordination with kubelets. As we evolve CSI (container storage interface) and add stronger support for flex volume plugins, necessary support will be added to cloud controller manager so that clouds can fully integrate with volumes. Learn more about out-of-tree CSI volume plugins [here](https://github.com/kubernetes/features/issues/178). ### Scalability The cloud-controller-manager queries your cloud provider's APIs to retrieve information for all nodes. For very large clusters, consider possible bottlenecks such as resource requirements and API rate limiting. ### Chicken and Egg The goal of the cloud controller manager project is to decouple development of cloud features from the core Kubernetes project. Unfortunately, many aspects of the Kubernetes project has assumptions that cloud provider features are tightly integrated into the project. As a result, adopting this new architecture can create several situations where a request is being made for information from a cloud provider, but the cloud controller manager may not be able to return that information without the original request being complete. A good example of this is the TLS bootstrapping feature in the Kubelet. TLS bootstrapping assumes that the Kubelet has the ability to ask the cloud provider (or a local metadata service) for all its address types (private, public, etc) but cloud controller manager cannot set a node's address types without being initialized in the first place which requires that the kubelet has TLS certificates to communicate with the apiserver. As this initiative evolves, changes will be made to address these issues in upcoming releases. ## {{% heading "whatsnext" %}} To build and develop your own cloud controller manager, read [Developing Cloud Controller Manager](/docs/tasks/administer-cluster/developing-cloud-controller-manager/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/running-cloud-controller.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/running-cloud-controller.md
|
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This page shows how to access clusters using the Kubernetes API. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Accessing the Kubernetes API ### Accessing for the first time with kubectl When accessing the Kubernetes API for the first time, use the Kubernetes command-line tool, `kubectl`. To access a cluster, you need to know the location of the cluster and have credentials to access it. Typically, this is automatically set-up when you work through a [Getting started guide](/docs/setup/), or someone else set up the cluster and provided you with credentials and a location. Check the location and credentials that kubectl knows about with this command: ```shell kubectl config view ``` Many of the [examples](https://github.com/kubernetes/examples/tree/master/) provide an introduction to using kubectl. Complete documentation is found in the [kubectl manual](/docs/reference/kubectl/). ### Directly accessing the REST API kubectl handles locating and authenticating to the API server. If you want to directly access the REST API with an http client like `curl` or `wget`, or a browser, there are multiple ways you can locate and authenticate against the API server: 1. Run kubectl in proxy mode (recommended). This method is recommended, since it uses the stored API server location and verifies the identity of the API server using a self-signed certificate. No man-in-the-middle (MITM) attack is possible using this method. 1. Alternatively, you can provide the location and credentials directly to the http client. This works with client code that is confused by proxies. To protect against man in the middle attacks, you'll need to import a root cert into your browser. Using the Go or Python client libraries provides accessing kubectl in proxy mode. #### Using kubectl proxy The following command runs kubectl in a mode where it acts as a reverse proxy. It handles locating the API server and authenticating. Run it like this: ```shell kubectl proxy --port=8080 & ``` See [kubectl proxy](/docs/reference/generated/kubectl/kubectl-commands/#proxy) for more details. Then you can explore the API with curl, wget, or a browser, like so: ```shell curl http://localhost:8080/api/ ``` The output is similar to this: ```json { "versions": [ "v1" ], "serverAddressByClientCIDRs": [ { "clientCIDR": "0.0.0.0/0", "serverAddress": "10.0.1.149:443" } ] } ``` #### Without kubectl proxy It is possible to avoid using kubectl proxy by passing an authentication token directly to the API server, like this: Using `grep/cut` approach: ```shell # Check all possible clusters, as your .KUBECONFIG may have multiple contexts: kubectl config view -o jsonpath='{"Cluster name\tServer\n"}{range .clusters[\*]}{.name}{"\t"}{.cluster.server}{"\n"}{end}' # Select name of cluster you want to interact with from above output: export CLUSTER\_NAME="some\_server\_name" # Point to the API server referring the cluster name APISERVER=$(kubectl config view -o jsonpath="{.clusters[?(@.name==\"$CLUSTER\_NAME\")].cluster.server}") # Create a secret to hold a token for the default service account kubectl apply -f - </dev/null; do echo "waiting for token..." >&2 sleep 1 done # Get the token value TOKEN=$(kubectl get secret default-token -o jsonpath='{.data.token}' | base64 --decode) # Explore the API with TOKEN curl -X GET $APISERVER/api --header "Authorization: Bearer $TOKEN" --insecure ``` The output is similar to this: ```json { "kind": "APIVersions", "versions": [ "v1" ], "serverAddressByClientCIDRs": [ { "clientCIDR": "0.0.0.0/0", "serverAddress": "10.0.1.149:443" } ] } ``` The above example uses the `--insecure` flag. This leaves it subject to MITM attacks. When kubectl accesses the cluster it uses a stored root certificate and client certificates to access the server. (These are installed in the `~/.kube` directory). Since cluster certificates are typically self-signed, it may take special configuration to get your http client to use root certificate. On some clusters, the API server does not require authentication; it may serve on localhost, or be protected by a firewall. There
| null |
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https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/access-cluster-api.md
|
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server. (These are installed in the `~/.kube` directory). Since cluster certificates are typically self-signed, it may take special configuration to get your http client to use root certificate. On some clusters, the API server does not require authentication; it may serve on localhost, or be protected by a firewall. There is not a standard for this. [Controlling Access to the Kubernetes API](/docs/concepts/security/controlling-access) describes how you can configure this as a cluster administrator. ### Programmatic access to the API Kubernetes officially supports client libraries for [Go](#go-client), [Python](#python-client), [Java](#java-client), [dotnet](#dotnet-client), [JavaScript](#javascript-client), and [Haskell](#haskell-client). There are other client libraries that are provided and maintained by their authors, not the Kubernetes team. See [client libraries](/docs/reference/using-api/client-libraries/) for accessing the API from other languages and how they authenticate. #### Go client \* To get the library, run the following command: `go get k8s.io/client-go@kubernetes-` See [https://github.com/kubernetes/client-go/releases](https://github.com/kubernetes/client-go/releases) to see which versions are supported. \* Write an application atop of the client-go clients. {{< note >}} `client-go` defines its own API objects, so if needed, import API definitions from client-go rather than from the main repository. For example, `import "k8s.io/client-go/kubernetes"` is correct. {{< /note >}} The Go client can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://git.k8s.io/client-go/examples/out-of-cluster-client-configuration/main.go): ```golang package main import ( "context" "fmt" "k8s.io/apimachinery/pkg/apis/meta/v1" "k8s.io/client-go/kubernetes" "k8s.io/client-go/tools/clientcmd" ) func main() { // uses the current context in kubeconfig // path-to-kubeconfig -- for example, /root/.kube/config config, \_ := clientcmd.BuildConfigFromFlags("", "") // creates the clientset clientset, \_ := kubernetes.NewForConfig(config) // access the API to list pods pods, \_ := clientset.CoreV1().Pods("").List(context.TODO(), v1.ListOptions{}) fmt.Printf("There are %d pods in the cluster\n", len(pods.Items)) } ``` If the application is deployed as a Pod in the cluster, see [Accessing the API from within a Pod](/docs/tasks/access-application-cluster/access-cluster/#accessing-the-api-from-a-pod). #### Python client To use [Python client](https://github.com/kubernetes-client/python), run the following command: `pip install kubernetes`. See [Python Client Library page](https://github.com/kubernetes-client/python) for more installation options. The Python client can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://github.com/kubernetes-client/python/blob/master/examples/out\_of\_cluster\_config.py): ```python from kubernetes import client, config config.load\_kube\_config() v1=client.CoreV1Api() print("Listing pods with their IPs:") ret = v1.list\_pod\_for\_all\_namespaces(watch=False) for i in ret.items: print("%s\t%s\t%s" % (i.status.pod\_ip, i.metadata.namespace, i.metadata.name)) ``` #### Java client To install the [Java Client](https://github.com/kubernetes-client/java), run: ```shell # Clone java library git clone --recursive https://github.com/kubernetes-client/java # Installing project artifacts, POM etc: cd java mvn install ``` See [https://github.com/kubernetes-client/java/releases](https://github.com/kubernetes-client/java/releases) to see which versions are supported. The Java client can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://github.com/kubernetes-client/java/blob/master/examples/examples-release-15/src/main/java/io/kubernetes/client/examples/KubeConfigFileClientExample.java): ```java package io.kubernetes.client.examples; import io.kubernetes.client.ApiClient; import io.kubernetes.client.ApiException; import io.kubernetes.client.Configuration; import io.kubernetes.client.apis.CoreV1Api; import io.kubernetes.client.models.V1Pod; import io.kubernetes.client.models.V1PodList; import io.kubernetes.client.util.ClientBuilder; import io.kubernetes.client.util.KubeConfig; import java.io.FileReader; import java.io.IOException; /\*\* \* A simple example of how to use the Java API from an application outside a kubernetes cluster \* \* Easiest way to run this: mvn exec:java \* -Dexec.mainClass="io.kubernetes.client.examples.KubeConfigFileClientExample" \* \*/ public class KubeConfigFileClientExample { public static void main(String[] args) throws IOException, ApiException { // file path to your KubeConfig String kubeConfigPath = "~/.kube/config"; // loading the out-of-cluster config, a kubeconfig from file-system ApiClient client = ClientBuilder.kubeconfig(KubeConfig.loadKubeConfig(new FileReader(kubeConfigPath))).build(); // set the global default api-client to the in-cluster one from above Configuration.setDefaultApiClient(client); // the CoreV1Api loads default api-client from global configuration. CoreV1Api api = new CoreV1Api(); // invokes the CoreV1Api client V1PodList list = api.listPodForAllNamespaces(null, null, null, null, null, null, null, null, null); System.out.println("Listing all pods: "); for (V1Pod item : list.getItems()) { System.out.println(item.getMetadata().getName()); } } } ``` #### dotnet client To use [dotnet client](https://github.com/kubernetes-client/csharp), run the following command: `dotnet add package KubernetesClient --version 1.6.1`. See [dotnet Client Library
| null |
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|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/access-cluster-api.md
|
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] | 0.149777
|
CoreV1Api client V1PodList list = api.listPodForAllNamespaces(null, null, null, null, null, null, null, null, null); System.out.println("Listing all pods: "); for (V1Pod item : list.getItems()) { System.out.println(item.getMetadata().getName()); } } } ``` #### dotnet client To use [dotnet client](https://github.com/kubernetes-client/csharp), run the following command: `dotnet add package KubernetesClient --version 1.6.1`. See [dotnet Client Library page](https://github.com/kubernetes-client/csharp) for more installation options. See [https://github.com/kubernetes-client/csharp/releases](https://github.com/kubernetes-client/csharp/releases) to see which versions are supported. The dotnet client can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://github.com/kubernetes-client/csharp/blob/master/examples/simple/PodList.cs): ```csharp using System; using k8s; namespace simple { internal class PodList { private static void Main(string[] args) { var config = KubernetesClientConfiguration.BuildDefaultConfig(); IKubernetes client = new Kubernetes(config); Console.WriteLine("Starting Request!"); var list = client.ListNamespacedPod("default"); foreach (var item in list.Items) { Console.WriteLine(item.Metadata.Name); } if (list.Items.Count == 0) { Console.WriteLine("Empty!"); } } } } ``` #### JavaScript client To install [JavaScript client](https://github.com/kubernetes-client/javascript), run the following command: `npm install @kubernetes/client-node`. See [https://github.com/kubernetes-client/javascript/releases](https://github.com/kubernetes-client/javascript/releases) to see which versions are supported. The JavaScript client can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://github.com/kubernetes-client/javascript/blob/master/examples/example.js): ```javascript const k8s = require('@kubernetes/client-node'); const kc = new k8s.KubeConfig(); kc.loadFromDefault(); const k8sApi = kc.makeApiClient(k8s.CoreV1Api); k8sApi.listNamespacedPod({ namespace: 'default' }).then((res) => { console.log(res); }); ``` #### Haskell client See [https://github.com/kubernetes-client/haskell/releases](https://github.com/kubernetes-client/haskell/releases) to see which versions are supported. The [Haskell client](https://github.com/kubernetes-client/haskell) can use the same [kubeconfig file](/docs/concepts/configuration/organize-cluster-access-kubeconfig/) as the kubectl CLI does to locate and authenticate to the API server. See this [example](https://github.com/kubernetes-client/haskell/blob/master/kubernetes-client/example/App.hs): ```haskell exampleWithKubeConfig :: IO () exampleWithKubeConfig = do oidcCache <- atomically $ newTVar $ Map.fromList [] (mgr, kcfg) <- mkKubeClientConfig oidcCache $ KubeConfigFile "/path/to/kubeconfig" dispatchMime mgr kcfg (CoreV1.listPodForAllNamespaces (Accept MimeJSON)) >>= print ``` ## {{% heading "whatsnext" %}} \* [Accessing the Kubernetes API from a Pod](/docs/tasks/run-application/access-api-from-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/access-cluster-api.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/access-cluster-api.md
|
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] | 0.114725
|
To avoid CNI plugin-related errors, verify that you are using or upgrading to a container runtime that has been tested to work correctly with your version of Kubernetes. ## About the "Incompatible CNI versions" and "Failed to destroy network for sandbox" errors Service issues exist for pod CNI network setup and tear down in containerd v1.6.0-v1.6.3 when the CNI plugins have not been upgraded and/or the CNI config version is not declared in the CNI config files. The containerd team reports, "these issues are resolved in containerd v1.6.4." With containerd v1.6.0-v1.6.3, if you do not upgrade the CNI plugins and/or declare the CNI config version, you might encounter the following "Incompatible CNI versions" or "Failed to destroy network for sandbox" error conditions. ### Incompatible CNI versions error If the version of your CNI plugin does not correctly match the plugin version in the config because the config version is later than the plugin version, the containerd log will likely show an error message on startup of a pod similar to: ``` incompatible CNI versions; config is \"1.0.0\", plugin supports [\"0.1.0\" \"0.2.0\" \"0.3.0\" \"0.3.1\" \"0.4.0\"]" ``` To fix this issue, [update your CNI plugins and CNI config files](#updating-your-cni-plugins-and-cni-config-files). ### Failed to destroy network for sandbox error If the version of the plugin is missing in the CNI plugin config, the pod may run. However, stopping the pod generates an error similar to: ``` ERROR[2022-04-26T00:43:24.518165483Z] StopPodSandbox for "b" failed error="failed to destroy network for sandbox \"bbc85f891eaf060c5a879e27bba9b6b06450210161dfdecfbb2732959fb6500a\": invalid version \"\": the version is empty" ``` This error leaves the pod in the not-ready state with a network namespace still attached. To recover from this problem, [edit the CNI config file](#updating-your-cni-plugins-and-cni-config-files) to add the missing version information. The next attempt to stop the pod should be successful. ### Updating your CNI plugins and CNI config files If you're using containerd v1.6.0-v1.6.3 and encountered "Incompatible CNI versions" or "Failed to destroy network for sandbox" errors, consider updating your CNI plugins and editing the CNI config files. Here's an overview of the typical steps for each node: 1. [Safely drain and cordon the node](/docs/tasks/administer-cluster/safely-drain-node/). 1. After stopping your container runtime and kubelet services, perform the following upgrade operations: - If you're running CNI plugins, upgrade them to the latest version. - If you're using non-CNI plugins, replace them with CNI plugins. Use the latest version of the plugins. - Update the plugin configuration file to specify or match a version of the CNI specification that the plugin supports, as shown in the following ["An example containerd configuration file"](#an-example-containerd-configuration-file) section. - For `containerd`, ensure that you have installed the latest version (v1.0.0 or later) of the CNI loopback plugin. - Upgrade node components (for example, the kubelet) to Kubernetes v1.24 - Upgrade to or install the most current version of the container runtime. 1. Bring the node back into your cluster by restarting your container runtime and kubelet. Uncordon the node (`kubectl uncordon `). ## An example containerd configuration file The following example shows a configuration for `containerd` runtime v1.6.x, which supports a recent version of the CNI specification (v1.0.0). Please see the documentation from your plugin and networking provider for further instructions on configuring your system. On Kubernetes, containerd runtime adds a loopback interface, `lo`, to pods as a default behavior. The containerd runtime configures the loopback interface via a CNI plugin, `loopback`. The `loopback` plugin is distributed as part of the `containerd` release packages that have the `cni` designation. `containerd` v1.6.0 and later includes a CNI v1.0.0-compatible loopback plugin as well as other default CNI plugins. The configuration for the loopback plugin is done internally
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/troubleshooting-cni-plugin-related-errors.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/troubleshooting-cni-plugin-related-errors.md
|
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] | 0.058795
|
loopback interface via a CNI plugin, `loopback`. The `loopback` plugin is distributed as part of the `containerd` release packages that have the `cni` designation. `containerd` v1.6.0 and later includes a CNI v1.0.0-compatible loopback plugin as well as other default CNI plugins. The configuration for the loopback plugin is done internally by containerd, and is set to use CNI v1.0.0. This also means that the version of the `loopback` plugin must be v1.0.0 or later when this newer version `containerd` is started. The following bash command generates an example CNI config. Here, the 1.0.0 value for the config version is assigned to the `cniVersion` field for use when `containerd` invokes the CNI bridge plugin. ```bash cat << EOF | tee /etc/cni/net.d/10-containerd-net.conflist { "cniVersion": "1.0.0", "name": "containerd-net", "plugins": [ { "type": "bridge", "bridge": "cni0", "isGateway": true, "ipMasq": true, "promiscMode": true, "ipam": { "type": "host-local", "ranges": [ [{ "subnet": "10.88.0.0/16" }], [{ "subnet": "2001:db8:4860::/64" }] ], "routes": [ { "dst": "0.0.0.0/0" }, { "dst": "::/0" } ] } }, { "type": "portmap", "capabilities": {"portMappings": true}, "externalSetMarkChain": "KUBE-MARK-MASQ" } ] } EOF ``` Update the IP address ranges in the preceding example with ones that are based on your use case and network addressing plan.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/troubleshooting-cni-plugin-related-errors.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/troubleshooting-cni-plugin-related-errors.md
|
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] | 0.030673
|
This task outlines the steps needed to update your container runtime to containerd from Docker. It is applicable for cluster operators running Kubernetes 1.23 or earlier. This also covers an example scenario for migrating from dockershim to containerd. Alternative container runtimes can be picked from this [page](/docs/setup/production-environment/container-runtimes/). ## {{% heading "prerequisites" %}} {{% thirdparty-content %}} Install containerd. For more information see [containerd's installation documentation](https://containerd.io/docs/getting-started/) and for specific prerequisite follow [the containerd guide](/docs/setup/production-environment/container-runtimes/#containerd). ## Drain the node ```shell kubectl drain --ignore-daemonsets ``` Replace `` with the name of your node you are draining. ## Stop the Docker daemon ```shell systemctl stop kubelet systemctl disable docker.service --now ``` ## Install Containerd Follow the [guide](/docs/setup/production-environment/container-runtimes/#containerd) for detailed steps to install containerd. {{< tabs name="tab-cri-containerd-installation" >}} {{% tab name="Linux" %}} 1. Install the `containerd.io` package from the official Docker repositories. Instructions for setting up the Docker repository for your respective Linux distribution and installing the `containerd.io` package can be found at [Getting started with containerd](https://github.com/containerd/containerd/blob/main/docs/getting-started.md). 1. Configure containerd: ```shell sudo mkdir -p /etc/containerd containerd config default | sudo tee /etc/containerd/config.toml ``` 1. Restart containerd: ```shell sudo systemctl restart containerd ``` {{% /tab %}} {{% tab name="Windows (PowerShell)" %}} Start a Powershell session, set `$Version` to the desired version (ex: `$Version="1.4.3"`), and then run the following commands: 1. Download containerd: ```powershell curl.exe -L https://github.com/containerd/containerd/releases/download/v$Version/containerd-$Version-windows-amd64.tar.gz -o containerd-windows-amd64.tar.gz tar.exe xvf .\containerd-windows-amd64.tar.gz ``` 2. Extract and configure: ```powershell Copy-Item -Path ".\bin\" -Destination "$Env:ProgramFiles\containerd" -Recurse -Force cd $Env:ProgramFiles\containerd\ .\containerd.exe config default | Out-File config.toml -Encoding ascii # Review the configuration. Depending on setup you may want to adjust: # - the sandbox\_image (Kubernetes pause image) # - cni bin\_dir and conf\_dir locations Get-Content config.toml # (Optional - but highly recommended) Exclude containerd from Windows Defender Scans Add-MpPreference -ExclusionProcess "$Env:ProgramFiles\containerd\containerd.exe" ``` 3. Start containerd: ```powershell .\containerd.exe --register-service Start-Service containerd ``` {{% /tab %}} {{< /tabs >}} ## Configure the kubelet to use containerd as its container runtime Edit the file `/var/lib/kubelet/kubeadm-flags.env` and add the containerd runtime to the flags; `--container-runtime-endpoint=unix:///run/containerd/containerd.sock`. Users using kubeadm should be aware that the kubeadm tool stores the host's CRI socket in the `/var/lib/kubelet/instance-config.yaml` file on each node. You can create this `/var/lib/kubelet/instance-config.yaml` file on the node. The `/var/lib/kubelet/instance-config.yaml` file allows setting the `containerRuntimeEndpoint` parameter. You can set this parameter's value to the path of your chosen CRI socket (for example `unix:///run/containerd/containerd.sock`). ## Restart the kubelet ```shell systemctl start kubelet ``` ## Verify that the node is healthy Run `kubectl get nodes -o wide` and containerd appears as the runtime for the node we just changed. ## Remove Docker Engine {{% thirdparty-content %}} If the node appears healthy, remove Docker. {{< tabs name="tab-remove-docker-engine" >}} {{% tab name="CentOS" %}} ```shell sudo yum remove docker-ce docker-ce-cli ``` {{% /tab %}} {{% tab name="Debian" %}} ```shell sudo apt-get purge docker-ce docker-ce-cli ``` {{% /tab %}} {{% tab name="Fedora" %}} ```shell sudo dnf remove docker-ce docker-ce-cli ``` {{% /tab %}} {{% tab name="Ubuntu" %}} ```shell sudo apt-get purge docker-ce docker-ce-cli ``` {{% /tab %}} {{< /tabs >}} The preceding commands don't remove images, containers, volumes, or customized configuration files on your host. To delete them, follow Docker's instructions to [Uninstall Docker Engine](https://docs.docker.com/engine/install/ubuntu/#uninstall-docker-engine). {{< caution >}} Docker's instructions for uninstalling Docker Engine create a risk of deleting containerd. Be careful when executing commands. {{< /caution >}} ## Uncordon the node ```shell kubectl uncordon ``` Replace `` with the name of your node you previously drained.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/change-runtime-containerd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/change-runtime-containerd.md
|
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] | 0.035019
|
kubectl uncordon ``` Replace `` with the name of your node you previously drained.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/change-runtime-containerd.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/change-runtime-containerd.md
|
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|
{{% thirdparty-content %}} Kubernetes' support for direct integration with Docker Engine is deprecated and has been removed. Most apps do not have a direct dependency on runtime hosting containers. However, there are still a lot of telemetry and monitoring agents that have a dependency on Docker to collect containers metadata, logs, and metrics. This document aggregates information on how to detect these dependencies as well as links on how to migrate these agents to use generic tools or alternative runtimes. ## Telemetry and security agents Within a Kubernetes cluster there are a few different ways to run telemetry or security agents. Some agents have a direct dependency on Docker Engine when they run as DaemonSets or directly on nodes. ### Why do some telemetry agents communicate with Docker Engine? Historically, Kubernetes was written to work specifically with Docker Engine. Kubernetes took care of networking and scheduling, relying on Docker Engine for launching and running containers (within Pods) on a node. Some information that is relevant to telemetry, such as a pod name, is only available from Kubernetes components. Other data, such as container metrics, is not the responsibility of the container runtime. Early telemetry agents needed to query the container runtime \*and\* Kubernetes to report an accurate picture. Over time, Kubernetes gained the ability to support multiple runtimes, and now supports any runtime that is compatible with the [container runtime interface](/docs/concepts/architecture/cri/). Some telemetry agents rely specifically on Docker Engine tooling. For example, an agent might run a command such as [`docker ps`](https://docs.docker.com/engine/reference/commandline/ps/) or [`docker top`](https://docs.docker.com/engine/reference/commandline/top/) to list containers and processes or [`docker logs`](https://docs.docker.com/engine/reference/commandline/logs/) to receive streamed logs. If nodes in your existing cluster use Docker Engine, and you switch to a different container runtime, these commands will not work any longer. ### Identify DaemonSets that depend on Docker Engine {#identify-docker-dependency} If a pod wants to make calls to the `dockerd` running on the node, the pod must either: - mount the filesystem containing the Docker daemon's privileged socket, as a {{< glossary\_tooltip text="volume" term\_id="volume" >}}; or - mount the specific path of the Docker daemon's privileged socket directly, also as a volume. For example: on COS images, Docker exposes its Unix domain socket at `/var/run/docker.sock` This means that the pod spec will include a `hostPath` volume mount of `/var/run/docker.sock`. Here's a sample shell script to find Pods that have a mount directly mapping the Docker socket. This script outputs the namespace and name of the pod. You can remove the `grep '/var/run/docker.sock'` to review other mounts. ```bash kubectl get pods --all-namespaces \ -o=jsonpath='{range .items[\*]}{"\n"}{.metadata.namespace}{":\t"}{.metadata.name}{":\t"}{range .spec.volumes[\*]}{.hostPath.path}{", "}{end}{end}' \ | sort \ | grep '/var/run/docker.sock' ``` {{< note >}} There are alternative ways for a pod to access Docker on the host. For instance, the parent directory `/var/run` may be mounted instead of the full path (like in [this example](https://gist.github.com/itaysk/7bc3e56d69c4d72a549286d98fd557dd)). The script above only detects the most common uses. {{< /note >}} ### Detecting Docker dependency from node agents If your cluster nodes are customized and install additional security and telemetry agents on the node, check with the agent vendor to verify whether it has any dependency on Docker. ### Telemetry and security agent vendors This section is intended to aggregate information about various telemetry and security agents that may have a dependency on container runtimes. We keep the work in progress version of migration instructions for various telemetry and security agent vendors in [Google doc](https://docs.google.com/document/d/1ZFi4uKit63ga5sxEiZblfb-c23lFhvy6RXVPikS8wf0/edit#). Please contact the vendor to get up to date instructions for migrating from dockershim. ## Migration from dockershim ### [Aqua](https://www.aquasec.com) No changes are needed: everything should work seamlessly on the runtime switch. ### [Datadog](https://www.datadoghq.com/product/) How to
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents.md
|
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] | 0.198305
|
version of migration instructions for various telemetry and security agent vendors in [Google doc](https://docs.google.com/document/d/1ZFi4uKit63ga5sxEiZblfb-c23lFhvy6RXVPikS8wf0/edit#). Please contact the vendor to get up to date instructions for migrating from dockershim. ## Migration from dockershim ### [Aqua](https://www.aquasec.com) No changes are needed: everything should work seamlessly on the runtime switch. ### [Datadog](https://www.datadoghq.com/product/) How to migrate: [Docker deprecation in Kubernetes](https://docs.datadoghq.com/agent/guide/docker-deprecation/) The pod that accesses Docker Engine may have a name containing any of: - `datadog-agent` - `datadog` - `dd-agent` ### [Dynatrace](https://www.dynatrace.com/) How to migrate: [Migrating from Docker-only to generic container metrics in Dynatrace](https://community.dynatrace.com/t5/Best-practices/Migrating-from-Docker-only-to-generic-container-metrics-in/m-p/167030#M49) Containerd support announcement: [Get automated full-stack visibility into containerd-based Kubernetes environments](https://www.dynatrace.com/news/blog/get-automated-full-stack-visibility-into-containerd-based-kubernetes-environments/) CRI-O support announcement: [Get automated full-stack visibility into your CRI-O Kubernetes containers (Beta)](https://www.dynatrace.com/news/blog/get-automated-full-stack-visibility-into-your-cri-o-kubernetes-containers-beta/) The pod accessing Docker may have name containing: - `dynatrace-oneagent` ### [Falco](https://falco.org) How to migrate: [Migrate Falco from dockershim](https://falco.org/docs/getting-started/deployment/#docker-deprecation-in-kubernetes) Falco supports any CRI-compatible runtime (containerd is used in the default configuration); the documentation explains all details. The pod accessing Docker may have name containing: - `falco` ### [Prisma Cloud Compute](https://docs.paloaltonetworks.com/prisma/prisma-cloud.html) Check [documentation for Prisma Cloud](https://docs.paloaltonetworks.com/prisma/prisma-cloud/prisma-cloud-admin-compute/install/install\_kubernetes.html), under the "Install Prisma Cloud on a CRI (non-Docker) cluster" section. The pod accessing Docker may be named like: - `twistlock-defender-ds` ### [SignalFx (Splunk)](https://www.splunk.com/en\_us/investor-relations/acquisitions/signalfx.html) The SignalFx Smart Agent (deprecated) uses several different monitors for Kubernetes including `kubernetes-cluster`, `kubelet-stats/kubelet-metrics`, and `docker-container-stats`. The `kubelet-stats` monitor was previously deprecated by the vendor, in favor of `kubelet-metrics`. The `docker-container-stats` monitor is the one affected by dockershim removal. Do not use the `docker-container-stats` with container runtimes other than Docker Engine. How to migrate from dockershim-dependent agent: 1. Remove `docker-container-stats` from the list of [configured monitors](https://github.com/signalfx/signalfx-agent/blob/main/docs/monitor-config.md). Note, keeping this monitor enabled with non-dockershim runtime will result in incorrect metrics being reported when docker is installed on node and no metrics when docker is not installed. 2. [Enable and configure `kubelet-metrics`](https://github.com/signalfx/signalfx-agent/blob/main/docs/monitors/kubelet-metrics.md) monitor. {{< note >}} The set of collected metrics will change. Review your alerting rules and dashboards. {{< /note >}} The Pod accessing Docker may be named something like: - `signalfx-agent` ### Yahoo Kubectl Flame Flame does not support container runtimes other than Docker. See [https://github.com/yahoo/kubectl-flame/issues/51](https://github.com/yahoo/kubectl-flame/issues/51)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents.md
|
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] | 0.00131
|
The `dockershim` component of Kubernetes allows the use of Docker as a Kubernetes's {{< glossary\_tooltip text="container runtime" term\_id="container-runtime" >}}. Kubernetes' built-in `dockershim` component was removed in release v1.24. This page explains how your cluster could be using Docker as a container runtime, provides details on the role that `dockershim` plays when in use, and shows steps you can take to check whether any workloads could be affected by `dockershim` removal. ## Finding if your app has a dependencies on Docker {#find-docker-dependencies} If you are using Docker for building your application containers, you can still run these containers on any container runtime. This use of Docker does not count as a dependency on Docker as a container runtime. When alternative container runtime is used, executing Docker commands may either not work or yield unexpected output. This is how you can find whether you have a dependency on Docker: 1. Make sure no privileged Pods execute Docker commands (like `docker ps`), restart the Docker service (commands such as `systemctl restart docker.service`), or modify Docker-specific files such as `/etc/docker/daemon.json`. 1. Check for any private registries or image mirror settings in the Docker configuration file (like `/etc/docker/daemon.json`). Those typically need to be reconfigured for another container runtime. 1. Check that scripts and apps running on nodes outside of your Kubernetes infrastructure do not execute Docker commands. It might be: - SSH to nodes to troubleshoot; - Node startup scripts; - Monitoring and security agents installed on nodes directly. 1. Third-party tools that perform above mentioned privileged operations. See [Migrating telemetry and security agents from dockershim](/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents) for more information. 1. Make sure there are no indirect dependencies on dockershim behavior. This is an edge case and unlikely to affect your application. Some tooling may be configured to react to Docker-specific behaviors, for example, raise alert on specific metrics or search for a specific log message as part of troubleshooting instructions. If you have such tooling configured, test the behavior on a test cluster before migration. ## Dependency on Docker explained {#role-of-dockershim} A [container runtime](/docs/concepts/containers/#container-runtimes) is software that can execute the containers that make up a Kubernetes pod. Kubernetes is responsible for orchestration and scheduling of Pods; on each node, the {{< glossary\_tooltip text="kubelet" term\_id="kubelet" >}} uses the container runtime interface as an abstraction so that you can use any compatible container runtime. In its earliest releases, Kubernetes offered compatibility with one container runtime: Docker. Later in the Kubernetes project's history, cluster operators wanted to adopt additional container runtimes. The CRI was designed to allow this kind of flexibility - and the kubelet began supporting CRI. However, because Docker existed before the CRI specification was invented, the Kubernetes project created an adapter component, `dockershim`. The dockershim adapter allows the kubelet to interact with Docker as if Docker were a CRI compatible runtime. You can read about it in [Kubernetes Containerd integration goes GA](/blog/2018/05/24/kubernetes-containerd-integration-goes-ga/) blog post.  Switching to Containerd as a container runtime eliminates the middleman. All the same containers can be run by container runtimes like Containerd as before. But now, since containers schedule directly with the container runtime, they are not visible to Docker. So any Docker tooling or fancy UI you might have used before to check on these containers is no longer available. You cannot get container information using `docker ps` or `docker inspect` commands. As you cannot list containers, you cannot get logs, stop containers, or execute something inside a container using `docker exec`. {{< note >}} If you're running workloads via Kubernetes, the best way to stop a container is through the Kubernetes API rather than
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/check-if-dockershim-removal-affects-you.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/check-if-dockershim-removal-affects-you.md
|
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] | 0.073702
|
using `docker ps` or `docker inspect` commands. As you cannot list containers, you cannot get logs, stop containers, or execute something inside a container using `docker exec`. {{< note >}} If you're running workloads via Kubernetes, the best way to stop a container is through the Kubernetes API rather than directly through the container runtime (this advice applies for all container runtimes, not only Docker). {{< /note >}} You can still pull images or build them using `docker build` command. But images built or pulled by Docker would not be visible to container runtime and Kubernetes. They needed to be pushed to some registry to allow them to be used by Kubernetes. ## Known issues ### Some filesystem metrics are missing and the metrics format is different The Kubelet `/metrics/cadvisor` endpoint provides Prometheus metrics, as documented in [Metrics for Kubernetes system components](/docs/concepts/cluster-administration/system-metrics/). If you install a metrics collector that depends on that endpoint, you might see the following issues: - The metrics format on the Docker node is `k8s\_\_\_\_\_` but the format on other runtime is different. For example, on containerd node it is ``. - Some filesystem metrics are missing, as follows: ``` container\_fs\_inodes\_free container\_fs\_inodes\_total container\_fs\_io\_current container\_fs\_io\_time\_seconds\_total container\_fs\_io\_time\_weighted\_seconds\_total container\_fs\_limit\_bytes container\_fs\_read\_seconds\_total container\_fs\_reads\_merged\_total container\_fs\_sector\_reads\_total container\_fs\_sector\_writes\_total container\_fs\_usage\_bytes container\_fs\_write\_seconds\_total container\_fs\_writes\_merged\_total ``` #### Workaround You can mitigate this issue by using [cAdvisor](https://github.com/google/cadvisor) as a standalone daemonset. 1. Find the latest [cAdvisor release](https://github.com/google/cadvisor/releases) with the name pattern `vX.Y.Z-containerd-cri` (for example, `v0.42.0-containerd-cri`). 2. Follow the steps in [cAdvisor Kubernetes Daemonset](https://github.com/google/cadvisor/tree/master/deploy/kubernetes) to create the daemonset. 3. Point the installed metrics collector to use the cAdvisor `/metrics` endpoint which provides the full set of [Prometheus container metrics](https://github.com/google/cadvisor/blob/master/docs/storage/prometheus.md). Alternatives: - Use alternative third party metrics collection solution. - Collect metrics from the Kubelet summary API that is served at `/stats/summary`. ## {{% heading "whatsnext" %}} - Read [Migrating from dockershim](/docs/tasks/administer-cluster/migrating-from-dockershim/) to understand your next steps - Read the [dockershim deprecation FAQ](/blog/2020/12/02/dockershim-faq/) article for more information.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/check-if-dockershim-removal-affects-you.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/check-if-dockershim-removal-affects-you.md
|
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|
This page outlines steps to find out what [container runtime](/docs/setup/production-environment/container-runtimes/) the nodes in your cluster use. Depending on the way you run your cluster, the container runtime for the nodes may have been pre-configured or you need to configure it. If you're using a managed Kubernetes service, there might be vendor-specific ways to check what container runtime is configured for the nodes. The method described on this page should work whenever the execution of `kubectl` is allowed. ## {{% heading "prerequisites" %}} Install and configure `kubectl`. See [Install Tools](/docs/tasks/tools/#kubectl) section for details. ## Find out the container runtime used on a Node Use `kubectl` to fetch and show node information: ```shell kubectl get nodes -o wide ``` The output is similar to the following. The column `CONTAINER-RUNTIME` outputs the runtime and its version. For Docker Engine, the output is similar to this: ```none NAME STATUS VERSION CONTAINER-RUNTIME node-1 Ready v1.16.15 docker://19.3.1 node-2 Ready v1.16.15 docker://19.3.1 node-3 Ready v1.16.15 docker://19.3.1 ``` If your runtime shows as Docker Engine, you still might not be affected by the removal of dockershim in Kubernetes v1.24. [Check the runtime endpoint](#which-endpoint) to see if you use dockershim. If you don't use dockershim, you aren't affected. For containerd, the output is similar to this: ```none NAME STATUS VERSION CONTAINER-RUNTIME node-1 Ready v1.19.6 containerd://1.4.1 node-2 Ready v1.19.6 containerd://1.4.1 node-3 Ready v1.19.6 containerd://1.4.1 ``` Find out more information about container runtimes on [Container Runtimes](/docs/setup/production-environment/container-runtimes/) page. ## Find out what container runtime endpoint you use {#which-endpoint} The container runtime talks to the kubelet over a Unix socket using the [CRI protocol](/docs/concepts/architecture/cri/), which is based on the gRPC framework. The kubelet acts as a client, and the runtime acts as the server. In some cases, you might find it useful to know which socket your nodes use. For example, with the removal of dockershim in Kubernetes v1.24 and later, you might want to know whether you use Docker Engine with dockershim. {{}} If you currently use Docker Engine in your nodes with `cri-dockerd`, you aren't affected by the dockershim removal. {{}} You can check which socket you use by checking the kubelet configuration on your nodes. 1. Read the starting commands for the kubelet process: ``` tr \\0 ' ' < /proc/"$(pgrep kubelet)"/cmdline ``` If you don't have `tr` or `pgrep`, check the command line for the kubelet process manually. 1. In the output, look for the `--container-runtime` flag and the `--container-runtime-endpoint` flag. \* If your nodes use Kubernetes v1.23 and earlier and these flags aren't present or if the `--container-runtime` flag is not `remote`, you use the dockershim socket with Docker Engine. The `--container-runtime` command line argument is not available in Kubernetes v1.27 and later. \* If the `--container-runtime-endpoint` flag is present, check the socket name to find out which runtime you use. For example, `unix:///run/containerd/containerd.sock` is the containerd endpoint. If you want to change the Container Runtime on a Node from Docker Engine to containerd, you can find out more information on [migrating from Docker Engine to containerd](/docs/tasks/administer-cluster/migrating-from-dockershim/change-runtime-containerd/), or, if you want to continue using Docker Engine in Kubernetes v1.24 and later, migrate to a CRI-compatible adapter like [`cri-dockerd`](https://github.com/Mirantis/cri-dockerd).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/find-out-runtime-you-use.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/find-out-runtime-you-use.md
|
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] | 0.08262
|
This section presents information you need to know when migrating from dockershim to other container runtimes. Since the announcement of [dockershim deprecation](/blog/2020/12/08/kubernetes-1-20-release-announcement/#dockershim-deprecation) in Kubernetes 1.20, there were questions on how this will affect various workloads and Kubernetes installations. Our [Dockershim Removal FAQ](/blog/2022/02/17/dockershim-faq/) is there to help you to understand the problem better. Dockershim was removed from Kubernetes with the release of v1.24. If you use Docker Engine via dockershim as your container runtime and wish to upgrade to v1.24, it is recommended that you either migrate to another runtime or find an alternative means to obtain Docker Engine support. Check out the [container runtimes](/docs/setup/production-environment/container-runtimes/) section to know your options. The version of Kubernetes with dockershim (1.23) is out of support and the v1.24 will run out of support [soon](/releases/#release-v1-24). Make sure to [report issues](https://github.com/kubernetes/kubernetes/issues) you encountered with the migration so the issues can be fixed in a timely manner and your cluster would be ready for dockershim removal. After v1.24 running out of support, you will need to contact your Kubernetes provider for support or upgrade multiple versions at a time if there are critical issues affecting your cluster. Your cluster might have more than one kind of node, although this is not a common configuration. These tasks will help you to migrate: \* [Check whether Dockershim removal affects you](/docs/tasks/administer-cluster/migrating-from-dockershim/check-if-dockershim-removal-affects-you/) \* [Migrating telemetry and security agents from dockershim](/docs/tasks/administer-cluster/migrating-from-dockershim/migrating-telemetry-and-security-agents/) ## {{% heading "whatsnext" %}} \* Check out [container runtimes](/docs/setup/production-environment/container-runtimes/) to understand your options for an alternative. \* If you find a defect or other technical concern relating to migrating away from dockershim, you can [report an issue](https://github.com/kubernetes/kubernetes/issues/new/choose) to the Kubernetes project.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/migrating-from-dockershim/_index.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/migrating-from-dockershim/_index.md
|
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] | 0.003408
|
This page shows how to set minimum and maximum values for memory used by containers running in a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. You specify minimum and maximum memory values in a [LimitRange](/docs/reference/kubernetes-api/policy-resources/limit-range-v1/) object. If a Pod does not meet the constraints imposed by the LimitRange, it cannot be created in the namespace. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. Each node in your cluster must have at least 1 GiB of memory available for Pods. ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace constraints-mem-example ``` ## Create a LimitRange and a Pod Here's an example manifest for a LimitRange: {{% code\_sample file="admin/resource/memory-constraints.yaml" %}} Create the LimitRange: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints.yaml --namespace=constraints-mem-example ``` View detailed information about the LimitRange: ```shell kubectl get limitrange mem-min-max-demo-lr --namespace=constraints-mem-example --output=yaml ``` The output shows the minimum and maximum memory constraints as expected. But notice that even though you didn't specify default values in the configuration file for the LimitRange, they were created automatically. ``` limits: - default: memory: 1Gi defaultRequest: memory: 1Gi max: memory: 1Gi min: memory: 500Mi type: Container ``` Now whenever you define a Pod within the constraints-mem-example namespace, Kubernetes performs these steps: \* If any container in that Pod does not specify its own memory request and limit, the control plane assigns the default memory request and limit to that container. \* Verify that every container in that Pod requests at least 500 MiB of memory. \* Verify that every container in that Pod requests no more than 1024 MiB (1 GiB) of memory. Here's a manifest for a Pod that has one container. Within the Pod spec, the sole container specifies a memory request of 600 MiB and a memory limit of 800 MiB. These satisfy the minimum and maximum memory constraints imposed by the LimitRange. {{% code\_sample file="admin/resource/memory-constraints-pod.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints-pod.yaml --namespace=constraints-mem-example ``` Verify that the Pod is running and that its container is healthy: ```shell kubectl get pod constraints-mem-demo --namespace=constraints-mem-example ``` View detailed information about the Pod: ```shell kubectl get pod constraints-mem-demo --output=yaml --namespace=constraints-mem-example ``` The output shows that the container within that Pod has a memory request of 600 MiB and a memory limit of 800 MiB. These satisfy the constraints imposed by the LimitRange for this namespace: ```yaml resources: limits: memory: 800Mi requests: memory: 600Mi ``` Delete your Pod: ```shell kubectl delete pod constraints-mem-demo --namespace=constraints-mem-example ``` ## Attempt to create a Pod that exceeds the maximum memory constraint Here's a manifest for a Pod that has one container. The container specifies a memory request of 800 MiB and a memory limit of 1.5 GiB. {{% code\_sample file="admin/resource/memory-constraints-pod-2.yaml" %}} Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints-pod-2.yaml --namespace=constraints-mem-example ``` The output shows that the Pod does not get created, because it defines a container that requests more memory than is allowed: ``` Error from server (Forbidden): error when creating "examples/admin/resource/memory-constraints-pod-2.yaml": pods "constraints-mem-demo-2" is forbidden: maximum memory usage per Container is 1Gi, but limit is 1536Mi. ``` ## Attempt to create a Pod that does not meet the minimum memory request Here's a manifest for a Pod that has one container. That container specifies a memory request of 100 MiB and a memory limit of 800 MiB. {{% code\_sample file="admin/resource/memory-constraints-pod-3.yaml" %}} Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints-pod-3.yaml --namespace=constraints-mem-example ``` The output shows that the Pod does not get created, because it defines a
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
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|
that has one container. That container specifies a memory request of 100 MiB and a memory limit of 800 MiB. {{% code\_sample file="admin/resource/memory-constraints-pod-3.yaml" %}} Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints-pod-3.yaml --namespace=constraints-mem-example ``` The output shows that the Pod does not get created, because it defines a container that requests less memory than the enforced minimum: ``` Error from server (Forbidden): error when creating "examples/admin/resource/memory-constraints-pod-3.yaml": pods "constraints-mem-demo-3" is forbidden: minimum memory usage per Container is 500Mi, but request is 100Mi. ``` ## Create a Pod that does not specify any memory request or limit Here's a manifest for a Pod that has one container. The container does not specify a memory request, and it does not specify a memory limit. {{% code\_sample file="admin/resource/memory-constraints-pod-4.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-constraints-pod-4.yaml --namespace=constraints-mem-example ``` View detailed information about the Pod: ```shell kubectl get pod constraints-mem-demo-4 --namespace=constraints-mem-example --output=yaml ``` The output shows that the Pod's only container has a memory request of 1 GiB and a memory limit of 1 GiB. How did that container get those values? ``` resources: limits: memory: 1Gi requests: memory: 1Gi ``` Because your Pod did not define any memory request and limit for that container, the cluster applied a [default memory request and limit](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) from the LimitRange. This means that the definition of that Pod shows those values. You can check it using `kubectl describe`: ```shell # Look for the "Requests:" section of the output kubectl describe pod constraints-mem-demo-4 --namespace=constraints-mem-example ``` At this point, your Pod might be running or it might not be running. Recall that a prerequisite for this task is that your Nodes have at least 1 GiB of memory. If each of your Nodes has only 1 GiB of memory, then there is not enough allocatable memory on any Node to accommodate a memory request of 1 GiB. If you happen to be using Nodes with 2 GiB of memory, then you probably have enough space to accommodate the 1 GiB request. Delete your Pod: ```shell kubectl delete pod constraints-mem-demo-4 --namespace=constraints-mem-example ``` ## Enforcement of minimum and maximum memory constraints The maximum and minimum memory constraints imposed on a namespace by a LimitRange are enforced only when a Pod is created or updated. If you change the LimitRange, it does not affect Pods that were created previously. ## Motivation for minimum and maximum memory constraints As a cluster administrator, you might want to impose restrictions on the amount of memory that Pods can use. For example: \* Each Node in a cluster has 2 GiB of memory. You do not want to accept any Pod that requests more than 2 GiB of memory, because no Node in the cluster can support the request. \* A cluster is shared by your production and development departments. You want to allow production workloads to consume up to 8 GiB of memory, but you want development workloads to be limited to 512 MiB. You create separate namespaces for production and development, and you apply memory constraints to each namespace. ## Clean up Delete your namespace: ```shell kubectl delete namespace constraints-mem-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
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] | 0.163328
|
Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace.md
|
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] | 0.176993
|
This page shows how to configure default CPU requests and limits for a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. A Kubernetes cluster can be divided into namespaces. If you create a Pod within a namespace that has a default CPU [limit](/docs/concepts/configuration/manage-resources-containers/#requests-and-limits), and any container in that Pod does not specify its own CPU limit, then the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} assigns the default CPU limit to that container. Kubernetes assigns a default CPU [request](/docs/concepts/configuration/manage-resources-containers/#requests-and-limits), but only under certain conditions that are explained later in this page. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. If you're not already familiar with what Kubernetes means by 1.0 CPU, read [meaning of CPU](/docs/concepts/configuration/manage-resources-containers/#meaning-of-cpu). ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace default-cpu-example ``` ## Create a LimitRange and a Pod Here's a manifest for an example {{< glossary\_tooltip text="LimitRange" term\_id="limitrange" >}}. The manifest specifies a default CPU request and a default CPU limit. {{% code\_sample file="admin/resource/cpu-defaults.yaml" %}} Create the LimitRange in the default-cpu-example namespace: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-defaults.yaml --namespace=default-cpu-example ``` Now if you create a Pod in the default-cpu-example namespace, and any container in that Pod does not specify its own values for CPU request and CPU limit, then the control plane applies default values: a CPU request of 0.5 and a default CPU limit of 1. Here's a manifest for a Pod that has one container. The container does not specify a CPU request and limit. {{% code\_sample file="admin/resource/cpu-defaults-pod.yaml" %}} Create the Pod. ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-defaults-pod.yaml --namespace=default-cpu-example ``` View the Pod's specification: ```shell kubectl get pod default-cpu-demo --output=yaml --namespace=default-cpu-example ``` The output shows that the Pod's only container has a CPU request of 500m `cpu` (which you can read as “500 millicpu”), and a CPU limit of 1 `cpu`. These are the default values specified by the LimitRange. ```shell containers: - image: nginx imagePullPolicy: Always name: default-cpu-demo-ctr resources: limits: cpu: "1" requests: cpu: 500m ``` ## What if you specify a container's limit, but not its request? Here's a manifest for a Pod that has one container. The container specifies a CPU limit, but not a request: {{% code\_sample file="admin/resource/cpu-defaults-pod-2.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-defaults-pod-2.yaml --namespace=default-cpu-example ``` View the [specification](/docs/concepts/overview/working-with-objects/#object-spec-and-status) of the Pod that you created: ``` kubectl get pod default-cpu-demo-2 --output=yaml --namespace=default-cpu-example ``` The output shows that the container's CPU request is set to match its CPU limit. Notice that the container was not assigned the default CPU request value of 0.5 `cpu`: ``` resources: limits: cpu: "1" requests: cpu: "1" ``` ## What if you specify a container's request, but not its limit? Here's an example manifest for a Pod that has one container. The container specifies a CPU request, but not a limit: {{% code\_sample file="admin/resource/cpu-defaults-pod-3.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-defaults-pod-3.yaml --namespace=default-cpu-example ``` View the specification of the Pod that you created: ``` kubectl get pod default-cpu-demo-3 --output=yaml --namespace=default-cpu-example ``` The output shows that the container's CPU request is set to the value you specified at the time you created the Pod (in other words: it matches the manifest). However, the same container's CPU limit is set to 1 `cpu`, which is the default CPU limit for that namespace. ``` resources: limits: cpu: "1" requests: cpu: 750m ``` ## Motivation for default CPU limits and requests If your namespace has a CPU {{< glossary\_tooltip text="resource quota" term\_id="resource-quota" >}} configured, it is helpful to have a default
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace.md
|
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] | 0.095631
|
set to 1 `cpu`, which is the default CPU limit for that namespace. ``` resources: limits: cpu: "1" requests: cpu: 750m ``` ## Motivation for default CPU limits and requests If your namespace has a CPU {{< glossary\_tooltip text="resource quota" term\_id="resource-quota" >}} configured, it is helpful to have a default value in place for CPU limit. Here are two of the restrictions that a CPU resource quota imposes on a namespace: \* For every Pod that runs in the namespace, each of its containers must have a CPU limit. \* CPU limits apply a resource reservation on the node where the Pod in question is scheduled. The total amount of CPU that is reserved for use by all Pods in the namespace must not exceed a specified limit. When you add a LimitRange: If any Pod in that namespace that includes a container does not specify its own CPU limit, the control plane applies the default CPU limit to that container, and the Pod can be allowed to run in a namespace that is restricted by a CPU ResourceQuota. ## Clean up Delete your namespace: ```shell kubectl delete namespace default-cpu-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Minimum and Maximum Memory Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace/) \* [Configure Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace.md
|
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|
This page shows how to set quotas for the total amount memory and CPU that can be used by all Pods running in a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. You specify quotas in a [ResourceQuota](/docs/reference/kubernetes-api/policy-resources/resource-quota-v1/) object. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. Each node in your cluster must have at least 1 GiB of memory. ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace quota-mem-cpu-example ``` ## Create a ResourceQuota Here is a manifest for an example ResourceQuota: {{% code\_sample file="admin/resource/quota-mem-cpu.yaml" %}} Create the ResourceQuota: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/quota-mem-cpu.yaml --namespace=quota-mem-cpu-example ``` View detailed information about the ResourceQuota: ```shell kubectl get resourcequota mem-cpu-demo --namespace=quota-mem-cpu-example --output=yaml ``` The ResourceQuota places these requirements on the quota-mem-cpu-example namespace: \* For every Pod in the namespace, each container must have a memory request, memory limit, cpu request, and cpu limit. \* The memory request total for all Pods in that namespace must not exceed 1 GiB. \* The memory limit total for all Pods in that namespace must not exceed 2 GiB. \* The CPU request total for all Pods in that namespace must not exceed 1 cpu. \* The CPU limit total for all Pods in that namespace must not exceed 2 cpu. See [meaning of CPU](/docs/concepts/configuration/manage-resources-containers/#meaning-of-cpu) to learn what Kubernetes means by “1 CPU”. ## Create a Pod Here is a manifest for an example Pod: {{% code\_sample file="admin/resource/quota-mem-cpu-pod.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/quota-mem-cpu-pod.yaml --namespace=quota-mem-cpu-example ``` Verify that the Pod is running and that its (only) container is healthy: ```shell kubectl get pod quota-mem-cpu-demo --namespace=quota-mem-cpu-example ``` Once again, view detailed information about the ResourceQuota: ```shell kubectl get resourcequota mem-cpu-demo --namespace=quota-mem-cpu-example --output=yaml ``` The output shows the quota along with how much of the quota has been used. You can see that the memory and CPU requests and limits for your Pod do not exceed the quota. ``` status: hard: limits.cpu: "2" limits.memory: 2Gi requests.cpu: "1" requests.memory: 1Gi used: limits.cpu: 800m limits.memory: 800Mi requests.cpu: 400m requests.memory: 600Mi ``` If you have the `jq` tool, you can also query (using [JSONPath](/docs/reference/kubectl/jsonpath/)) for just the `used` values, \*\*and\*\* pretty-print that that of the output. For example: ```shell kubectl get resourcequota mem-cpu-demo --namespace=quota-mem-cpu-example -o jsonpath='{ .status.used }' | jq . ``` ## Attempt to create a second Pod Here is a manifest for a second Pod: {{% code\_sample file="admin/resource/quota-mem-cpu-pod-2.yaml" %}} In the manifest, you can see that the Pod has a memory request of 700 MiB. Notice that the sum of the used memory request and this new memory request exceeds the memory request quota: 600 MiB + 700 MiB > 1 GiB. Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/quota-mem-cpu-pod-2.yaml --namespace=quota-mem-cpu-example ``` The second Pod does not get created. The output shows that creating the second Pod would cause the memory request total to exceed the memory request quota. ``` Error from server (Forbidden): error when creating "examples/admin/resource/quota-mem-cpu-pod-2.yaml": pods "quota-mem-cpu-demo-2" is forbidden: exceeded quota: mem-cpu-demo, requested: requests.memory=700Mi,used: requests.memory=600Mi, limited: requests.memory=1Gi ``` ## Discussion As you have seen in this exercise, you can use a ResourceQuota to restrict the memory request total for all Pods running in a namespace. You can also restrict the totals for memory limit, cpu request, and cpu limit. Instead of managing total resource use within a namespace, you might want to restrict individual Pods, or the containers in those Pods. To achieve that kind of limiting, use a [LimitRange](/docs/concepts/policy/limit-range/). ## Clean up Delete
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace.md
|
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] | 0.108541
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namespace. You can also restrict the totals for memory limit, cpu request, and cpu limit. Instead of managing total resource use within a namespace, you might want to restrict individual Pods, or the containers in those Pods. To achieve that kind of limiting, use a [LimitRange](/docs/concepts/policy/limit-range/). ## Clean up Delete your namespace: ```shell kubectl delete namespace quota-mem-cpu-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum Memory Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace/) \* [Configure Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace.md
|
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] | 0.188109
|
This page shows how to set a quota for the total number of Pods that can run in a {{< glossary\_tooltip text="Namespace" term\_id="namespace" >}}. You specify quotas in a [ResourceQuota](/docs/reference/kubernetes-api/policy-resources/resource-quota-v1/) object. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace quota-pod-example ``` ## Create a ResourceQuota Here is an example manifest for a ResourceQuota: {{% code\_sample file="admin/resource/quota-pod.yaml" %}} Create the ResourceQuota: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/quota-pod.yaml --namespace=quota-pod-example ``` View detailed information about the ResourceQuota: ```shell kubectl get resourcequota pod-demo --namespace=quota-pod-example --output=yaml ``` The output shows that the namespace has a quota of two Pods, and that currently there are no Pods; that is, none of the quota is used. ```yaml spec: hard: pods: "2" status: hard: pods: "2" used: pods: "0" ``` Here is an example manifest for a {{< glossary\_tooltip term\_id="deployment" >}}: {{% code\_sample file="admin/resource/quota-pod-deployment.yaml" %}} In that manifest, `replicas: 3` tells Kubernetes to attempt to create three new Pods, all running the same application. Create the Deployment: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/quota-pod-deployment.yaml --namespace=quota-pod-example ``` View detailed information about the Deployment: ```shell kubectl get deployment pod-quota-demo --namespace=quota-pod-example --output=yaml ``` The output shows that even though the Deployment specifies three replicas, only two Pods were created because of the quota you defined earlier: ```yaml spec: ... replicas: 3 ... status: availableReplicas: 2 ... lastUpdateTime: 2021-04-02T20:57:05Z message: 'unable to create pods: pods "pod-quota-demo-1650323038-" is forbidden: exceeded quota: pod-demo, requested: pods=1, used: pods=2, limited: pods=2' ``` ### Choice of resource In this task you have defined a ResourceQuota that limited the total number of Pods, but you could also limit the total number of other kinds of object. For example, you might decide to limit how many {{< glossary\_tooltip text="CronJobs" term\_id="cronjob" >}} that can live in a single namespace. ## Clean up Delete your namespace: ```shell kubectl delete namespace quota-pod-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum Memory Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace/) \* [Configure Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace.md
|
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] | 0.077267
|
This page shows how to set minimum and maximum values for the CPU resources used by containers and Pods in a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. You specify minimum and maximum CPU values in a [LimitRange](/docs/reference/kubernetes-api/policy-resources/limit-range-v1/) object. If a Pod does not meet the constraints imposed by the LimitRange, it cannot be created in the namespace. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. Each node in your cluster must have at least 1.0 CPU available for Pods. See [meaning of CPU](/docs/concepts/configuration/manage-resources-containers/#meaning-of-cpu) to learn what Kubernetes means by “1 CPU”. ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace constraints-cpu-example ``` ## Create a LimitRange and a Pod Here's a manifest for an example {{< glossary\_tooltip text="LimitRange" term\_id="limitrange" >}}: {{% code\_sample file="admin/resource/cpu-constraints.yaml" %}} Create the LimitRange: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-constraints.yaml --namespace=constraints-cpu-example ``` View detailed information about the LimitRange: ```shell kubectl get limitrange cpu-min-max-demo-lr --output=yaml --namespace=constraints-cpu-example ``` The output shows the minimum and maximum CPU constraints as expected. But notice that even though you didn't specify default values in the configuration file for the LimitRange, they were created automatically. ```yaml limits: - default: cpu: 800m defaultRequest: cpu: 800m max: cpu: 800m min: cpu: 200m type: Container ``` Now whenever you create a Pod in the constraints-cpu-example namespace (or some other client of the Kubernetes API creates an equivalent Pod), Kubernetes performs these steps: \* If any container in that Pod does not specify its own CPU request and limit, the control plane assigns the default CPU request and limit to that container. \* Verify that every container in that Pod specifies a CPU request that is greater than or equal to 200 millicpu. \* Verify that every container in that Pod specifies a CPU limit that is less than or equal to 800 millicpu. {{< note >}} When creating a `LimitRange` object, you can specify limits on huge-pages or GPUs as well. However, when both `default` and `defaultRequest` are specified on these resources, the two values must be the same. {{< /note >}} Here's a manifest for a Pod that has one container. The container manifest specifies a CPU request of 500 millicpu and a CPU limit of 800 millicpu. These satisfy the minimum and maximum CPU constraints imposed by the LimitRange for this namespace. {{% code\_sample file="admin/resource/cpu-constraints-pod.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-constraints-pod.yaml --namespace=constraints-cpu-example ``` Verify that the Pod is running and that its container is healthy: ```shell kubectl get pod constraints-cpu-demo --namespace=constraints-cpu-example ``` View detailed information about the Pod: ```shell kubectl get pod constraints-cpu-demo --output=yaml --namespace=constraints-cpu-example ``` The output shows that the Pod's only container has a CPU request of 500 millicpu and CPU limit of 800 millicpu. These satisfy the constraints imposed by the LimitRange. ```yaml resources: limits: cpu: 800m requests: cpu: 500m ``` ## Delete the Pod ```shell kubectl delete pod constraints-cpu-demo --namespace=constraints-cpu-example ``` ## Attempt to create a Pod that exceeds the maximum CPU constraint Here's a manifest for a Pod that has one container. The container specifies a CPU request of 500 millicpu and a cpu limit of 1.5 cpu. {{% code\_sample file="admin/resource/cpu-constraints-pod-2.yaml" %}} Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-constraints-pod-2.yaml --namespace=constraints-cpu-example ``` The output shows that the Pod does not get created, because it defines an unacceptable container. That container is not acceptable because it specifies a CPU limit that is too large: ``` Error from server (Forbidden): error when creating "examples/admin/resource/cpu-constraints-pod-2.yaml": pods "constraints-cpu-demo-2" is forbidden: maximum
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
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|
apply -f https://k8s.io/examples/admin/resource/cpu-constraints-pod-2.yaml --namespace=constraints-cpu-example ``` The output shows that the Pod does not get created, because it defines an unacceptable container. That container is not acceptable because it specifies a CPU limit that is too large: ``` Error from server (Forbidden): error when creating "examples/admin/resource/cpu-constraints-pod-2.yaml": pods "constraints-cpu-demo-2" is forbidden: maximum cpu usage per Container is 800m, but limit is 1500m. ``` ## Attempt to create a Pod that does not meet the minimum CPU request Here's a manifest for a Pod that has one container. The container specifies a CPU request of 100 millicpu and a CPU limit of 800 millicpu. {{% code\_sample file="admin/resource/cpu-constraints-pod-3.yaml" %}} Attempt to create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-constraints-pod-3.yaml --namespace=constraints-cpu-example ``` The output shows that the Pod does not get created, because it defines an unacceptable container. That container is not acceptable because it specifies a CPU request that is lower than the enforced minimum: ``` Error from server (Forbidden): error when creating "examples/admin/resource/cpu-constraints-pod-3.yaml": pods "constraints-cpu-demo-3" is forbidden: minimum cpu usage per Container is 200m, but request is 100m. ``` ## Create a Pod that does not specify any CPU request or limit Here's a manifest for a Pod that has one container. The container does not specify a CPU request, nor does it specify a CPU limit. {{% code\_sample file="admin/resource/cpu-constraints-pod-4.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/cpu-constraints-pod-4.yaml --namespace=constraints-cpu-example ``` View detailed information about the Pod: ``` kubectl get pod constraints-cpu-demo-4 --namespace=constraints-cpu-example --output=yaml ``` The output shows that the Pod's single container has a CPU request of 800 millicpu and a CPU limit of 800 millicpu. How did that container get those values? ```yaml resources: limits: cpu: 800m requests: cpu: 800m ``` Because that container did not specify its own CPU request and limit, the control plane applied the [default CPU request and limit](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) from the LimitRange for this namespace. At this point, your Pod may or may not be running. Recall that a prerequisite for this task is that your Nodes must have at least 1 CPU available for use. If each of your Nodes has only 1 CPU, then there might not be enough allocatable CPU on any Node to accommodate a request of 800 millicpu. If you happen to be using Nodes with 2 CPU, then you probably have enough CPU to accommodate the 800 millicpu request. Delete your Pod: ``` kubectl delete pod constraints-cpu-demo-4 --namespace=constraints-cpu-example ``` ## Enforcement of minimum and maximum CPU constraints The maximum and minimum CPU constraints imposed on a namespace by a LimitRange are enforced only when a Pod is created or updated. If you change the LimitRange, it does not affect Pods that were created previously. ## Motivation for minimum and maximum CPU constraints As a cluster administrator, you might want to impose restrictions on the CPU resources that Pods can use. For example: \* Each Node in a cluster has 2 CPU. You do not want to accept any Pod that requests more than 2 CPU, because no Node in the cluster can support the request. \* A cluster is shared by your production and development departments. You want to allow production workloads to consume up to 3 CPU, but you want development workloads to be limited to 1 CPU. You create separate namespaces for production and development, and you apply CPU constraints to each namespace. ## Clean up Delete your namespace: ```shell kubectl delete namespace constraints-cpu-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
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] | 0.135722
|
constraints to each namespace. ## Clean up Delete your namespace: ```shell kubectl delete namespace constraints-cpu-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default Memory Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum Memory Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace.md
|
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] | 0.18291
|
This page shows how to configure default memory requests and limits for a {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. A Kubernetes cluster can be divided into namespaces. Once you have a namespace that has a default memory [limit](/docs/concepts/configuration/manage-resources-containers/#requests-and-limits), and you then try to create a Pod with a container that does not specify its own memory limit, then the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} assigns the default memory limit to that container. Kubernetes assigns a default memory request under certain conditions that are explained later in this topic. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} You must have access to create namespaces in your cluster. Each node in your cluster must have at least 2 GiB of memory. ## Create a namespace Create a namespace so that the resources you create in this exercise are isolated from the rest of your cluster. ```shell kubectl create namespace default-mem-example ``` ## Create a LimitRange and a Pod Here's a manifest for an example {{< glossary\_tooltip text="LimitRange" term\_id="limitrange" >}}. The manifest specifies a default memory request and a default memory limit. {{% code\_sample file="admin/resource/memory-defaults.yaml" %}} Create the LimitRange in the default-mem-example namespace: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-defaults.yaml --namespace=default-mem-example ``` Now if you create a Pod in the default-mem-example namespace, and any container within that Pod does not specify its own values for memory request and memory limit, then the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} applies default values: a memory request of 256MiB and a memory limit of 512MiB. Here's an example manifest for a Pod that has one container. The container does not specify a memory request and limit. {{% code\_sample file="admin/resource/memory-defaults-pod.yaml" %}} Create the Pod. ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-defaults-pod.yaml --namespace=default-mem-example ``` View detailed information about the Pod: ```shell kubectl get pod default-mem-demo --output=yaml --namespace=default-mem-example ``` The output shows that the Pod's container has a memory request of 256 MiB and a memory limit of 512 MiB. These are the default values specified by the LimitRange. ```shell containers: - image: nginx imagePullPolicy: Always name: default-mem-demo-ctr resources: limits: memory: 512Mi requests: memory: 256Mi ``` Delete your Pod: ```shell kubectl delete pod default-mem-demo --namespace=default-mem-example ``` ## What if you specify a container's limit, but not its request? Here's a manifest for a Pod that has one container. The container specifies a memory limit, but not a request: {{% code\_sample file="admin/resource/memory-defaults-pod-2.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-defaults-pod-2.yaml --namespace=default-mem-example ``` View detailed information about the Pod: ```shell kubectl get pod default-mem-demo-2 --output=yaml --namespace=default-mem-example ``` The output shows that the container's memory request is set to match its memory limit. Notice that the container was not assigned the default memory request value of 256Mi. ``` resources: limits: memory: 1Gi requests: memory: 1Gi ``` ## What if you specify a container's request, but not its limit? Here's a manifest for a Pod that has one container. The container specifies a memory request, but not a limit: {{% code\_sample file="admin/resource/memory-defaults-pod-3.yaml" %}} Create the Pod: ```shell kubectl apply -f https://k8s.io/examples/admin/resource/memory-defaults-pod-3.yaml --namespace=default-mem-example ``` View the Pod's specification: ```shell kubectl get pod default-mem-demo-3 --output=yaml --namespace=default-mem-example ``` The output shows that the container's memory request is set to the value specified in the container's manifest. The container is limited to use no more than 512MiB of memory, which matches the default memory limit for the namespace. ``` resources: limits: memory: 512Mi requests: memory: 128Mi ``` {{< note >}} A `LimitRange` does \*\*not\*\* check the consistency of the default values it applies. This means that a default value for the \_limit\_ that is set by `LimitRange` may be less than the \_request\_ value specified for the container in
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/memory-default-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/memory-default-namespace.md
|
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|
resources: limits: memory: 512Mi requests: memory: 128Mi ``` {{< note >}} A `LimitRange` does \*\*not\*\* check the consistency of the default values it applies. This means that a default value for the \_limit\_ that is set by `LimitRange` may be less than the \_request\_ value specified for the container in the spec that a client submits to the API server. If that happens, the final Pod will not be scheduleable. See [Constraints on resource limits and requests](/docs/concepts/policy/limit-range/#constraints-on-resource-limits-and-requests) for more details. {{< /note >}} ## Motivation for default memory limits and requests If your namespace has a memory {{< glossary\_tooltip text="resource quota" term\_id="resource-quota" >}} configured, it is helpful to have a default value in place for memory limit. Here are three of the restrictions that a resource quota imposes on a namespace: \* For every Pod that runs in the namespace, the Pod and each of its containers must have a memory limit. (If you specify a memory limit for every container in a Pod, Kubernetes can infer the Pod-level memory limit by adding up the limits for its containers). \* Memory limits apply a resource reservation on the node where the Pod in question is scheduled. The total amount of memory reserved for all Pods in the namespace must not exceed a specified limit. \* The total amount of memory actually used by all Pods in the namespace must also not exceed a specified limit. When you add a LimitRange: If any Pod in that namespace that includes a container does not specify its own memory limit, the control plane applies the default memory limit to that container, and the Pod can be allowed to run in a namespace that is restricted by a memory ResourceQuota. ## Clean up Delete your namespace: ```shell kubectl delete namespace default-mem-example ``` ## {{% heading "whatsnext" %}} ### For cluster administrators \* [Configure Default CPU Requests and Limits for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-default-namespace/) \* [Configure Minimum and Maximum Memory Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/memory-constraint-namespace/) \* [Configure Minimum and Maximum CPU Constraints for a Namespace](/docs/tasks/administer-cluster/manage-resources/cpu-constraint-namespace/) \* [Configure Memory and CPU Quotas for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-memory-cpu-namespace/) \* [Configure a Pod Quota for a Namespace](/docs/tasks/administer-cluster/manage-resources/quota-pod-namespace/) \* [Configure Quotas for API Objects](/docs/tasks/administer-cluster/quota-api-object/) ### For app developers \* [Assign Memory Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/) \* [Assign CPU Resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/) \* [Assign Pod-level CPU and memory resources](/docs/tasks/configure-pod-container/assign-pod-level-resources/) \* [Configure Quality of Service for Pods](/docs/tasks/configure-pod-container/quality-service-pod/)
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/manage-resources/memory-default-namespace.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/manage-resources/memory-default-namespace.md
|
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] | 0.117589
|
This page shows how to use Romana for NetworkPolicy. ## {{% heading "prerequisites" %}} Complete steps 1, 2, and 3 of the [kubeadm getting started guide](/docs/reference/setup-tools/kubeadm/). ## Installing Romana with kubeadm Follow the [containerized installation guide](https://github.com/romana/romana/tree/master/containerize) for kubeadm. ## Applying network policies To apply network policies use one of the following: \* [Romana network policies](https://github.com/romana/romana/wiki/Romana-policies). \* [Example of Romana network policy](https://github.com/romana/core/blob/master/doc/policy.md). \* The NetworkPolicy API. ## {{% heading "whatsnext" %}} Once you have installed Romana, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/romana-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/romana-network-policy.md
|
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] | 0.163493
|
This page shows a couple of quick ways to create a Calico cluster on Kubernetes. ## {{% heading "prerequisites" %}} Decide whether you want to deploy a [cloud](#creating-a-calico-cluster-with-google-kubernetes-engine-gke) or [local](#creating-a-local-calico-cluster-with-kubeadm) cluster. ## Creating a Calico cluster with Google Kubernetes Engine (GKE) \*\*Prerequisite\*\*: [gcloud](https://cloud.google.com/sdk/docs/quickstarts). 1. To launch a GKE cluster with Calico, include the `--enable-network-policy` flag. \*\*Syntax\*\* ```shell gcloud container clusters create [CLUSTER\_NAME] --enable-network-policy ``` \*\*Example\*\* ```shell gcloud container clusters create my-calico-cluster --enable-network-policy ``` 1. To verify the deployment, use the following command. ```shell kubectl get pods --namespace=kube-system ``` The Calico pods begin with `calico`. Check to make sure each one has a status of `Running`. ## Creating a local Calico cluster with kubeadm To get a local single-host Calico cluster in fifteen minutes using kubeadm, refer to the [Calico Quickstart](https://projectcalico.docs.tigera.io/getting-started/kubernetes/). ## {{% heading "whatsnext" %}} Once your cluster is running, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/calico-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/calico-network-policy.md
|
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] | 0.094821
|
This page shows how to use [Kube-router](https://github.com/cloudnativelabs/kube-router) for NetworkPolicy. ## {{% heading "prerequisites" %}} You need to have a Kubernetes cluster running. If you do not already have a cluster, you can create one by using any of the cluster installers like Kops, Bootkube, Kubeadm etc. ## Installing Kube-router addon The Kube-router Addon comes with a Network Policy Controller that watches Kubernetes API server for any NetworkPolicy and pods updated and configures iptables rules and ipsets to allow or block traffic as directed by the policies. Please follow the [trying Kube-router with cluster installers](https://www.kube-router.io/docs/user-guide/#try-kube-router-with-cluster-installers) guide to install Kube-router addon. ## {{% heading "whatsnext" %}} Once you have installed the Kube-router addon, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/kube-router-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/kube-router-network-policy.md
|
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] | 0.063447
|
This page shows how to use Weave Net for NetworkPolicy. ## {{% heading "prerequisites" %}} You need to have a Kubernetes cluster. Follow the [kubeadm getting started guide](/docs/reference/setup-tools/kubeadm/) to bootstrap one. ## Install the Weave Net addon Follow the [Integrating Kubernetes via the Addon](https://github.com/weaveworks/weave/blob/master/site/kubernetes/kube-addon.md#-installation) guide. The Weave Net addon for Kubernetes comes with a [Network Policy Controller](https://github.com/weaveworks/weave/blob/master/site/kubernetes/kube-addon.md#network-policy) that automatically monitors Kubernetes for any NetworkPolicy annotations on all namespaces and configures `iptables` rules to allow or block traffic as directed by the policies. ## Test the installation Verify that the weave works. Enter the following command: ```shell kubectl get pods -n kube-system -o wide ``` The output is similar to this: ``` NAME READY STATUS RESTARTS AGE IP NODE weave-net-1t1qg 2/2 Running 0 9d 192.168.2.10 worknode3 weave-net-231d7 2/2 Running 1 7d 10.2.0.17 worknodegpu weave-net-7nmwt 2/2 Running 3 9d 192.168.2.131 masternode weave-net-pmw8w 2/2 Running 0 9d 192.168.2.216 worknode2 ``` Each Node has a weave Pod, and all Pods are `Running` and `2/2 READY`. (`2/2` means that each Pod has `weave` and `weave-npc`.) ## {{% heading "whatsnext" %}} Once you have installed the Weave Net addon, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy. If you have any question, contact us at [#weave-community on Slack or Weave User Group](https://github.com/weaveworks/weave#getting-help).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/weave-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/weave-network-policy.md
|
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] | 0.0713
|
This page shows how to use Cilium for NetworkPolicy. For background on Cilium, read the [Introduction to Cilium](https://docs.cilium.io/en/stable/overview/intro). ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}} ## Deploying Cilium on Minikube for Basic Testing To get familiar with Cilium easily you can follow the [Cilium Kubernetes Getting Started Guide](https://docs.cilium.io/en/stable/gettingstarted/k8s-install-default/) to perform a basic DaemonSet installation of Cilium in minikube. To start minikube, minimal version required is >= v1.5.2, run the with the following arguments: ```shell minikube version ``` ``` minikube version: v1.5.2 ``` ```shell minikube start --network-plugin=cni ``` For minikube you can install Cilium using its CLI tool. To do so, first download the latest version of the CLI with the following command: ```shell curl -LO https://github.com/cilium/cilium-cli/releases/latest/download/cilium-linux-amd64.tar.gz ``` Then extract the downloaded file to your `/usr/local/bin` directory with the following command: ```shell sudo tar xzvfC cilium-linux-amd64.tar.gz /usr/local/bin rm cilium-linux-amd64.tar.gz ``` After running the above commands, you can now install Cilium with the following command: ```shell cilium install ``` Cilium will then automatically detect the cluster configuration and create and install the appropriate components for a successful installation. The components are: - Certificate Authority (CA) in Secret `cilium-ca` and certificates for Hubble (Cilium's observability layer). - Service accounts. - Cluster roles. - ConfigMap. - Agent DaemonSet and an Operator Deployment. After the installation, you can view the overall status of the Cilium deployment with the `cilium status` command. See the expected output of the `status` command [here](https://docs.cilium.io/en/stable/gettingstarted/k8s-install-default/#validate-the-installation). The remainder of the Getting Started Guide explains how to enforce both L3/L4 (i.e., IP address + port) security policies, as well as L7 (e.g., HTTP) security policies using an example application. ## Deploying Cilium for Production Use For detailed instructions around deploying Cilium for production, see: [Cilium Kubernetes Installation Guide](https://docs.cilium.io/en/stable/network/kubernetes/concepts/) This documentation includes detailed requirements, instructions and example production DaemonSet files. ## Understanding Cilium components Deploying a cluster with Cilium adds Pods to the `kube-system` namespace. To see this list of Pods run: ```shell kubectl get pods --namespace=kube-system -l k8s-app=cilium ``` You'll see a list of Pods similar to this: ```console NAME READY STATUS RESTARTS AGE cilium-kkdhz 1/1 Running 0 3m23s ... ``` A `cilium` Pod runs on each node in your cluster and enforces network policy on the traffic to/from Pods on that node using Linux BPF. ## {{% heading "whatsnext" %}} Once your cluster is running, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy with Cilium. Have fun, and if you have questions, contact us using the [Cilium Slack Channel](https://slack.cilium.io/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/cilium-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/cilium-network-policy.md
|
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] | 0.124548
|
This page shows how to install and use Antrea CNI plugin on Kubernetes. For background on Project Antrea, read the [Introduction to Antrea](https://antrea.io/docs/). ## {{% heading "prerequisites" %}} You need to have a Kubernetes cluster. Follow the [kubeadm getting started guide](/docs/reference/setup-tools/kubeadm/) to bootstrap one. ## Deploying Antrea with kubeadm Follow [Getting Started](https://github.com/vmware-tanzu/antrea/blob/main/docs/getting-started.md) guide to deploy Antrea for kubeadm. ## {{% heading "whatsnext" %}} Once your cluster is running, you can follow the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/) to try out Kubernetes NetworkPolicy.
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/network-policy-provider/antrea-network-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/network-policy-provider/antrea-network-policy.md
|
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] | 0.2088
|
This page explains how to enable a package repository for the desired Kubernetes minor release upon upgrading a cluster. This is only needed for users of the community-owned package repositories hosted at `pkgs.k8s.io`. Unlike the legacy package repositories, the community-owned package repositories are structured in a way that there's a dedicated package repository for each Kubernetes minor version. {{< note >}} This guide only covers a part of the Kubernetes upgrade process. Please see the [upgrade guide](/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) for more information about upgrading Kubernetes clusters. {{}} {{< note >}} This step is only needed upon upgrading a cluster to another \*\*minor\*\* release. If you're upgrading to another patch release within the same minor release (e.g. v{{< skew currentVersion >}}.5 to v{{< skew currentVersion >}}.7), you don't need to follow this guide. However, if you're still using the legacy package repositories, you'll need to migrate to the new community-owned package repositories before upgrading (see the next section for more details on how to do this). {{}} ## {{% heading "prerequisites" %}} This document assumes that you're already using the community-owned package repositories (`pkgs.k8s.io`). If that's not the case, it's strongly recommended to migrate to the community-owned package repositories as described in the [official announcement](/blog/2023/08/15/pkgs-k8s-io-introduction/). {{% legacy-repos-deprecation %}} ### Verifying if the Kubernetes package repositories are used If you're unsure whether you're using the community-owned package repositories or the legacy package repositories, take the following steps to verify: {{< tabs name="k8s\_install\_versions" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} Print the contents of the file that defines the Kubernetes `apt` repository: ```shell # On your system, this configuration file could have a different name pager /etc/apt/sources.list.d/kubernetes.list ``` If you see a line similar to: ``` deb [signed-by=/etc/apt/keyrings/kubernetes-apt-keyring.gpg] https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/deb/ / ``` \*\*You're using the Kubernetes package repositories and this guide applies to you.\*\* Otherwise, it's strongly recommended to migrate to the Kubernetes package repositories as described in the [official announcement](/blog/2023/08/15/pkgs-k8s-io-introduction/). {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} Print the contents of the file that defines the Kubernetes `yum` repository: ```shell # On your system, this configuration file could have a different name cat /etc/yum.repos.d/kubernetes.repo ``` If you see a `baseurl` similar to the `baseurl` in the output below: ``` [kubernetes] name=Kubernetes baseurl=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/ enabled=1 gpgcheck=1 gpgkey=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/repodata/repomd.xml.key exclude=kubelet kubeadm kubectl ``` \*\*You're using the Kubernetes package repositories and this guide applies to you.\*\* Otherwise, it's strongly recommended to migrate to the Kubernetes package repositories as described in the [official announcement](/blog/2023/08/15/pkgs-k8s-io-introduction/). {{% /tab %}} {{% tab name="openSUSE or SLES" %}} Print the contents of the file that defines the Kubernetes `zypper` repository: ```shell # On your system, this configuration file could have a different name cat /etc/zypp/repos.d/kubernetes.repo ``` If you see a `baseurl` similar to the `baseurl` in the output below: ``` [kubernetes] name=Kubernetes baseurl=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/ enabled=1 gpgcheck=1 gpgkey=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/repodata/repomd.xml.key exclude=kubelet kubeadm kubectl ``` \*\*You're using the Kubernetes package repositories and this guide applies to you.\*\* Otherwise, it's strongly recommended to migrate to the Kubernetes package repositories as described in the [official announcement](/blog/2023/08/15/pkgs-k8s-io-introduction/). {{% /tab %}} {{< /tabs >}} {{< note >}} The URL used for the Kubernetes package repositories is not limited to `pkgs.k8s.io`, it can also be one of: - `pkgs.k8s.io` - `pkgs.kubernetes.io` - `packages.kubernetes.io` {{}} ## Switching to another Kubernetes package repository This step should be done upon upgrading from one to another Kubernetes minor release in order to get access to the packages of the desired Kubernetes minor version. {{< tabs name="k8s\_upgrade\_versions" >}} {{% tab name="Ubuntu, Debian
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/change-package-repository.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/change-package-repository.md
|
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|
- `pkgs.k8s.io` - `pkgs.kubernetes.io` - `packages.kubernetes.io` {{}} ## Switching to another Kubernetes package repository This step should be done upon upgrading from one to another Kubernetes minor release in order to get access to the packages of the desired Kubernetes minor version. {{< tabs name="k8s\_upgrade\_versions" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} 1. Open the file that defines the Kubernetes `apt` repository using a text editor of your choice: ```shell nano /etc/apt/sources.list.d/kubernetes.list ``` You should see a single line with the URL that contains your current Kubernetes minor version. For example, if you're using v{{< skew currentVersionAddMinor -1 "." >}}, you should see this: ``` deb [signed-by=/etc/apt/keyrings/kubernetes-apt-keyring.gpg] https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/deb/ / ``` 1. Change the version in the URL to \*\*the next available minor release\*\*, for example: ``` deb [signed-by=/etc/apt/keyrings/kubernetes-apt-keyring.gpg] https://pkgs.k8s.io/core:/stable:/{{< param "version" >}}/deb/ / ``` 1. Save the file and exit your text editor. Continue following the relevant upgrade instructions. {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} 1. Open the file that defines the Kubernetes `yum` repository using a text editor of your choice: ```shell nano /etc/yum.repos.d/kubernetes.repo ``` You should see a file with two URLs that contain your current Kubernetes minor version. For example, if you're using v{{< skew currentVersionAddMinor -1 "." >}}, you should see this: ``` [kubernetes] name=Kubernetes baseurl=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/ enabled=1 gpgcheck=1 gpgkey=https://pkgs.k8s.io/core:/stable:/v{{< skew currentVersionAddMinor -1 "." >}}/rpm/repodata/repomd.xml.key exclude=kubelet kubeadm kubectl cri-tools kubernetes-cni ``` 1. Change the version in these URLs to \*\*the next available minor release\*\*, for example: ``` [kubernetes] name=Kubernetes baseurl=https://pkgs.k8s.io/core:/stable:/{{< param "version" >}}/rpm/ enabled=1 gpgcheck=1 gpgkey=https://pkgs.k8s.io/core:/stable:/{{< param "version" >}}/rpm/repodata/repomd.xml.key exclude=kubelet kubeadm kubectl cri-tools kubernetes-cni ``` 1. Save the file and exit your text editor. Continue following the relevant upgrade instructions. {{% /tab %}} {{< /tabs >}} ## {{% heading "whatsnext" %}} \* See how to [Upgrade Linux nodes](/docs/tasks/administer-cluster/kubeadm/upgrading-linux-nodes/). \* See how to [Upgrade Windows nodes](/docs/tasks/administer-cluster/kubeadm/upgrading-windows-nodes/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/change-package-repository.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/change-package-repository.md
|
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|
This page explains how to upgrade a Linux Worker Nodes created with kubeadm. ## {{% heading "prerequisites" %}} {{< include "task-tutorial-prereqs-node-upgrade.md" >}} {{< version-check >}} \* Familiarize yourself with [the process for upgrading the rest of your kubeadm cluster](/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade). You will want to upgrade the control plane nodes before upgrading your Linux Worker nodes. ## Changing the package repository If you're using the community-owned package repositories (`pkgs.k8s.io`), you need to enable the package repository for the desired Kubernetes minor release. This is explained in [Changing the Kubernetes package repository](/docs/tasks/administer-cluster/kubeadm/change-package-repository/) document. {{% legacy-repos-deprecation %}} ## Upgrading worker nodes ### Upgrade kubeadm Upgrade kubeadm: {{< tabs name="k8s\_install\_kubeadm\_worker\_nodes" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo apt-mark unhold kubeadm && \ sudo apt-get update && sudo apt-get install -y kubeadm='{{< skew currentVersion >}}.x-\*' && \ sudo apt-mark hold kubeadm ``` {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} For systems with DNF: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubeadm-'{{< skew currentVersion >}}.x-\*' --disableexcludes=kubernetes ``` For systems with DNF5: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubeadm-'{{< skew currentVersion >}}.x-\*' --setopt=disable\_excludes=kubernetes ``` {{% /tab %}} {{< /tabs >}} ### Call "kubeadm upgrade" For worker nodes this upgrades the local kubelet configuration: ```shell sudo kubeadm upgrade node ``` ### Drain the node Prepare the node for maintenance by marking it unschedulable and evicting the workloads: ```shell # execute this command on a control plane node # replace with the name of your node you are draining kubectl drain --ignore-daemonsets ``` ### Upgrade kubelet and kubectl 1. Upgrade the kubelet and kubectl: {{< tabs name="k8s\_kubelet\_and\_kubectl" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo apt-mark unhold kubelet kubectl && \ sudo apt-get update && sudo apt-get install -y kubelet='{{< skew currentVersion >}}.x-\*' kubectl='{{< skew currentVersion >}}.x-\*' && \ sudo apt-mark hold kubelet kubectl ``` {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} For systems with DNF: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubelet-'{{< skew currentVersion >}}.x-\*' kubectl-'{{< skew currentVersion >}}.x-\*' --disableexcludes=kubernetes ``` For systems with DNF5: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubelet-'{{< skew currentVersion >}}.x-\*' kubectl-'{{< skew currentVersion >}}.x-\*' --setopt=disable\_excludes=kubernetes ``` {{% /tab %}} {{< /tabs >}} 1. Restart the kubelet: ```shell sudo systemctl daemon-reload sudo systemctl restart kubelet ``` ### Uncordon the node Bring the node back online by marking it schedulable: ```shell # execute this command on a control plane node # replace with the name of your node kubectl uncordon ``` ## {{% heading "whatsnext" %}} \* See how to [Upgrade Windows nodes](/docs/tasks/administer-cluster/kubeadm/upgrading-windows-nodes/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/upgrading-linux-nodes.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/upgrading-linux-nodes.md
|
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|
This page explains how to add Linux worker nodes to a kubeadm cluster. ## {{% heading "prerequisites" %}} \* Each joining worker node has installed the required components from [Installing kubeadm](/docs/setup/production-environment/tools/kubeadm/install-kubeadm/), such as, kubeadm, the kubelet and a {{< glossary\_tooltip term\_id="container-runtime" text="container runtime" >}}. \* A running kubeadm cluster created by `kubeadm init` and following the steps in the document [Creating a cluster with kubeadm](/docs/setup/production-environment/tools/kubeadm/create-cluster-kubeadm/). \* You need superuser access to the node. ## Adding Linux worker nodes To add new Linux worker nodes to your cluster do the following for each machine: 1. Connect to the machine by using SSH or another method. 1. Run the command that was output by `kubeadm init`. For example: ```bash sudo kubeadm join --token : --discovery-token-ca-cert-hash sha256: ``` ### Additional information for kubeadm join {{< note >}} To specify an IPv6 tuple for `:`, IPv6 address must be enclosed in square brackets, for example: `[2001:db8::101]:2073`. {{< /note >}} If you do not have the token, you can get it by running the following command on the control plane node: ```bash # Run this on a control plane node sudo kubeadm token list ``` The output is similar to this: ```console TOKEN TTL EXPIRES USAGES DESCRIPTION EXTRA GROUPS 8ewj1p.9r9hcjoqgajrj4gi 23h 2018-06-12T02:51:28Z authentication, The default bootstrap system: signing token generated by bootstrappers: 'kubeadm init'. kubeadm: default-node-token ``` By default, node join tokens expire after 24 hours. If you are joining a node to the cluster after the current token has expired, you can create a new token by running the following command on the control plane node: ```bash # Run this on a control plane node sudo kubeadm token create ``` The output is similar to this: ```console 5didvk.d09sbcov8ph2amjw ``` To print a kubeadm join command while also generating a new token you can use: ```bash sudo kubeadm token create --print-join-command ``` If you don't have the value of `--discovery-token-ca-cert-hash`, you can get it by running the following commands on the control plane node: ```bash # Run this on a control plane node sudo cat /etc/kubernetes/pki/ca.crt | openssl x509 -pubkey | openssl rsa -pubin -outform der 2>/dev/null | \ openssl dgst -sha256 -hex | sed 's/^.\* //' ``` The output is similar to: ```console 8cb2de97839780a412b93877f8507ad6c94f73add17d5d7058e91741c9d5ec78 ``` The output of the `kubeadm join` command should look something like: ``` [preflight] Running pre-flight checks ... (log output of join workflow) ... Node join complete: \* Certificate signing request sent to control-plane and response received. \* Kubelet informed of new secure connection details. Run 'kubectl get nodes' on control-plane to see this machine join. ``` A few seconds later, you should notice this node in the output from `kubectl get nodes`. (for example, run `kubectl` on a control plane node). {{< note >}} As the cluster nodes are usually initialized sequentially, the CoreDNS Pods are likely to all run on the first control plane node. To provide higher availability, please rebalance the CoreDNS Pods with `kubectl -n kube-system rollout restart deployment coredns` after at least one new node is joined. {{< /note >}} ## {{% heading "whatsnext" %}} \* See how to [add Windows worker nodes](/docs/tasks/administer-cluster/kubeadm/adding-windows-nodes/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/adding-linux-nodes.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/adding-linux-nodes.md
|
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|
{{< feature-state for\_k8s\_version="v1.18" state="beta" >}} This page explains how to add Windows worker nodes to a kubeadm cluster. ## {{% heading "prerequisites" %}} \* A running [Windows Server 2022](https://www.microsoft.com/cloud-platform/windows-server-pricing) (or higher) instance with administrative access. \* A running kubeadm cluster created by `kubeadm init` and following the steps in the document [Creating a cluster with kubeadm](/docs/setup/production-environment/tools/kubeadm/create-cluster-kubeadm/). ## Adding Windows worker nodes {{< note >}} To facilitate the addition of Windows worker nodes to a cluster, PowerShell scripts from the repository https://sigs.k8s.io/sig-windows-tools are used. {{< /note >}} Do the following for each machine: 1. Open a PowerShell session on the machine. 1. Make sure you are Administrator or a privileged user. Then proceed with the steps outlined below. ### Install containerd {{% thirdparty-content %}} To install containerd, first run the following command: ```PowerShell curl.exe -LO https://raw.githubusercontent.com/kubernetes-sigs/sig-windows-tools/master/hostprocess/Install-Containerd.ps1 `````` Then run the following command, but first replace `CONTAINERD\_VERSION` with a recent release from the [containerd repository](https://github.com/containerd/containerd/releases). The version must not have a `v` prefix. For example, use `1.7.22` instead of `v1.7.22`: ```PowerShell .\Install-Containerd.ps1 -ContainerDVersion CONTAINERD\_VERSION ``` \* Adjust any other parameters for `Install-Containerd.ps1` such as `netAdapterName` as you need them. \* Set `skipHypervisorSupportCheck` if your machine does not support Hyper-V and cannot host Hyper-V isolated containers. \* If you change the `Install-Containerd.ps1` optional parameters `CNIBinPath` and/or `CNIConfigPath` you will need to configure the installed Windows CNI plugin with matching values. ### Install kubeadm and kubelet Run the following commands to install kubeadm and the kubelet: ```PowerShell curl.exe -LO https://raw.githubusercontent.com/kubernetes-sigs/sig-windows-tools/master/hostprocess/PrepareNode.ps1 .\PrepareNode.ps1 -KubernetesVersion v{{< skew currentPatchVersion >}} ``` \* Adjust the parameter `KubernetesVersion` of `PrepareNode.ps1` if needed. ### Run `kubeadm join` Run the command that was output by `kubeadm init`. For example: ```bash kubeadm join --token : --discovery-token-ca-cert-hash sha256: ``` #### Additional information about kubeadm join {{< note >}} To specify an IPv6 tuple for `:`, IPv6 address must be enclosed in square brackets, for example: `[2001:db8::101]:2073`. {{< /note >}} If you do not have the token, you can get it by running the following command on the control plane node: ```bash # Run this on a control plane node sudo kubeadm token list ``` The output is similar to this: ```console TOKEN TTL EXPIRES USAGES DESCRIPTION EXTRA GROUPS 8ewj1p.9r9hcjoqgajrj4gi 23h 2018-06-12T02:51:28Z authentication, The default bootstrap system: signing token generated by bootstrappers: 'kubeadm init'. kubeadm: default-node-token ``` By default, node join tokens expire after 24 hours. If you are joining a node to the cluster after the current token has expired, you can create a new token by running the following command on the control plane node: ```bash # Run this on a control plane node sudo kubeadm token create ``` The output is similar to this: ```console 5didvk.d09sbcov8ph2amjw ``` If you don't have the value of `--discovery-token-ca-cert-hash`, you can get it by running the following commands on the control plane node: ```bash sudo cat /etc/kubernetes/pki/ca.crt | openssl x509 -pubkey | openssl rsa -pubin -outform der 2>/dev/null | \ openssl dgst -sha256 -hex | sed 's/^.\* //' ``` The output is similar to: ```console 8cb2de97839780a412b93877f8507ad6c94f73add17d5d7058e91741c9d5ec78 ``` The output of the `kubeadm join` command should look something like: ``` [preflight] Running pre-flight checks ... (log output of join workflow) ... Node join complete: \* Certificate signing request sent to control-plane and response received. \* Kubelet informed of new secure connection details. Run 'kubectl get nodes' on control-plane to see this machine join. ``` A few seconds later, you should notice this node in the output from `kubectl get nodes`. (for example, run `kubectl` on a control plane node). ### Network configuration CNI setup on clusters mixed with Linux and Windows nodes requires more steps than just
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/adding-windows-nodes.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/adding-windows-nodes.md
|
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|
control-plane to see this machine join. ``` A few seconds later, you should notice this node in the output from `kubectl get nodes`. (for example, run `kubectl` on a control plane node). ### Network configuration CNI setup on clusters mixed with Linux and Windows nodes requires more steps than just running `kubectl apply` on a manifest file. Additionally, the CNI plugin running on control plane nodes must be prepared to support the CNI plugin running on Windows worker nodes. {{% thirdparty-content %}} Only a few CNI plugins currently support Windows. Below you can find individual setup instructions for them: \* [Flannel](https://sigs.k8s.io/sig-windows-tools/guides/flannel.md) \* [Calico](https://docs.tigera.io/calico/latest/getting-started/kubernetes/windows-calico/) ### Install kubectl for Windows (optional) {#install-kubectl} See [Install and Set Up kubectl on Windows](/docs/tasks/tools/install-kubectl-windows/). ## {{% heading "whatsnext" %}} \* See how to [add Linux worker nodes](/docs/tasks/administer-cluster/kubeadm/adding-linux-nodes/).
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/adding-windows-nodes.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/adding-windows-nodes.md
|
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] | 0.117689
|
This page explains how to upgrade a Kubernetes cluster created with kubeadm from version {{< skew currentVersionAddMinor -1 >}}.x to version {{< skew currentVersion >}}.x, and from version {{< skew currentVersion >}}.x to {{< skew currentVersion >}}.y (where `y > x`). Skipping MINOR versions when upgrading is unsupported. For more details, please visit [Version Skew Policy](/releases/version-skew-policy/). To see information about upgrading clusters created using older versions of kubeadm, please refer to following pages instead: - [Upgrading a kubeadm cluster from {{< skew currentVersionAddMinor -2 >}} to {{< skew currentVersionAddMinor -1 >}}](https://v{{< skew currentVersionAddMinor -1 "-" >}}.docs.kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) - [Upgrading a kubeadm cluster from {{< skew currentVersionAddMinor -3 >}} to {{< skew currentVersionAddMinor -2 >}}](https://v{{< skew currentVersionAddMinor -2 "-" >}}.docs.kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) - [Upgrading a kubeadm cluster from {{< skew currentVersionAddMinor -4 >}} to {{< skew currentVersionAddMinor -3 >}}](https://v{{< skew currentVersionAddMinor -3 "-" >}}.docs.kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) - [Upgrading a kubeadm cluster from {{< skew currentVersionAddMinor -5 >}} to {{< skew currentVersionAddMinor -4 >}}](https://v{{< skew currentVersionAddMinor -4 "-" >}}.docs.kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade/) The Kubernetes project recommends upgrading to the latest patch releases promptly, and to ensure that you are running a supported minor release of Kubernetes. Following this recommendation helps you to stay secure. The upgrade workflow at high level is the following: 1. Upgrade a primary control plane node. 1. Upgrade additional control plane nodes. 1. Upgrade worker nodes. ## {{% heading "prerequisites" %}} - Make sure you read the [release notes](https://git.k8s.io/kubernetes/CHANGELOG) carefully. - The cluster should use a static control plane and etcd pods or external etcd. - Make sure to back up any important components, such as app-level state stored in a database. `kubeadm upgrade` does not touch your workloads, only components internal to Kubernetes, but backups are always a best practice. - [Swap must be disabled](https://serverfault.com/questions/684771/best-way-to-disable-swap-in-linux). ### Additional information - The instructions below outline when to drain each node during the upgrade process. If you are performing a \*\*minor\*\* version upgrade for any kubelet, you \*\*must\*\* first drain the node (or nodes) that you are upgrading. In the case of control plane nodes, they could be running CoreDNS Pods or other critical workloads. For more information see [Draining nodes](/docs/tasks/administer-cluster/safely-drain-node/). - The Kubernetes project recommends that you match your kubelet and kubeadm versions. You can instead use a version of kubelet that is older than kubeadm, provided it is within the range of supported versions. For more details, please visit [kubeadm's skew against the kubelet](/docs/setup/production-environment/tools/kubeadm/create-cluster-kubeadm/#kubeadm-s-skew-against-the-kubelet). - All containers are restarted after upgrade, because the container spec hash value is changed. - To verify that the kubelet service has successfully restarted after the kubelet has been upgraded, you can execute `systemctl status kubelet` or view the service logs with `journalctl -xeu kubelet`. - `kubeadm upgrade` supports `--config` with a [`UpgradeConfiguration` API type](/docs/reference/config-api/kubeadm-config.v1beta4) which can be used to configure the upgrade process. - `kubeadm upgrade` does not support reconfiguration of an existing cluster. Follow the steps in [Reconfiguring a kubeadm cluster](/docs/tasks/administer-cluster/kubeadm/kubeadm-reconfigure) instead. ### Considerations when upgrading etcd Because the `kube-apiserver` static pod is running at all times (even if you have drained the node), when you perform a kubeadm upgrade which includes an etcd upgrade, in-flight requests to the server will stall while the new etcd static pod is restarting. As a workaround, it is possible to actively stop the `kube-apiserver` process a few seconds before starting the `kubeadm upgrade apply` command. This permits to complete in-flight requests and close existing connections, and minimizes the consequence of the etcd downtime. This can be done as follows on control plane nodes: ```shell killall -s SIGTERM kube-apiserver # trigger a graceful kube-apiserver shutdown sleep 20 # wait a little bit to
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
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|
upgrade apply` command. This permits to complete in-flight requests and close existing connections, and minimizes the consequence of the etcd downtime. This can be done as follows on control plane nodes: ```shell killall -s SIGTERM kube-apiserver # trigger a graceful kube-apiserver shutdown sleep 20 # wait a little bit to permit completing in-flight requests kubeadm upgrade ... # execute a kubeadm upgrade command ``` ## Changing the package repository If you're using the community-owned package repositories (`pkgs.k8s.io`), you need to enable the package repository for the desired Kubernetes minor release. This is explained in [Changing the Kubernetes package repository](/docs/tasks/administer-cluster/kubeadm/change-package-repository/) document. {{% legacy-repos-deprecation %}} ## Determine which version to upgrade to Find the latest patch release for Kubernetes {{< skew currentVersion >}} using the OS package manager: {{< tabs name="k8s\_install\_versions" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} ```shell # Find the latest {{< skew currentVersion >}} version in the list. # It should look like {{< skew currentVersion >}}.x-\*, where x is the latest patch. sudo apt update sudo apt-cache madison kubeadm ``` {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} For systems with DNF: ```shell # Find the latest {{< skew currentVersion >}} version in the list. # It should look like {{< skew currentVersion >}}.x-\*, where x is the latest patch. sudo yum list --showduplicates kubeadm --disableexcludes=kubernetes ``` For systems with DNF5: ```shell # Find the latest {{< skew currentVersion >}} version in the list. # It should look like {{< skew currentVersion >}}.x-\*, where x is the latest patch. sudo yum list --showduplicates kubeadm --setopt=disable\_excludes=kubernetes ``` {{% /tab %}} {{< /tabs >}} If you don't see the version you expect to upgrade to, [verify if the Kubernetes package repositories are used.](/docs/tasks/administer-cluster/kubeadm/change-package-repository/#verifying-if-the-kubernetes-package-repositories-are-used) ## Upgrading control plane nodes The upgrade procedure on control plane nodes should be executed one node at a time. Pick a control plane node that you wish to upgrade first. It must have the `/etc/kubernetes/admin.conf` file. ### Call "kubeadm upgrade" \*\*For the first control plane node\*\* 1. Upgrade kubeadm: {{< tabs name="k8s\_install\_kubeadm\_first\_cp" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo apt-mark unhold kubeadm && \ sudo apt-get update && sudo apt-get install -y kubeadm='{{< skew currentVersion >}}.x-\*' && \ sudo apt-mark hold kubeadm ``` {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} For systems with DNF: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubeadm-'{{< skew currentVersion >}}.x-\*' --disableexcludes=kubernetes ``` For systems with DNF5: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubeadm-'{{< skew currentVersion >}}.x-\*' --setopt=disable\_excludes=kubernetes ``` {{% /tab %}} {{< /tabs >}} 1. Verify that the download works and has the expected version: ```shell kubeadm version ``` 1. Verify the upgrade plan: ```shell sudo kubeadm upgrade plan ``` This command checks that your cluster can be upgraded, and fetches the versions you can upgrade to. It also shows a table with the component config version states. {{< note >}} `kubeadm upgrade` also automatically renews the certificates that it manages on this node. To opt-out of certificate renewal the flag `--certificate-renewal=false` can be used. For more information see the [certificate management guide](/docs/tasks/administer-cluster/kubeadm/kubeadm-certs). {{}} 1. Choose a version to upgrade to, and run the appropriate command. For example: ```shell # replace x with the patch version you picked for this upgrade sudo kubeadm upgrade apply v{{< skew currentVersion >}}.x ``` Once the command finishes you should see: ``` [upgrade/successful] SUCCESS! Your cluster was upgraded to "v{{<
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
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a version to upgrade to, and run the appropriate command. For example: ```shell # replace x with the patch version you picked for this upgrade sudo kubeadm upgrade apply v{{< skew currentVersion >}}.x ``` Once the command finishes you should see: ``` [upgrade/successful] SUCCESS! Your cluster was upgraded to "v{{< skew currentVersion >}}.x". Enjoy! [upgrade/kubelet] Now that your control plane is upgraded, please proceed with upgrading your kubelets if you haven't already done so. ``` {{< note >}} For versions earlier than v1.28, kubeadm defaulted to a mode that upgrades the addons (including CoreDNS and kube-proxy) immediately during `kubeadm upgrade apply`, regardless of whether there are other control plane instances that have not been upgraded. This may cause compatibility problems. Since v1.28, kubeadm defaults to a mode that checks whether all the control plane instances have been upgraded before starting to upgrade the addons. You must perform control plane instances upgrade sequentially or at least ensure that the last control plane instance upgrade is not started until all the other control plane instances have been upgraded completely, and the addons upgrade will be performed after the last control plane instance is upgraded. {{}} 1. Manually upgrade your CNI provider plugin. Your Container Network Interface (CNI) provider may have its own upgrade instructions to follow. Check the [addons](/docs/concepts/cluster-administration/addons/) page to find your CNI provider and see whether additional upgrade steps are required. This step is not required on additional control plane nodes if the CNI provider runs as a DaemonSet. \*\*For the other control plane nodes\*\* Same as the first control plane node but use: ```shell sudo kubeadm upgrade node ``` instead of: ```shell sudo kubeadm upgrade apply ``` Also calling `kubeadm upgrade plan` and upgrading the CNI provider plugin is no longer needed. ### Drain the node Prepare the node for maintenance by marking it unschedulable and evicting the workloads: ```shell # replace with the name of your node you are draining kubectl drain --ignore-daemonsets ``` ### Upgrade kubelet and kubectl {{< note >}} On Linux nodes, the kubelet defaults to supporting only cgroups v2. For Kubernetes {{< skew currentVersion >}} the `FailCgroupV1` kubelet configuration option is set to `true` by default. To learn more, refer to the [Kubernetes cgroup v1 deprecation documentation](/docs/concepts/architecture/cgroups/#deprecation-of-cgroup-v1). {{}} 1. Upgrade the kubelet and kubectl: {{< tabs name="k8s\_install\_kubelet" >}} {{% tab name="Ubuntu, Debian or HypriotOS" %}} ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo apt-mark unhold kubelet kubectl && \ sudo apt-get update && sudo apt-get install -y kubelet='{{< skew currentVersion >}}.x-\*' kubectl='{{< skew currentVersion >}}.x-\*' && \ sudo apt-mark hold kubelet kubectl ``` {{% /tab %}} {{% tab name="CentOS, RHEL or Fedora" %}} For systems with DNF: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubelet-'{{< skew currentVersion >}}.x-\*' kubectl-'{{< skew currentVersion >}}.x-\*' --disableexcludes=kubernetes ``` For systems with DNF5: ```shell # replace x in {{< skew currentVersion >}}.x-\* with the latest patch version sudo yum install -y kubelet-'{{< skew currentVersion >}}.x-\*' kubectl-'{{< skew currentVersion >}}.x-\*' --setopt=disable\_excludes=kubernetes ``` {{% /tab %}} {{< /tabs >}} 1. Restart the kubelet: ```shell sudo systemctl daemon-reload sudo systemctl restart kubelet ``` ### Uncordon the node Bring the node back online by marking it schedulable: ```shell # replace with the name of your node kubectl uncordon ``` ## Upgrade worker nodes The upgrade procedure on worker nodes should be executed one node at a time or few nodes at a time, without compromising the minimum required capacity for running your workloads. The following pages show how to upgrade Linux and Windows worker nodes:
| null |
./vendor/kubernetes/content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade.md
|
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] | 0.038717
|
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