vania-janet/multiturn-rag-retrieval-data huggingface dataset:
initContainers:
- command:
- sh
- -c
- sysctl -e -w net.ipv4.tcp_keepalive_time=40; sysctl -e -w net.ipv4.tcp_keepalive_intvl=15; sysctl -e -w net.ipv4.tcp_keepalive_probes=6;
image: us.icr.io/armada-master/alpine:latest
imagePullPolicy: IfNotPresent
name: sysctl-init
resources: {}
securityContext:
privileged: true
containers:
- name: test-sysctl
image: us.icr.io/armada-master/alpine:latest
command: ["sleep", "2592000"]
EOF

Show more





 Adjusting cluster metrics provider resources 

Your cluster has a metrics service provided by the metrics-server deployment in the kube-system namespace. The metrics-server resource requests are based on the number of nodes in the cluster and are optimized for clusters with 30 or less pods per worker node. The metric service matches the memory and CPU limits of the resource requests.

The metrics-service containers can be "out-of-memory killed" if the memory requests are too low. They might respond very slowly or fail liveness and readiness probes, due to CPU throttling if the CPU requests are too low.

Memory use is driven by the number of pods in the cluster. CPU use is driven by the number of requests for metrics (HPAs, kubectl top nodes / pods, and so on) and by API discovery requests. The metrics-server provides a Kubernetes API, so that clients such as kubectl that use API discovery place some load on the metrics-server even if they don't use metrics.

The following symptoms might indicate a need to adjust the metrics-server resources:

- The metrics-server is restarting frequently.
Before you use the the CLI to manage IBM Cloud Metrics Routing account settings, [Install the IBM Cloud Metrics Routing CLI](https://cloud.ibm.com/docs/metrics_router?topic=metrics_router-metrics_router-cli-config).

Check that you have IAM permissions to read, update, or both the IBM Cloud Metrics Routing account settings.





 Getting account settings using the CLI 

Use this command to get the settings for the IBM Cloud Metrics Routing account configurations.

ibmcloud metrics-router setting get [--output FORMAT]



 Command options 

--output FORMAT
: If JSON is specified, output will be returned in JSON format. If JSON is not specified, output will be returned in a tabular format.

help | --help | -h
: List options available for the command.





 Example 

The following is an example where no default or permitted targets have been set.

Primary metadata region: us-east
Backup metadata region: -
Default targets: []
Permitted target regions: []
Private api endpoint only: false







 Updating settings using the CLI 

Use this command to modify current account settings such as the default targets, permitted target regions, and the primary metadata region.

ibmcloud metrics-router setting update [--primary-metadata-region REGION] [--backup-metadata-region REGION] [--private-api-endpoint-only ( TRUE | FALSE )] [--default-targets TARGET] [--permitted-target-regions REGIONS] [--output FORMAT] [--force]



 Command options 

primary-metadata-region
: Specify the REGION where the metadata associated with route and target definitions is stored.

backup-metadata-region
: Specify the REGION where the metadata associated with route and target definitions is stored as a backup.

private-api-endpoint-only
: Specifies whether nor not a private endpoint can be used. If TRUE only a private endpoint can be used.

default-targets
: Is a list of target IDs.
Later on, you can use these tags to identify metrics from the environment where the agent is running.
* The sysdig_capture_enabled is set to false to disable the capture feature. By default this is set to true. For more information, see [Working with captures](https://cloud.ibm.com/docs/monitoring?topic=monitoring-capturescaptures).
* The secure flag must be set to true to use a secure SSL/TLS connection to send metrics to the collector.



If the monitoring agent fails to install correctly, install the kernel headers manually. Choose a distribution and run the command for that distribution. Then, retry the deployment of the monitoring agent.



* For Debian and Ubuntu Linux distributions, run the following command:

apt-get -y install linux-headers-$(uname -r)
* For RHEL, CentOS, and Fedora Linux distributions, run the following command:

yum -y install kernel-devel-$(uname -r)



6. Configure the agent for non-orchestrated environments.

Open the dragent.yaml file that is located in /opt/draios/etc/.

Add the following configuration parameter:

feature:
mode: monitor_light

Restart the agent. Run the following command:

service dragent restart







 Step 4: Launch the monitoring UI 

Complete the following steps to launch the web UI:



1. [Log in to your IBM Cloud account](https://cloud.ibm.com/login).

After you log in with your user ID and password, the IBM Cloud Dashboard opens.
2. In the navigation menu, select Observability.
3. Select Monitoring.

The list of instances that are available on IBM Cloud is displayed.
4. Select your instance. Then, click Open dashboard.



IIt may take some time before you see the server entry while the information is initally collected and processed by the monitoring agent.

You only can monitor one instance per browser. You could have multiple tabs for the same instance.
Updated support of ephemeral storage for apps and jobs
: Code Engine adds support for setting ephemeral storage for apps and jobs in the console. Added validation checks for ephemeral storage to clarify the relationship between ephemeral storage and memory. Ephemeral storage is bounded by the configured memory.



* See [Limits and quotas for Code Engine](https://cloud.ibm.com/docs/codeengine?topic=codeengine-limits).
* See [Supported memory and CPU combinations](https://cloud.ibm.com/docs/codeengine?topic=codeengine-mem-cpu-combo).



Updated versions for buildpacks
: See [Choosing a build strategy](https://cloud.ibm.com/docs/codeengine?topic=codeengine-plan-buildbuild-strategy).





 20 October 2022 

CLI version 1.39.6 released
: See [CLI version history](https://cloud.ibm.com/docs/codeengine?topic=codeengine-cli_versions).

Revised and improved descriptions of metrics for monitoring Code Engine
: See [Monitoring for Code Engine](https://cloud.ibm.com/docs/codeengine?topic=codeengine-monitor).

Updated versions for buildpacks
: See [Choosing a build strategy](https://cloud.ibm.com/docs/codeengine?topic=codeengine-plan-buildbuild-strategy).





 17 October 2022 

Updated versions for buildpacks
: See [Choosing a build strategy](https://cloud.ibm.com/docs/codeengine?topic=codeengine-plan-buildbuild-strategy).





 06 October 2022 

CLI version 1.39.5 released
: See [CLI version history](https://cloud.ibm.com/docs/codeengine?topic=codeengine-cli_versions).

Updated versions for buildpacks
Kubernetes Metrics Server v0.3.1 v0.3.3 See the [Kubernetes Metrics Server release notes](https://github.com/kubernetes-sigs/metrics-server/releases/tag/v0.3.3). 
 Trusted compute agent 13c7ef0 e8c6d72 Updated image for [CVE-2018-10844](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10844), [CVE-2018-10845](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10845), [CVE-2018-10846](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10846), [CVE-2019-3829](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3829), [CVE-2019-3836](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3836), [CVE-2019-9893](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-9893), [CVE-2019-5435](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5435), and [CVE-2019-5436](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5436). 







 Change log for worker node fix pack 1.12.8_1553, released 20 May 2019 

The following table shows the changes that are in the patch 1.12.8_1553.



Changes since version 1.12.8_1553
Use Smart Document Understanding (SDU) to improve search results 

In this tutorial, you use the Smart Document Understanding feature of the Discovery service to create a user-trained Smart Document Understanding (SDU) model. You then split a single document into many smaller documents so that some types of answers are easier to find.

This tutorial works with both managed and installed deployments.



 Learning objectives 

By the time you finish the tutorial, you will understand how to:



* Create a Document Retrieval project in Discovery.
* Upload a PDF document to your Discovery project.
* Use the Smart Document Understanding (SDU) tool to create a user-trained SDU model.
* Split a document into smaller, more consumable chunks.





 Duration 

This tutorial takes approximately 3 hours to complete.





 Prerequisite 



1. Before you begin, you must set up a paid account with IBM Cloud.

You can complete this tutorial at no cost by using a Plus plan, which offers a 30-day trial at no cost. However, to create a Plus plan instance of the service, you must have a paid account (where you provide credit card details). For more information about creating a paid account, see [Upgrading your account](https://cloud.ibm.com/docs/account?topic=account-upgrading-account).
2. Create a Plus plan Discovery service instance.

Go to the [Discovery resource](https://cloud.ibm.com/catalog/services/watson-discovery) page in the IBM Cloud catalog and create a Plus plan service instance.



If you decide to stop using the Plus plan and don't want to pay for it, delete the Plus plan service instance before the 30-day trial period ends.







 Step 1: Create the Document Retrieval project 

Create a project. Choose to create a Document Retrieval project type. This type is optimized for finding answers that are returned as passages from large documents.

For more information about project types, see [Creating projects](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-projects).



1. From the Discovery Plus plan service page in IBM Cloud, click Launch Discovery.
[Platform metrics](https://cloud.ibm.com/docs/data-virtualization?topic=data-virtualization-monitor) 
 [IBM® Db2® on Cloud](https://cloud.ibm.com/docs/Db2onCloud?topic=Db2onCloud-about) IBM Db2 on Cloud is a fully managed public cloud service on IBM Cloud. As a relational database, it delivers fast query processing with enterprise-level performance and capabilities for online transactional processing (OLTP). [Platform metrics](https://cloud.ibm.com/docs/Db2onCloud?topic=Db2onCloud-monitor) 







 Developer tools 

The following table lists developer tools and DevOps services that are enabled for IBM Cloud Monitoring:



Table 4. List of developer tools and DevOps services

 Service Description Metrics 

 [IBM Cloud® Continuous Delivery](https://cloud.ibm.com/docs/ContinuousDelivery?topic=ContinuousDelivery-getting-started) With Continuous Delivery, you can build, test, and deliver applications by using DevOps practices and industry-leading tools. [Platform metrics](https://cloud.ibm.com/docs/ContinuousDelivery?topic=ContinuousDelivery-cd-monitor-sysdig) 
 [IBM Cloud® App Configuration](https://cloud.ibm.com/docs/app-configuration?topic=app-configuration-getting-started) Instrument your applications with App Configuration SDKs, and use the App Configuration dashboard or App Configuration administrator API to define features flags or properties. [Platform metrics](https://cloud.ibm.com/docs/app-configuration?topic=app-configuration-ac-monitoring) 
 [IBM Cloud® Event Notifications](https://cloud.ibm.com/docs/event-notifications?topic=event-notifications-getting-started) A centralized alerts management service that notifies and alerts you to events occurring in your IBM Cloud account. [Platform metrics](https://cloud.ibm.com/docs/event-notifications?topic=event-notifications-en-monitoring) 







 Integration services
Kubernetes Metrics Server v0.3.1 v0.3.3 See the [Kubernetes Metrics Server release notes](https://github.com/kubernetes-sigs/metrics-server/releases/tag/v0.3.3). 
 Trusted compute agent 13c7ef0 e8c6d72 Updated image for [CVE-2018-10844](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10844), [CVE-2018-10845](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10845), [CVE-2018-10846](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10846), [CVE-2019-3829](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3829), [CVE-2019-3836](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3836), [CVE-2019-9893](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-9893), [CVE-2019-5435](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5435), and [CVE-2019-5436](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5436). 







 Change log for worker node fix pack 1.13.6_1522, released 20 May 2019 

The following table shows the changes that are in the patch 1.13.6_1522.



Table 1.
Kubernetes Metrics Server v0.3.1 v0.3.3 See the [Kubernetes Metrics Server release notes](https://github.com/kubernetes-sigs/metrics-server/releases/tag/v0.3.3). 
 Trusted compute agent 13c7ef0 e8c6d72 Updated image for [CVE-2018-10844](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10844), [CVE-2018-10845](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10845), [CVE-2018-10846](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-10846), [CVE-2019-3829](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3829), [CVE-2019-3836](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-3836), [CVE-2019-9893](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-9893), [CVE-2019-5435](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5435), and [CVE-2019-5436](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-5436). 







 Change log for worker node fix pack 1.14.1_1519, released 20 May 2019 

The following table shows the changes that are in the patch 1.14.1_1519.



Table 1.
: The CRN service name of an [IBM Cloud service that generates metrics managed through [IBM Cloud Metrics Routing](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-cloud-services-mr)

service_instance, resource_type, and resource
: Values appropriate to an [IBM Cloud service that generates metrics managed through [IBM Cloud Metrics Routing](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-cloud-services-mr)

--rules RULES
: A JSON formatted rule definition enclosed in single quotation marks. For example,

--rules '[{"action": "send", "targets":{"id": "11111111-1111-1111-1111-111111111111"}], "inclusion_filters":{"operand": "location","operator": "is","values": "us-south"]}]}]

Where targets is a comma-separated list of target IDs.

The rule definition can optionally also include inclusion filters. For example,

[{
"action": "send",
"targets": {
"id":"11111111-1111-1111-1111-111111111111"
}],
"inclusion_filters":
{
"operand": "service_name",
"operator": "in",
"values":
"appconnect",
"cloudant",
"containers-kubernetes"
]
},
{
"operand": "location",
"operator": "in",
"values":
"us-south",
"eu-de"
]
}
]
}]
Show more

Where:

action
: Action defines whether IBM Cloud® Metrics Routing includes or excludes metrics on the route. Two actions are supported: send and drop.
Error from server: Get “https://10.38.193.213:10250/containerLogs/kube-system/metrics-server-65fc69c6b7-f682d/metrics-server”: EOF

kubectl -n kube-system exec -it metrics-server-65fc69c6b7-f682d -c metrics-server -- sh
Error from server: error dialing backend: EOF

 How to fix it 

Review and complete the following the steps for your cluster version.

Kubernetes version 1.21 and later
: The Konnectivity VPN connection between the master node and worker nodes is not functioning properly.



* The cluster has both private and public service endpoints enabled.
* Service endpoints or VRF are not enabled in the account.



To determine if VRF and service endpoints are enabled in your account, run ibmcloud account show. Look for the following output.

VRF Enabled: true
Service Endpoint Enabled: true

To determine if your classic cluster has both public and private service endpoint enabled, run ibmcloud ks cluster get -c <cluster_id>. Look for output similar to the following.

Public Service Endpoint URL: https://c105.<REGION>.containers.cloud.ibm.com:<port>
Private Service Endpoint URL: https://c105.private.<REGION>.containers.cloud.ibm.com:<port>

If your cluster meets these conditions, [enable service endpoints and VRF](https://cloud.ibm.com/docs/account?topic=account-vrf-service-endpoint&interface=uivrf) for the account.
In the bare metal server, from the shh session, change to the directory /opt/draios/etc/. Run the following command:

cd /opt/draios/etc/
2. Update the /opt/draios/etc/dragent.yaml.

Append the following section to the dragent.yaml file:

prometheus:
enabled: true
interval: 30
log_errors: true
max_metrics: 3000
max_metrics_per_process: 3000
max_tags_per_metric: 20
process_filter:
- include:
port: 9090
conf:
port: 9090
path: "/metrics"
- include:
port: 9290
conf:
port: 9290
path: "/metrics"
Show more
3. Restart the monitoring agent. Run the following command:

service dragent restart









 Step 5: Verify that you can see the prometheus ipmi metrics 

Complete the following steps:



1. Click the Menu icon ![Menu icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/images/icon_hamburger.svg) > Observability.
2. Select Monitoring.
3. Identify the monitoring instance that you created. Then, click Open dashboard.
4. In the Explore view, select Hosts and Containers. Then, select the bare metal server that you want to monitor.

Zoom

![Hosts and Containers view](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/infrastructure/images/monitor-baremetal-img2.png)

Hosts and Containers view
5.
: The new name to be given to the target.

Do not include any personal identifying information (PII) in any resource names.

--destination-crn DESTINATION_TARGET_CRN
: The CRN of the service instance or resource to receive the metrics sent by IBM Cloud Metrics Routing. Ensure you have a service authorization between IBM Cloud Metrics Routing and your IBM Cloud resource. For more information, see [Managing authorizations to grant access between services.](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-iam-service-auth). --output FORMAT
: Support format is JSON. If specified, output is returned in JSON format. If JSON is not specified, output is returned in a tabular format.

help | --help | -h
: List options available for the command.







 ibmcloud metrics-router target rm 

Use this command to delete a target.

ibmcloud metrics-router target rm --target TARGET [--force]



 Command options 

--target TARGET
: The ID or name of the target.

--force | -f
: Deletes the target without providing the user with any additional prompt.

help | --help | -h
: List options available for the command.







 ibmcloud metrics-router target get 

Use this command to get information about an IBM Cloud Metrics Routing target.

ibmcloud metrics-router target get --target TARGET [--output FORMAT]



 Command options 

--target TARGET
: The ID or name of the target.

--output FORMAT
: Supported format is JSON. If specified, output is returned in JSON format. If JSON is not specified, output is returned in a tabular format.

help | --help | -h
: List options available for the command.







 ibmcloud metrics-router target ls 

Use this command to list the configured targets for IBM Cloud Metrics Routing.

ibmcloud metrics-router target ls [--output FORMAT]
Select a [region](https://cloud.ibm.com/docs/monitoring?topic=monitoring-endpointsendpoints_regions).
4. Choose the monitoring instance that will collect metrics from enabled services on that location.
5. Click Select.



The main Observability page opens.







 Enabling a monitoring instance from the command line 

To enable platform metrics in a region, the instance that you want to configure to receive platform metrics must have set on the default_receiver property.

Complete the following steps:



1. [Pre-requisite] [Install the IBM Cloud CLI](https://cloud.ibm.com/docs/cli?topic=cli-install-ibmcloud-cli).
2. Log in to the region in the IBM Cloud where the monitoring instance is running. Run the following command: [ibmcloud login](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_cliibmcloud_login)
3. Set the resource group where the monitoring instance is running. Run the following command: [ibmcloud target](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_cliibmcloud_target)

By default, the default resource group is set.
4. Get the instance name. Run the following command: [ibmcloud resource service-instances](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_commands_resourceibmcloud_resource_service_instances)

ibmcloud resource service-instances
5. Get the plan ID of the instance.

Run the following command. Look for the entry for the monitoring instance. Then, copy the value of the field resource_plan_id. This value is needed to update the instance.

ibmcloud resource service-instances --long --output JSON
6. Set on the default_receiver property. Run the following command:
Table 1. National language Understanding package entities

 Entity Type Parameters Description 

 [natural-language-understanding-v1](https://cloud.ibm.com/apidocs/natural-language-understanding) Package username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, Work with the Natural Language Understanding service. 
 [analyze](https://cloud.ibm.com/apidocs/natural-language-understandinganalyze-text) Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, features, text, html, url, clean, xpath, fallback_to_raw, return_analyzed_text, language, limit_text_characters, Analyze text, HTML, or a public web page. 
 [delete-model](https://cloud.ibm.com/apidocs/natural-language-understandingdelete-model) Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, model_id, Delete model. 
 [list-models](https://cloud.ibm.com/apidocs/natural-language-understandinglist-models) Action username, password, iam_access_token, iam_apikey, iam_url, headers, headers[X-Watson-Learning-Opt-Out], url, List models. 





 Creating a Natural Language Understanding service instance 

Before you install the package, you must create a Natural Language Understanding service instance and service credentials.



1. [Create a Natural Language Understanding service instance](https://cloud.ibm.com/catalog/services/natural-language-understanding).
2. When the service instance is created, service credentials are automatically created for you.







 Installing the Natural Language Understanding package 

After you have a Natural Language Understanding service instance, install the Natural Language Understanding package into your namespace.