Training on metric data

Learn how to train metric data to detect anomalies and create analytic policies.

1. Run the following command:

   oc describe noi | grep CONTAINER_IMAGE.*ea-events-tooling

   An example of the output of the command is:

   --env=CONTAINER_IMAGE=`kubectl describe pod noi-cassandra-0 -n netcool| grep Image: | grep cassandra | head -1 | awk '{$1=""; print $0}' |awk -F'/' '{OFS = FS}{$NF=""; print $0}' | xargs`ea-events-tooling:15.0.0-20220622161201BST \

2. Copy and paste the text from the output of the command in Step 1 to set an environment variable named CONTAINER_IMAGE.
   Note: Copy the output text except the characters --env= and \.
   View and verify the setting by using the following command:

   echo $CONTAINER_IMAGE

3. Set the RELEASE environment variable and start the metric training by using the following command:
   Note: The release name is configurable and you must set it as the release environment used. The default release name is evtmanager.

   RELEASE=noi

4. Then, run the following command to execute training manually:

   kubectl run enablesinglemetrictraining -it --restart=Never --env=LICENSE=accept --command=true  \
   --overrides='{"apiVersion":"v1", "spec":{"imagePullSecrets":[{"name":"noi-registry-secret"}]}}' \
   --image=$CONTAINER_IMAGE --image-pull-policy=Always runTraining.sh \
   -- -r $RELEASE -a metric-manager-anomaly-detection -t cfd95b7e-3bc7-4006-a4a8-a73a79c71255

   Where noi-registry-secret is the entitlementSecret that is used in your deployment.

   Note: If you get an error such as a pod exists, then you can complete either of the following steps:

   • Use oc delete pod <name> to remove it.
   • Use a name for the pod that is not currently in use.
5. Schedule the metric anomaly detection training by running the command:

   kubectl run enablemetrictraining -it --restart=Never --env=LICENSE=accept --command=true  \
   --overrides='{"apiVersion":"v1", "spec":{"imagePullSecrets":[{"name":"noi-registry-secret"}]}}' \
   --image=$CONTAINER_IMAGE --image-pull-policy=Always enableTrainingSchedule.sh \
   -- -r $RELEASE -a metric-manager-anomaly-detection -t cfd95b7e-3bc7-4006-a4a8-a73a79c71255

6. Run the following command on the system to verify that the schedule runs correctly:

   TRAINER_IP=$(oc get svc|grep ibm-hdm-analytics-dev-trainer|awk '{print $3}') 
   oc rsh $(oc get po |grep spark-slave|head -1|awk '{print $1}') curl -X GET --header 'Content-Type: application/json' \
    --header 'Accept: application/json' --header 'X-TenantID: cfd95b7e-3bc7-4006-a4a8-a73a79c71255' \
    "http://${TRAINER_IP}:8080/1.0/training/analytics/metric-manager-anomaly-detection/schedule"