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Manual Configuration:

This configuration is required to enable the ranSlice features in SDN-R.

SDNC:

  •  Create the below environment variable in the helm chart at kubernetes/sdnc/templates/statefulset.yaml (for sdnc container). 

+          - name: SDNR_NORTHBOUND
+            value: "{{ .Values.config.sdnr.enabled | default "false"}}"

  • Make the SDNC chart and then deploy.
  • Execute the following command to log into the sdnc container 
    1. kubectl exec -it dev-sdnc-0 bash 
  • Once in the docker container, edit the properties file  /opt/onap/ccsdk/data/properties/ran-slice-api-dg.properties

POLICY:

  • Login to the policy-drools-pdp container and check if the value 'actor.service.SO.operations.Modify\ NSSI.path=3gppservices/v1/modify' is present in the below file:
    • kubectl exec -ti -n onap dev-policy-drools-pdp-0 sh
    • /opt/app/policy/config/event-manager.properties
  • If value not present update the policy-drools-pdp-image to this version'/onap/policy-pdpd-cl:1.10.2-20220413T1305' or any version after '1.10.2'


Policies needed:

Execute these curl requests from any of the running pods.

...

  1. git clone "https://gerrit.onap.org/r/cps/cps-tbdmt
  2. cd cps-tbdmt/
  3. mvn clean install
  4. cd docker-compose/
  5. update cps & ncmp ip-address in application.yml
  6. cps-tbdmt/docker-compose/application.yml should have the below mapping under the section schemaToAnchor:
    1. schemaToAnchor:
          ran-coverage-area: coverage-area-onap
          e2e-cavsta-schemaset: e2e-cavsta1
          CSIT-SchemaSet: CSIT-Anchor
          ns-schemaset: ns-anchor
          ran-network: 11
          ran-inventory: ran-inventory-anchor
  7. docker-compose up (use the image built using the above steps in the docker-compose file)

...

      2. Give chmod 777 to upload folder which will be created automatically in the home dir.

ML-prediction-ms:

  1. git clone "https://gerrit.onap.org/r/dcaegen2/services"(use patchset ml-prediction-ms if code not merged)
  2. cd services/components/ml-prediction-ms
  3. Update Ransim, Dmaap and ConfigDB IPAddress/Port details in ml-prediction-ms.config
  4. Build docker image using: 'docker build -t ml-prediction-ms:latest .'
  5. Run the ml-prediction-ms container.
    1. docker run -d --name ml-prediction-ms -p "5000:5000"  ml-prediction-ms:latest
  6. To view the logs:
    1. docker exec -ti ml-prediction-ms bash
    2. tail -f IntelligentSliceMl.log


NOTE: Use sample data attached under CONFIGDB, RANSIM and CPS if E2E communication service is not done.