vania-janet/multiturn-rag-retrieval-data huggingface dataset:
* In the Private Key field, upload a file that contains the admin identity's private key (in base64 or PEM format).



After you upload the certificate and private key of the identity to the console, you can use the console associate the identity with the peer or ordering node.







 Option 2: Create a five node ordering service using certificates from an external CA 

When you have a paid Kubernetes cluster on IBM Cloud, you have the additional option of deploying a five node ordering service that uses the Raft consensus protocol. Before you deploy a five node ordering service, you need to build a JSON file that contains all of the certificates for the five nodes by using the following instructions:



 Create the certificates JSON file 

The required certificates JSON file contains an array of five msp entries, where each array element contains the certificates for one of the ordering nodes. You must specify unique certificates for each node. Do not reuse certificates across the different ordering nodes. The certificates in the component section represent the certificates for the node itself, while the tls section includes the certificates issued by the TLS CA.



* keystore: The private key for this node
* signcerts: The public key (also known as a signing certificate or enrollment certificate) assigned by the CA for this node.
* cacerts: The certificate of the root CA.
* admincerts: The certificate of the admin users of the node. This might also be the admin of the organization.
* intermediatecerts: If your network includes multi-level CAs, paste in the certificate of the intermediate CA. If you did not use an intermediate certificate, you can leave this field blank.



Using the certificates that you gathered above, paste in the corresponding certificate in the fields below, in base64 format.

You can convert the contents of your certificate file, <cert.pem> from PEM format into a base64 string by running the following command on your local machine:

export FLAG=$(if [ "$(uname -s)" == "Linux" ]; then echo "-d"; else echo "-b 0"; fi)
cat <cert.pem> | base64 $FLAG

[
{
"msp": {
logging.basicConfig()
logging.root.setLevel(logging.NOTSET)
logging.basicConfig(level=logging.NOTSET)

authenticator = IAMAuthenticator('')

schematics_service = SchematicsV1(authenticator = authenticator)

schematics_service.set_service_url('https://us.schematics.cloud.ibm.com')

template_source_data_request_model = {}
template_source_data_request_model['env_values'] = [
{
"name": "TF_CLI_ARGS_plan",
"value": "-parallelism=250",
},
{
"name": "TF_CLI_ARGS_apply",
"value": "-parallelism=250"
}
]
template_source_data_request_model['folder'] = ''
template_source_data_request_model['type'] = 'terraform_v0.14.11'
template_source_data_request_model['variablestore'] = [
{
"name": "ssh_key_name",
"value": "sym-hpcc-key",
},
{
"name": "ibm_customer_number",
"value": "true"
}]

template_repo_request_model = {}
template_repo_request_model['url'] = 'https://github.com/IBM-Cloud/hpc-cluster-symphony'

logging.info("Started Creating Schematic Workspace")

workspace_response = schematics_service.create_workspace(
description="HPC Cluster schematic workspace using API",
name="Sample Schematic API workspace",
template_data=[template_source_data_request_model],
template_repo=template_repo_request_model,
kubectl scale statefulsets {set-name} --replicas={number}









 Stopping and restarting the cluster 

You can manually scale the cluster down and back up or use a script to stop and restart the service.



 Use a script to stop and restart Watson Assistant 

You can use the wactl.sh script to stop or restart the service.

To use the script to stop or restart the service, complete the following steps:



1. From a machine that has Kubernetes access to your cluster, log in to your cluster and change to the correct namespace (project).
2. Access the Helm chart from the file server on [Github](https://github.com/IBM/cloud-pak/tree/master/repo/cpd3/modules/ibm-watson-assistant/x86_64/).
3. Unzip the Helm chart TGZ file so you can access the scripts that are provided in the service installation package.
4. On the coordinator node, change to the /path/to/ibm-watson-assistant-prod/ibm_cloud_pakpak_extensions/post-install/namespaceAdministration/ subdirectory.
5. Run the wactl.sh script.



wactl.sh
--action [stop | start | restart | clean]
--release RELEASE
[--cli kubectl | oc]
[--include-ds]

The script accepts the following parameters:



* action: Required. Indicates the action you want to perform. Options include:



* stop: Stops the service by scaling down the replicas in an order that limits possible dependency issues. This option also stores an annotation within the deployment or statefulset. If you subsequently try to use the script to start the service and the annotation doesn't exist in one of the deployments or statefulsets, the script fails.
* start: You can only use this command to start the service if the wactl script was used to stop the service.
Run the px_cleanup.sh script to remove the DaemonSet from your cluster.

sh ./px_cleanup.sh







 Removing Portworx from your cluster 

If you don't want to use Portworx in your cluster, you can uninstall the Helm chart and delete your Portworx instance.

The following steps walk you through deleting the Portworx Helm chart from your cluster and deleting your Portworx instance. If you want to clean up your Portworx installation by removing your volumes from your apps, removing individual worker nodes from Portworx, or if you want to completely remove Portworx and all your volumes and data, see [Cleaning up your Portworx cluster](https://cloud.ibm.com/docs/openshift?topic=openshift-storage_portworx_removing).

The following commands result in data loss.



1. Follow the steps to [uninstall Portworx](https://docs.portworx.com/portworx-install-with-kubernetes/operate-and-maintain-on-kubernetes/uninstall/uninstall/delete-wipe-px-cluster-configuration). Note that for private clusters, you must specify the px-node-wiper image from the private icr.io registry.

curl -fSsL https://install.portworx.com/px-wipe | bash -s -- --talismanimage icr.io/ext/portworx/talisman --talismantag 1.1.0 --wiperimage icr.io/ext/portworx/px-node-wiper --wipertag 2.5.0
2. Find the installation name of your Portworx Helm chart.

helm ls -A | grep portworx

Example output

NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
logging.root.setLevel(logging.NOTSET)
logging.basicConfig(level=logging.NOTSET)

authenticator = IAMAuthenticator('')

schematics_service = SchematicsV1(authenticator = authenticator)

schematics_service.set_service_url('https://us.schematics.cloud.ibm.com')

template_source_data_request_model = {}
template_source_data_request_model['env_values'] = [
{
"name": "TF_CLI_ARGS_plan",
"value": "-parallelism=250",
},
{
"name": "TF_CLI_ARGS_apply",
"value": "-parallelism=250"
}
]
template_source_data_request_model['folder'] = ''
template_source_data_request_model['type'] = 'terraform_v0.14.11'
template_source_data_request_model['variablestore'] = [
{
"name": "ssh_key_name",
"value": "lsf-bcc-key",
},
{
"name": "ibm_customer_number",
"value": ""
}]

template_repo_request_model = {}
template_repo_request_model['url'] = 'https://github.com/IBM-Cloud/hpc-cluster-lsf'

logging.info("Started Creating Schematic Workspace")

workspace_response = schematics_service.create_workspace(
description="HPC Cluster schematic workspace using API",
name="Sample Schematic API workspace",
template_data=[template_source_data_request_model],
template_repo=template_repo_request_model,
Labels: <none>
Selector: app=liberty
Type: LoadBalancer
Location: dal10
IP: 172.21.xxx.xxx
LoadBalancer Ingress: 169.xx.xxx.xxx
Port: <unset> 8080/TCP
NodePort: <unset> 32040/TCP
Endpoints: 172.30.xxx.xxx:8080
Session Affinity: None
Events:
FirstSeen LastSeen Count From SubObjectPath Type Reason Message
--------- -------- ----- ---- ------------- ---- ------ -------
10s 10s 1 {service-controller } Normal CreatingLoadBalancer Creating load balancer
10s 10s 1 {service-controller } Normal CreatedLoadBalancer Created load balancer

The LoadBalancer Ingress IP address is the portable IP address that was assigned to your NLB service.
4. If you created a public NLB, access your app from the internet.



1. Open your preferred web browser.
2. Enter the portable public IP address of the NLB and port.

http://169.xx.xxx.xxx:8080



5. Optional: An NLB service also makes your app available over the service's NodePorts. [NodePorts](https://cloud.ibm.com/docs/containers?topic=containers-nodeport) are accessible on every public and private IP address for every node within the cluster. To block traffic to NodePorts while you are using an NLB service, see [Controlling inbound traffic to network load balancer (NLB) or NodePort services](https://cloud.ibm.com/docs/containers?topic=containers-network_policiesblock_ingress).



Next, you can [register an NLB subdomain](https://cloud.ibm.com/docs/containers?topic=containers-loadbalancer_hostname).





 Scheduling algorithms
VPC landing zone configurations 

This solution is verified and supported with only the following configurations (presets) for a VPC landing zone. These presets must be selected or inserted when deploying the VPC landing zone either separately or as part of a new Power infrastructure with VPC landing zone deployment.



* [RHEL secure landing zone preset](https://github.com/terraform-ibm-modules/terraform-ibm-powervs-infrastructure/blob/main/examples/ibm-catalog/presets/slz-for-powervs/rhel-vpc-pvs.preset.json). This preset creates a secure landing zone that is composed of three VPCs (edge, management, and workload) and of three VSIs with RHEL as operating system (bastion host, proxy server, management VSI)
* [SLES secure landing zone preset](https://github.com/terraform-ibm-modules/terraform-ibm-powervs-infrastructure/blob/main/examples/ibm-catalog/presets/slz-for-powervs/sles-vpc-pvs.preset.json). This preset creates a secure landing zone that is composed of three VPCs (edge, management, and workload) and of three VSIs with SLES as operating system (bastion host, proxy server, management VSI)



For more information regarding components that are defined in presets and the deployable architecture calling these presets, see [reference architecture for initial infrastructure deployment](https://cloud.ibm.com/docs/deployable-reference-architectures?topic=deployable-reference-architectures-deploy-arch-ibm-pvs-inf-full-stack).



 Trusted zones specified by configurations 

When you provision this landscape by using the VPC landing zone presets, the following trusted zones are configured.



Table 1. Trusted zones

 Trusted zone name Trusted zone type Trusted zone purpose Isolation methods 

 Edge VPC VPC service Isolate network connectivity to all resources located outside of the provisioned environment Restrictions by network ACLs and VPC security groups
The following example shows you how to revoke a target instance:

$ ibmcloud ae-v3 target --unset-instance
...

Target instance d0f582f7-cbf4-4c64-bf7f-72efd21c9f32 revoked
No target instance is set







 Instance management commands 

Use this command for Instance management.

ibmcloud analytics-engine-v3 instance --help



 ibmcloud analytics-engine-v3 instance show 

Retrieve the details of a single Analytics Engine instance.

ibmcloud analytics-engine-v3 instance show [--id ID]



 Command options 

-i, --id (string)
: GUID of the Analytics Engine service instance to retrieve. When specified, it overrides the target instance ID if it was set. Required if target instance was not set.

The value must match the regular expression /u0008[0-9a-f]{8}u0008-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-u0008[0-9a-f]{12}u0008/.





 Examples 

The following example shows how to use the show command without an instance ID. The requested operation is performed on the target instance.

ibmcloud analytics-engine-v3 instance show --output json

The following example shows how to use the show command with an instance ID that overrides the target instance ID if defined:

ibmcloud analytics-engine-v3 instance show --id=e64c907a-e82f-46fd-addc-ccfafbd28b09 --output json





 Example output 

The output is as follows:

{
"id" : "dc0e9889-eab2-4t9e-9441-566209499546",
"state" : "active",
"state_change_time" : "2021-04-21T04:24:01Z",
oc patch statefulset c-$INSTANCENAME-redis-m -p '{"spec":{"updateStrategy":{"type":"RollingUpdate"}}}'
oc patch statefulset c-$INSTANCENAME-redis-s -p '{"spec":{"updateStrategy":{"type":"RollingUpdate"}}}'
4. Update the Redis statefulsets with the resized cpu and memory values:
Member CPU

oc patch statefulset c-$INSTANCENAME-redis-m --type='json' -p='{"op": "replace", "path": "/spec/template/spec/containers/0/resources/requests/cpu", "value":"50m"},{"op": "replace", "path": "/spec/template/spec/containers/1/resources/requests/cpu", "value":"50m"},{"op": "replace", "path": "/spec/template/spec/containers/2/resources/requests/cpu", "value":"50m"},{"op": "replace", "path": "/spec/template/spec/containers/3/resources/requests/cpu", "value":"50m"}]'

Member memory
- name: statefulset-azuredisk
image: mcr.microsoft.com/oss/nginx/nginx:1.19.5
command:
- "/bin/bash"
- "-c"
- set -euo pipefail; while true; do echo $(date) >> /mnt/azuredisk/outfile; sleep 1; done
volumeMounts:
- name: persistent-storage
mountPath: /mnt/azuredisk
updateStrategy:
type: RollingUpdate
selector:
matchLabels:
app: nginx
volumeClaimTemplates:
- metadata:
name: persistent-storage
annotations:
volume.beta.kubernetes.io/storage-class: sat-azure-block-silver
spec:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 10Gi
Show more
5. Create the pod in your cluster.

oc apply -f statefulset-azuredisk.yaml
6. Verify that the pod is deployed. Note that it might take a few minutes for your app to get into a Running state.

oc get pods

NAME READY STATUS RESTARTS AGE
statefulset-azuredisk 1/1 Running 0 2m58s
7. Verify that the app can write to your Azure Disk by logging in to your pod.

oc exec statefulset-azuredisk -it bash
8. View the contents of the outfile file to confirm that your app can write data to your persistent storage.

cat /mnt/azuredisk/outfile

Example output

Fri Jul 16 07:49:39 EDT 2021
Fri Jul 16 07:49:39 EDT 2021
Fri Jul 16 07:49:39 EDT 2021
9. Exit the pod.

exit







 Removing Azure Disk storage from your apps
Global parameters can also be stored in persistent configuration so that they do not need to be manually specified each time the plugin is invoked. Each parameter can be configured with the config command and its subcommands.

ibmcloud secrets-manager config





 ibmcloud secrets-manager config set 

Set a new config value for a specific option. Each subcommand of the set command maps to a global option. Each subcommand accepts a single argument, the string representation of the value to store for the option.

ibmcloud secrets-manager config set <option> <value>



 Examples 

ibmcloud secrets-manager config set service-url 'https://ibm.cloud.com/my-api'







 ibmcloud secrets-manager config get 

Print out the currently set value for a specific option. Each subcommand of the get command maps to a global option.

ibmcloud secrets-manager config get <option>



 Examples 

ibmcloud secrets-manager config get service-url







 ibmcloud secrets-manager config unset 

Unset the currently set value for a specific option. Each subcommand of the unset command maps to a global option.

The subcommands available for this service are: service-url, .

ibmcloud secrets-manager config unset <option>



 Examples 

ibmcloud secrets-manager config unset service-url







 ibmcloud secrets-manager config list 

List out all of the currently set config values.

ibmcloud secrets-manager config list



 Examples 

ibmcloud secrets-manager config list









 Secret groups 

Control who can access secrets by creating and managing groups.



 ibmcloud secrets-manager secret-group-create 

Create a secret group that you can use to organize secrets and control who can access them.

A successful request returns the ID value of the secret group, along with other properties.
IBM Cloud Object Storage (COS) cloud_object_storage 



When you define a target in IBM Cloud Object Storage (COS), consider the following information:



* You can create the bucket in any location. For more information, see [Managing IBM Cloud Object Storage (COS) buckets](https://cloud.ibm.com/docs/atracker?topic=atracker-cos).
* You configure 1 bucket for each target.



If you have regulatory and compliance requirements, check the locations where you can create a bucket. Then, if performance is critical, consider creating the COS bucket in the same region where the auditing events are generated.



 CLI prerequisites 

Before you use the CLI to manage targets, complete the following steps:



1. Identify the endpoint in the region where you plan to configure or manage a target. For more information, see [Endpoints](https://cloud.ibm.com/docs/atracker?topic=atracker-endpointsendpoints_api).
2. [Pre-requisite] [Install the IBM Cloud CLI](https://cloud.ibm.com/docs/cli?topic=cli-install-ibmcloud-cli).
3. [Pre-requisite] [Install the IBM Cloud Activity Tracker Event Routing CLI](https://cloud.ibm.com/docs/atracker?topic=atracker-activity-tracking-cliactivity-tracking-cli-prereq).
4. Log in to the region in the IBM Cloud where the instance is running. Run the following command: [ibmcloud login](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_cliibmcloud_login)
5. Set the resource group where the instance is running. Run the following command: [ibmcloud target](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_cliibmcloud_target)
Watson Discovery News 

IBM Watson™ Discovery News is included with Discovery. Watson Discovery News is an indexed dataset that is pre-enriched with the following cognitive insights: Keyword Extraction, Entity Extraction, Semantic Role Extraction, Sentiment Analysis, Relation Extraction, and Category Classification. (To learn more about enrichments, see [Adding enrichments](https://cloud.ibm.com/docs/discovery?topic=discovery-configserviceadding-enrichments).) The following additional metadata is also added: crawl date and publication date. Historical search is available for the past 60 days of news data.

The Watson Discovery News feature is deprecated as of 8 October 2021. Existing News collections are available and support continues until 8 October 2022, after which date they will no longer be accessible.

Watson Discovery News is updated continuously with new articles, and is available in English, Spanish, German, Korean, French, and Japanese. Discovery News English is updated with approximately 200,000 new articles daily; Discovery News Spanish is updated with approximately 60,000 new articles daily; Discovery News German is updated with approximately 15,000 new articles daily; Discovery News Korean with 10,000 new articles daily; Discovery News French with 23,000 new articles daily; Discovery News Japanese is updated with approximately 17,000 new articles daily. The news sources vary by language, so the query results for each collection are not identical.

Use cases for Watson Discovery News:



* News alerting - Create news alerts by taking advantage of the support for entities, keywords, categories, and sentiment analysis to watch for both news and how it is perceived.
* Event detection - The subject/action/object semantic role extraction checks for terms/actions such as "acquisition", "election results", or "IPO".
* Trending topics in the news - Identify popular topics and monitor increases and decreases in how frequently they (or related topics) are mentioned.



For information about writing queries for IBM Watson™ Discovery News, see:



* [Querying Watson Discovery News](https://cloud.ibm.com/docs/discovery?topic=discovery-query-conceptsquerying-news)
For more information about endpoints, see [Endpoints and storage locations](https://cloud.ibm.com/docs/services/cloud-object-storage?topic=cloud-object-storage-endpointsendpoints)

Syntax

PUT https://{endpoint}/{bucket-name}?protection= path style
PUT https://{bucket-name}.{endpoint}?protection= virtual host style

Example request

PUT /example-bucket?protection= HTTP/1.1
Authorization: {authorization-string}
x-amz-date: 20181011T190354Z
x-amz-content-sha256: 2938f51643d63c864fdbea618fe71b13579570a86f39da2837c922bae68d72df
Content-MD5: GQmpTNpruOyK6YrxHnpj7g==
Content-Type: text/plain
Host: 67.228.254.193
Content-Length: 299
<ProtectionConfiguration>
<Status>Retention</Status>
<MinimumRetention>
<Days>100</Days>
</MinimumRetention>
<MaximumRetention>
<Days>10000</Days>
</MaximumRetention>
<DefaultRetention>
<Days>2555</Days>
</DefaultRetention>
</ProtectionConfiguration>
Show more

Example response

HTTP/1.1 200 OK
Date: Wed, 5 Oct 2018 15:39:38 GMT
X-Clv-Request-Id: 7afca6d8-e209-4519-8f2c-1af3f1540b42
Accept-Ranges: bytes
Server: Cleversafe/3.14.1
X-Clv-S3-Version: 2.5
x-amz-request-id: 7afca6d8-e209-4519-8f2c-1af3f1540b42
Delete an object DELETE {endpoint}/{bucket}/{key} cloud-object-storage.object.delete cloud-object-storage.object.delete 
 Add a CORS configuration PUT {endpoint}/{bucket}?cors cloud-object-storage.bucket.put_cors cloud-object-storage.bucket-cors.create 
 Read a CORS configuration GET {endpoint}/{bucket}?cors cloud-object-storage.bucket.get_cors cloud-object-storage.bucket-cors.read 
 Delete a CORS configuration DELETE {endpoint}/{bucket}?cors cloud-object-storage.bucket.delete_cors cloud-object-storage.bucket-cors.delete 
 Add/edit a bucket's lifecycle configuration PUT {endpoint}/{bucket}?lifecycle cloud-object-storage.bucket.put_lifecycle cloud-object-storage.bucket-lifecycle.create 
 Read a bucket's lifecycle configuration GET {endpoint}/{bucket}?lifecycle cloud-object-storage.bucket.get_lifecycle cloud-object-storage.bucket-lifecycle.read 
 Delete a bucket's lifecycle configuration DELETE {endpoint}/{bucket}?lifecycle cloud-object-storage.bucket.put_lifecycle cloud-object-storage.bucket-lifecycle.delete 
 Add/edit/remove a bucket's Immutable Storage policy PUT {endpoint}/{bucket}?protection cloud-object-storage.bucket.put_protection cloud-object-storage.bucket-retention.create 
 Read a bucket's Immutable Storage policy GET {endpoint}/{bucket}?protection cloud-object-storage.bucket.get_protection cloud-object-storage.bucket-retention.read 
 Initiate a multipart upload POST {endpoint}/{bucket}/{key}?uploads cloud-object-storage.object.post_initiate_upload cloud-object-storage.object-multipart.start
Consider securely configuring the bucket with appropriate encryption, access management, and data retention.

For cost control measures, you should set a quota to the [relevant bucket](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-quota) and set an [expiration rule](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-expiry).

Once the audit records have been successfully uploaded to the cloud object storage bucket, you can preview the files in the Console. To review larger subsets of the audit logs, refer to [Audit Policy](https://www.ibm.com/docs/en/db2woc?topic=features-audit-policy-guidelines). The [format](https://www.ibm.com/docs/en/db2/11.5?topic=format-example-del-file) of the archived audit logs is DEL which separates the text with commas. You can reformat and process this file in your system for further analysis.

For more information about auditing for Db2 Warehouse on Cloud, see [Audit policy guidelines](https://www.ibm.com/support/knowledgecenter/SS6NHC/com.ibm.swg.im.dashdb.security.doc/doc/audit_policy_guidelines.html).