cwielenb/CNCF-Dataset huggingface dataset:
Project: Gloo (Orchestration & Management / API Gateway)
File: typed_struct.proto.sk.md

title: "typed_struct.proto" weight: 5 <!-- Code generated by solo-kit. DO NOT EDIT. --> A TypedStruct contains an arbitrary JSON serialized protocol buffer message with a URL that describes the type of the serialized message. This is very similar to google.protobuf.Any, instead of having protocol buffer binary, this employs google.protobuf.Struct as value. This message is intended to be embedded inside Any, so it shouldn't be directly referred from other UDPA messages. When packing an opaque extension config, packing the expected type into Any is preferred wherever possible for its efficiency. TypedStruct should be used only if a proto descriptor is not available, for example if: A control plane sends opaque message that is originally from external source in human readable format such as JSON or YAML. The control plane doesn't have the knowledge of the protocol buffer schema hence it cannot serialize the message in protocol buffer binary format. The DPLB doesn't have have the knowledge of the protocol buffer schema its plugin or extension uses. This has to be indicated in the DPLB capability negotiation. When a DPLB receives a TypedStruct in Any, it should: Check if the type_url of the TypedStruct matches the type the extension expects. Convert value to the type described in type_url and perform validation. TODO(lizan): Figure out how TypeStruct should be used with DPLB extensions that doesn't link protobuf descriptor with DPLB itself, (e.g. gRPC LB Plugin, Envoy WASM extensions). ```yaml "typeUrl": string "value": .google.protobuf.Struct ``` | Field | Type | Description | | -- | - | -- | | `typeUrl` | `string` | A URL that uniquely identifies the type of the serialize protocol buffer message. This has same semantics and format described in google.protobuf.Any: https://github.com/protocolbuffers/protobuf/blob/master/src/google/protobuf/any.proto. | | `value` | | A JSON representation of the above specified type. | <!-- Start of HubSpot Embed Code --> <script type="text/javascript" id="hs-script-loader" async defer src="//js.hs-scripts.com/5130874.js"></script> <!-- End of HubSpot Embed Code -->
Project: KubeStellar (Orchestration & Management / Scheduling & Orchestration)
File: mvi.md

Medium - <br/> <p align=center> <div id="spinner1"> <img width="140" height="140" src="../../../images/spinner.gif" class="centerImage"> </div> <iframe class="centerImage" id="embed1" width="0" height="0" src="https://www.youtube.com/embed/5P8O4bxHvKw?controls=0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen style="visibility:hidden;" onload= "document.getElementById('spinner1').style.display='none';document.getElementById('embed1').style.visibility='visible';document.getElementById('embed1').width='720';document.getElementById('embed1').height='400';"></iframe> </p> to create this document <p align=center> <div id="spinner1"> <img width="140" height="140" src="../../../images/spinner.gif" class="centerImage"> </div> <iframe class="centerImage" id="embed2" src="https://www.linkedin.com/embed/feed/update/urn:li:share:7076627464424189953" scrolling=no height="0" width="0" frameborder="0" allowfullscreen="" title="Embedded post" style="visibility:hidden;" onload= "document.getElementById('spinner1').style.display='none';document.getElementById('embed2').style.visibility='visible';document.getElementById('embed2').width='740';document.getElementById('embed2').height='400';"></iframe> </p> <p align=center> <div id="spinner2"> <img width="140" height="140" src="../../../images/spinner.gif" class="centerImage"> </div> <iframe class="centerImage" id="embed2" src="https://www.linkedin.com/embed/feed/update/urn:li:share:7076651072211013632" scrolling=no height="0" width="0" frameborder="0" allowfullscreen="" title="Embedded post" style="visibility:hidden;" onload= "document.getElementById('spinner2').style.display='none';document.getElementById('embed2').style.visibility='visible';document.getElementById('embed2').width='740';document.getElementById('embed2').height='400';"></iframe> </p> <style type="text/css"> .centerImage { display: block; margin: auto; } </style>
Project: Karmada (Orchestration & Management / Scheduling & Orchestration)
File: bug-report.md

name: Bug Report about: Report a bug encountered while using Karmada. labels: kind/bug <!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks! --> What happened: What you expected to happen: How to reproduce it (as minimally and precisely as possible): Anything else we need to know?: Environment: Karmada version: kubectl-karmada or karmadactl version (the result of `kubectl-karmada version` or `karmadactl version`): Others:
Project: Gloo (Orchestration & Management / API Gateway)
File: retries.proto.sk.md

title: "retries.proto" weight: 5 <!-- Code generated by solo-kit. DO NOT EDIT. --> This specifies the retry policy interval for backoffs. Note that if the base interval provided is larger than the maximum interval OR if any of the durations passed are <= 0 MS, there will be an error. ```yaml "baseInterval": .google.protobuf.Duration "maxInterval": .google.protobuf.Duration ``` | Field | Type | Description | | -- | - | -- | | `baseInterval` | | Specifies the base interval for a retry. | | `maxInterval` | | Specifies the max interval for a retry. | Retry Policy applied at the Route and/or Virtual Hosts levels. ```yaml "retryOn": string "numRetries": int "perTryTimeout": .google.protobuf.Duration "retryBackOff": .retries.options.gloo.solo.io.RetryBackOff ``` | Field | Type | Description | | -- | - | -- | | `retryOn` | `string` | Specifies the conditions under which retry takes place. These are the same conditions . | | `numRetries` | `int` | Specifies the allowed number of retries. This parameter is optional and defaults to 1. These are the same conditions . | | `perTryTimeout` | | Specifies a non-zero upstream timeout per retry attempt. This parameter is optional. | | `retryBackOff` | | Specifies the retry policy interval. | <!-- Start of HubSpot Embed Code --> <script type="text/javascript" id="hs-script-loader" async defer src="//js.hs-scripts.com/5130874.js"></script> <!-- End of HubSpot Embed Code -->
Project: Capsule (Orchestration & Management / Scheduling & Orchestration)
File: GOVERNANCE.md

This document lays out the guidelines under which the Capsule project will be governed. The goal is to make sure that the roles and responsibilities are well defined and clarify how decisions are made. In the context of Capsule project, we consider the following roles: Users: everyone using Capsule, typically willing to provide feedback by proposing features and/or filing issues. Contributors: everyone contributing code, documentation, examples, tests, and participating in feature proposals as well as design discussions. Maintainers: are responsible for engaging with and assisting contributors to iterate on the contributions until it reaches acceptable quality. Maintainers can decide whether the contributions can be accepted into the project or rejected. The release process will be governed by Maintainers. Please, refer to the available in the source code. Maintainers will share roadmap and release versions as milestones in GitHub.
Project: Volcano (Orchestration & Management / Scheduling & Orchestration)
File: adopters.md

Below are the adopters of project Volcano. If you are using Volcano to improve scheduling or job management in AI/ML, big-data, etc, please feel free to add yourself into the following list by a pull request. There're several phases as follow: Evaluation:* Known Volcano, that's interesting; evaluating the features/scopes of Volcano Testing:* Take Volcano as one of candidates, testing Kubernetes cluster with Volcano Staging:* Decide to use Volcano, testing it in pre-product environment Production:* Already put Volcano into product environment | Organization | Contact | Environment | Description of Use | | | - | -- | | | || Production | Scheduler & Job Management of AI Container Service and service | | || Production | Production in AI Platform | | || Production | Scheduler for Deep Learning Platform to Optimize Performance | | | | Production | Scheduler & Job Management for Deep Learning platform on K8s | | | , | Production | Batch system for internal machine learning platform | | | | Production | Tensorflow on K8s | | | | Production | Batch system for Distributed Deep Learning platform on K8s | | | | Production | Batch system for Distributed AI platform on K8s | | | | Production | Work as part of Leinao OS | | | | Production | Batch system for AI platform on K8s | | || Evaluation | Spark on K8S | | || Evaluation | Scientific calculations in physics, materials , biology and chemistry. molecular dynamics simulation. | | || Evaluation | Evaluation in ATLAS AI Platform | | | | Evaluation | Spark on K8s | | | | Evaluation | Scheduler for Vtraining (deep learning training platform) | | || Evaluation | Infrastructure of Hanwell (Huawei Cloud backend of Cromwell which is a Broad Institute implementation of WDL) | | |, | Evaluation | spark scheduler of our next cloud native product. | | | | Evaluation | Spark and AI on K8S. | | | | Staging | Ray on K8s. |
Project: Apache bRPC (Orchestration & Management / Remote Procedure Call)
File: dummy_server.md

If your program only uses client in brpc or doesn't use brpc at all, but you also want to use built-in services in brpc. The thing you should do is to start an empty server, which is called dummy server. Create a file named dummy_server.port which contains a port number(such as 8888) in the running directory of program, a dummy server would be started at this port. All of the bvar in the same process can be seen by visiting its built-in service. You must manually add the dummy server. First read to learn how to download and compile brpc, and then add the following code snippet at the program entry: ```c++ ... int main() { ... brpc::StartDummyServerAt(8888/port/); ... } ```
Project: CoreDNS (Orchestration & Management / Coordination & Service Discovery)
File: coredns-1.8.7.md

+++ title = "CoreDNS-1.8.7 Release" description = "CoreDNS-1.8.7 Release Notes." tags = ["Release", "1.8.7", "Notes"] release = "1.8.7" date = "2021-12-09T00:00:00+00:00" author = "coredns" +++ This is a release with bug fixes and some new features added. We now enable HTTP/2 in gRPC service (https://github.com/coredns/coredns/pull/4842). The shuffling algorithm in loadbalance plugin has also been improved to have a more consistent behavior (https://github.com/coredns/coredns/pull/4961). This release will also log deprecation warnings when wildcard queries are received by kubernetes. The wildcard functionality will be completely removed from kubernetes plugin in future releases. Chris O'Haver, Christian Ang, Cyb3r Jak3, Denis Tingaikin, gomakesix, Hu Shuai, Humberto Leal, jayonlau, Johnny Bergstrm, LiuCongran, Matt Palmer, Miek Gieben, OctoHuman, Ondej Benkovsk, Pavol Lieskovsk, Vector, Wu Shuang, xuweiwei, xww, Yong Tang, ZhangJian He, Zou Nengren core: Support plain HTTP for DoH (https://github.com/coredns/coredns/pull/4997) plugin/auto: Fix panic caused by config invalid reload value (https://github.com/coredns/coredns/pull/4986) plugin/cache: fix data race (https://github.com/coredns/coredns/pull/4932) plugin/file: Fix print tree error (https://github.com/coredns/coredns/pull/4962) plugin/file: Fix issue of multiple file plugin have same reload time (https://github.com/coredns/coredns/pull/5020) plugin/forward: Use new msg.Id for upstream queries (https://github.com/coredns/coredns/pull/4841) plugin/grpc: Enable HTTP/2 in gRPC service (https://github.com/coredns/coredns/pull/4842) plugin/k8s_external: Fix SRV queries doesn't work with AWS ELB/NLB (https://github.com/coredns/coredns/pull/4929) plugin/kubernetes: Add wildcard warnings (https://github.com/coredns/coredns/pull/5030) plugin/loadbalance: More consistent shuffling (https://github.com/coredns/coredns/pull/4961) plugin/metrics: Support HTTPS qType in requests count metric label (https://github.com/coredns/coredns/pull/4934) plugin/metrics: Expand corednsdnsresponses_total with plugin label (https://github.com/coredns/coredns/pull/4914) plugin/route53: Configurable AWS Endpoint (https://github.com/coredns/coredns/pull/4963)
Project: DolphinScheduler (Orchestration & Management / Scheduling & Orchestration)
File: task-group.md

The task group is mainly used to control the concurrency of task instances, and is designed to control the pressure of other resources (it can also control the pressure of the Hadoop cluster, the cluster will have queue control it). When creating a new task definition, you can configure the corresponding task group and configure the priority of the task running in the task group. The user can only view the task groups belongs to authorized projects, and can create or update task groups belongs to one project only if they have write permission. Note: The task group's resource restrictions are on the project level and unrelated to tenants. The user clicks `Resources -> Task Group Management -> Task Group option -> Create Task Group` You need to enter the information inside the picture: Task group name: The name displayed when the task group is used Project name: The project that the task group functions, this item is optional, if not selected, all the projects in the whole system can use this task group. Resource pool size: The maximum number of concurrent task instances allowed. Click the button to view task group usage information: Note: The use of task groups is applicable to tasks executed by workers, such as `switch` nodes, `condition` nodes, `sub_process` and other node types executed by the master are not controlled by the task group. Let's take the shell node as an example: Regarding the configuration of the task group, all you need to do is to configure these parts in the red box: Task group name: The task group name is displayed on the task group configuration page. Here you can only see the task group that the project has permission to access (the project is selected when creating a task group) or the task group that scope globally (no project is selected when creating a task group). Priority: When there is a waiting resource, the task with high priority will be distributed to the worker by the master first. The larger the value of this part, the higher the priority. The master judges whether the task is configured with a task group when distributing the task. If the task is not configured, it is normally thrown to the worker to run; if a task group is configured, it checks whether the remaining size of the task group resource pool meets the current task operation before throwing it to the worker for execution. , if the resource pool -1 is satisfied, continue to run; if not, exit the task distribution and wait for other tasks to wake up. When the task that has occupied the task group resource is finished, the task group resource will be released. After the release, it will check whether there is a task waiting in the current task group. If there is, mark the task with the best priority to run, and create a new executable event. The event stores the task ID that is marked to acquire the resource, and then the task obtains the task group resource and run.
Project: Gloo (Orchestration & Management / API Gateway)
File: csrf.proto.sk.md

title: "csrf.proto" weight: 5 <!-- Code generated by solo-kit. DO NOT EDIT. --> copied from https://github.com/envoyproxy/envoy/blob/main/api/envoy/extensions/filters/http/csrf/v3/csrf.proto CSRF filter config. ```yaml "filterEnabled": .solo.io.envoy.config.core.v3.RuntimeFractionalPercent "shadowEnabled": .solo.io.envoy.config.core.v3.RuntimeFractionalPercent "additionalOrigins": []solo.io.envoy.type.matcher.v3.StringMatcher ``` | Field | Type | Description | | -- | - | -- | | `filterEnabled` | | Specifies the % of requests for which the CSRF filter is enabled. If :ref:`runtimekey <envoyapifieldconfig.core.v3.RuntimeFractionalPercent.runtimekey>` is specified, Envoy will lookup the runtime key to get the percentage of requests to filter. .. note:: This field defaults to 100/:ref:`HUNDRED <envoyapienumtype.v3.FractionalPercent.DenominatorType>`. | | `shadowEnabled` | | Specifies that CSRF policies will be evaluated and tracked, but not enforced. This is intended to be used when ``filterenabled`` is off and will be ignored otherwise. If :ref:`runtimekey <envoyapifieldconfig.core.v3.RuntimeFractionalPercent.runtimekey>` is specified, Envoy will lookup the runtime key to get the percentage of requests for which it will evaluate and track the request's Origin and Destination to determine if it's valid, but will not enforce any policies. | | `additionalOrigins` | | Specifies additional source origins that will be allowed in addition to the destination origin. More information on how this can be configured via runtime can be found :ref:`here <csrf-configuration>`. | <!-- Start of HubSpot Embed Code --> <script type="text/javascript" id="hs-script-loader" async defer src="//js.hs-scripts.com/5130874.js"></script> <!-- End of HubSpot Embed Code -->
Project: SRPC (Orchestration & Management / Remote Procedure Call)
File: docs-02-service.md

It is the basic unit for SRPC services. Each service must be generated by one type of IDLs. Service is determined by IDL type, not by specific network communication protocol. You can follow the detailed example below: Use the same `example.proto` IDL above. Run the official `protoc example.proto --cppout=./ --protopath=./` to get two files: `example.pb.h` and `example.pb.cpp`. Run the `srpc_generator protobuf ./example.proto ./` in SRPC to get `example.srpc.h`. Derive `Example::Service` to implement the rpc business logic, which is an RPC Service. Please note that this Service does not involve any concepts such as network, port, communication protocol, etc., and it is only responsible for completing the business logic that convert `EchoRequest` to `EchoResponse`. ~~~cpp class ExampleServiceImpl : public Example::Service { public: void Echo(EchoRequest request, EchoResponse response, RPCContext *ctx) override { response->set_message("Hi, " + request->name()); printf("getreq:\n%s\nsetresp:\n%s\n", request->DebugString().c_str(), response->DebugString().c_str()); } }; ~~~
Project: gRPC (Orchestration & Management / Remote Procedure Call)
File: qos-dscp.md

Differentiated services or DiffServ is a mechanism for classifying network traffic and providing quality of service on IP networks. DiffServ uses dedicated fields in the IP header for packet classification purposes. By marking outgoing packets using a Differentiated Services Code Point (DSCP) the network can prioritize accordingly. The DSCP value on outgoing packets is controlled by the following channel argument: GRPC_ARG_DSCP* This channel argument accepts integer values 0 to 63. See for details. Default value is to use system default, i.e. not set. Only apply to POSIX systems.
Project: Kusk Gateway (Orchestration & Management / API Gateway)
File: kusk_completion_bash.md

Generate the autocompletion script for bash Generate the autocompletion script for the bash shell. This script depends on the 'bash-completion' package. If it is not installed already, you can install it via your OS's package manager. To load completions in your current shell session: source <(kusk completion bash) To load completions for every new session, execute once: kusk completion bash > /etc/bash_completion.d/kusk kusk completion bash > $(brew --prefix)/etc/bash_completion.d/kusk You will need to start a new shell for this setup to take effect. ``` kusk completion bash ``` ``` -h, --help help for bash --no-descriptions disable completion descriptions ``` ``` --config string config file (default is $HOME/.kusk.yaml) ``` - Generate the autocompletion script for the specified shell
Project: k8gb (Orchestration & Management / Coordination & Service Discovery)
File: rancher.md

The K8gb has been modified to be easily deployed using . All you need to supply is a file and possibly expose the labels on your cluster. The following shows the rancher application that will be installed on the target cluster. The values `k8gb-dnsZone`, `k8gb-clusterGeoTag`, `k8gb-extGslbClustersGeoTags` will be taken from the labels that are set on the cluster. ```yaml defaultNamespace: k8gb kustomize: dir: overlays/kustomization labels: bundle: k8gb helm: repo: https://www.k8gb.io chart: k8gb version: v0.11.4 releaseName: k8gb values: k8gb: dnsZone: global.fleet.clusterLabels.k8gb-dnsZone edgeDNSZone: "cloud.example.com" edgeDNSServers: "1.2.3.4" "5.6.7.8" clusterGeoTag: global.fleet.clusterLabels.k8gb-clusterGeoTag extGslbClustersGeoTags: global.fleet.clusterLabels.k8gb-extGslbClustersGeoTags log: format: simple ```
Project: BFE (Orchestration & Management / Service Proxy)
File: server_cert_conf.data.md

servercertconf.data records the config for server certificate and private key | Config Item | Description | | -- | | | Version | String<br>Version of configure file | | Config | Object<br>Server certificate configuration information | | Config.Default | String<br>Name of default cert <br>- Default cert must be configured <br>- Default cert must be included in cert list {CertConf} | | Config.CertConf | Object<br>Cert list | | Config.CertConf{k} | String<br>Name of cert <br>- Cert name can not be "BFEDEFAULTCERT" | | Config.CertConf{v} | Object<br>Cert related file path | | Config.CertConf{v}.ServerCertFile | String<br>Path of server certificate | | Config.CertConf{v}.ServerKeyFile | String<br>Path of private key | | Config.CertConf{v}.OcspResponseFile | String<br>Path of OCSP Stple (optional) | ```json { "Version": "20190101000000", "Config": { "Default": "example.org", "CertConf": { "example.org": { "ServerCertFile": "tls_conf/certs/server.crt", "ServerKeyFile" : "tls_conf/certs/server.key" } } } } ```
Project: Prefect (Orchestration & Management / Scheduling & Orchestration)
File: SECURITY.md

To report a (suspected) security issue, please email `bugbounty@prefect.io` and follow the instructions for our . Prefect will acknowledge receipt of your report in a timely manner, usually within 48 hours. After the initial reply to your report, the security team will keep you informed of the progress towards a fix and full announcement, and may ask for additional information or guidance.
Project: Apache Mesos (Orchestration & Management / Scheduling & Orchestration)
File: grpc.md

https://github.com/grpc/grpc ```sh git clone -b v<version> https://github.com/grpc/grpc.git grpc-<version> (cd grpc-<version> && git submodule update --init third_party/cares) tar zcvf grpc-<version>.tar.gz --exclude .git grpc-<version> ``` We bundle 1.11.1 for better CMake build support, and s390x support. Upstream PR: https://github.com/grpc/grpc/pull/15128 Upstream PR: https://github.com/grpc/grpc/pull/16323 Upstream PR: https://github.com/grpc/grpc/pull/17726
Project: Gloo (Orchestration & Management / API Gateway)
File: grpc_output_sink.proto.sk.md

title: "grpcoutputsink.proto" weight: 5 <!-- Code generated by solo-kit. DO NOT EDIT. --> GRPC output sink definition ```yaml "grpcService": .solo.io.envoy.config.core.v3.GrpcService ``` | Field | Type | Description | | -- | - | -- | | `grpcService` | | Location of the GRPC service to which output traces should be submitted. | <!-- Start of HubSpot Embed Code --> <script type="text/javascript" id="hs-script-loader" async defer src="//js.hs-scripts.com/5130874.js"></script> <!-- End of HubSpot Embed Code -->