Deploy GIM Stream Processor

Learn how to deploy GIM Stream Processor (GSP) into a private edition environment.

Related documentation:

• How Reporting works
• Suite-level guide
• All services
• Genesys Info Mart Release Notes

RSS:

• For private edition

Assumptions

• The instructions on this page assume you are deploying the service in a service-specific namespace, named in accordance with the requirements on Creating namespaces. If you are using a single namespace for all private edition services, replace the namespace element in the commands on this page with the name of your single namespace or project.
• Similarly, the configuration and environment setup instructions assume you need to create namespace-specific (in other words, service-specific) secrets. If you are using a single namespace for all private edition services, you might not need to create separate secrets for each service, depending on your credentials management requirements. However, if you do create service-specific secrets in a single namespace, be sure to avoid naming conflicts.

Important

Make sure to review Before you begin GSP deployment for the full list of prerequisites required to deploy GSP, including creation of the required S3-compatible storage (see Create object storage).

Set up your environment

To prepare your environment for the deployment, complete the steps in this section for:

• OpenShift
• GKE

Environment setup for OpenShift

1. Log in to the OpenShift cluster via CLI on the host where you will run the deployment:

   oc login --token <token> --server <URL of the API server>

2. (Optional) Check the cluster version:

   oc get clusterversion

3. If the cluster administrator has not already done so, create a new project for GSP:

   oc new-project gsp

4. Set the default project to gsp:

   oc project gsp

5. Create a secret for docker-registry in order to pull images from the Genesys JFrog repository:

   oc create secret docker-registry <repository secret name> --docker-server=<repository> --docker-username=<username> --docker-password=<password/API key> --docker-email=<email id> -n gsp

   Create a secret named kafka-secrets in order to access Kafka.

   When Kafka is deployed without authentication:

   oc create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"<kafka-bootstrap-url>\"} -n gsp

   When Kafka is deployed with authentication:

   oc create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"<kafka-bootstrap-url>\", \"username\":\"gsp\",\"password\":\"<password>\"} -n gsp

   For example:

   oc create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"infra-kafka-cp-kafka.infra.svc.cluster.local:9092\",\"username\":\"gsp\",\"password\":\"kafka-password\"} -n gsp

Environment setup for GKE

1. Ensure that the gcloud CLI and required Helm version are installed on the host where you will run the deployment.
2. Log in to the GKE cluster from the host where you will run the deployment:

   gcloud container clusters get-credentials <cluster>

3. If the cluster administrator has not already done so, create a new namespace for GSP:
   1. Create a .json file specifying the namespace metadata. For example, create-gsp-namespace.json:

      {
        "apiVersion": "v1",
        "kind": "Namespace",
        "metadata": {
          "name": "gsp",
          "labels": {
            "name": "gsp"
          }
        }
      }

   2. Execute the following command to create the namespace:

      kubectl apply -f create-gsp-namespace.json

   3. Confirm namespace creation:

      kubectl describe namespace gsp

4. Create a secret for docker-registry in order to pull images from the Genesys JFrog repository:

   kubectl create secret docker-registry <repository secret name> --docker-server=<repository> --docker-username=<username> --docker-password=<password/API key> --docker-email=<email id> -n gsp

5. Create a secret named kafka-secrets in order to access Kafka.

   When Kafka is deployed without authentication:

   kubectl create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"<kafka-bootstrap-url>\"} -n gsp

   When Kafka is deployed with authentication:

   kubectl create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"<kafka-bootstrap-url>\", \"username\":\"gsp\",\"password\":\"<password>\"} -n gsp

   For example:

   kubectl create secret generic kafka-secrets --from-literal=kafka-secrets={\"bootstrap\":\"infra-kafka-cp-kafka.infra.svc.cluster.local:9092\",\"username\":\"gsp\",\"password\":\"kafka-password\"} -n gsp

Deploy

Execute the following command:

helm install gsp <gsp-helm-artifact> -f <gsp-values.yaml> -n gsp

Validate the deployment

You can consider GSP deployment successful when the pod is running and in Ready state. Genesys Info Mart does not report the Ready state for pods until internal health checks are satisfied and the pods are operational. You can use standard kubectl commands like list and get to verify the successful deployment and readiness status of the Kubernetes objects.

However, from a functional point of view, you cannot validate GSP deployment unless GCA and GIM have been deployed as well. Do not expect consistent data until all three Genesys Info Mart services are up and running. When all three services have been deployed:

1. Make a few test calls employing different routing strategies under different scenarios, and verify that all the calls are correctly captured in the Info Mart database. For example:
   • The calls appear in the interaction-related tables.
   • The calls have been correctly assigned to agents and queues.
2. Review the logs to verify no errors.
3. Monitor the operations dashboard to verify that the services report their status as Ready, and pods are not continually restarting.