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How to Deploy with Helm

Prerequisites

  • System Requirements
  • K8s installation on single or multi node must be done as pre-requisite to continue the following deployment. Note: The kubernetes cluster is set up with kubeadm, kubectl and kubelet packages on single and multi nodes with v1.30.2. Refer to tutorials such as https://adamtheautomator.com/installing-kubernetes-on-ubuntu and many other online tutorials to setup kubernetes cluster on the web with host OS as ubuntu 22.04.
  • For helm installation, refer to helm website

Note If Ubuntu Desktop is not installed on the target system, follow the instructions from Ubuntu to install Ubuntu desktop.

Generate or Download the helm charts

  • Using pre-built helm charts:

    Follow this procedure on the target system to install the package.

    1. Download helm chart with the following command

      helm pull oci://<path-to-internal-harbor-registry-OR-intel-docker-hub-registry-path>/wind-turbine-anomaly-detection-sample-app --version 1.0.0

    2. unzip the package using the following command

      tar -xvzf wind-turbine-anomaly-detection-sample-app-1.0.0.tgz

    • Get into the helm directory

      cd wind-turbine-anomaly-detection-sample-app

  • Generate the helm charts

    cd edge-ai-suites/manufacturing-ai-suite/wind-turbine-anomaly-detection # path relative to git clone folder
make gen_helm_charts
cd helm/

Configure and update the environment variables

  1. Update the below fields in edge-ai-suites/manufacturing-ai-suite/wind-turbine-anomaly-detection/helm/values.yaml file in the helm chart

    INFLUXDB_USERNAME:
INFLUXDB_PASSWORD:
VISUALIZER_GRAFANA_USER:
VISUALIZER_GRAFANA_PASSWORD:
POSTGRES_PASSWORD:
MINIO_ACCESS_KEY:  
MINIO_SECRET_KEY: 
http_proxy: # example: http_proxy: http://proxy.example.com:891
https_proxy: # example: http_proxy: http://proxy.example.com:891

Install helm charts - use only one of the options below:

Note:

  1. Please uninstall the helm charts if already installed.
  2. If the worker nodes are running behind proxy server, then please additionally set env.HTTP_PROXY and env.HTTPS_PROXY env like the way env.TELEGRAF_INPUT_PLUGIN is being set below with helm install command

  • OPC-UA ingestion flow:

    helm install ts-wind-turbine-anomaly --set env.TELEGRAF_INPUT_PLUGIN=opcua . -n apps --create-namespace

  • MQTT ingestion flow:

    helm install ts-wind-turbine-anomaly --set env.TELEGRAF_INPUT_PLUGIN=mqtt_consumer . -n apps --create-namespace

Use the following command to verify if all the application resources got installed w/ their status:

   kubectl get all -n apps

Copy the windturbine_anomaly_detection udf package for helm deployment to Time Series Analytics Microservice

You need to copy your own or existing model into Time Series Analytics Microservice in order to run this sample application in Kubernetes environment:

  1. The udf package is placed as below in the repository under time_series_analytics_microservice.

    - time_series_analytics_microservice/
    - models/
        - windturbine_anomaly_detector.pkl
    - tick_scripts/
        - windturbine_anomaly_detector.tick
    - udfs/
        - requirements.txt
        - windturbine_anomaly_detector.py

  2. Copy your new udf package (windturbine anomaly detection udf package used here as an example) to time-series-analytics-microservice pod.

    cd edge-ai-suites/manufacturing-ai-suite/wind-turbine-anomaly-detection # path relative to git clone folder
cd time_series_analytics_microservice
mkdir windturbine_anomaly_detector
cp -r models tick_scripts udfs windturbine_anomaly_detector/.

POD_NAME=$(kubectl get pods -n apps -o jsonpath='{.items[*].metadata.name}' | tr ' ' '\n' | grep deployment-time-series-analytics-microservice | head -n 1)

kubectl cp windturbine_anomaly_detector $POD_NAME:/tmp/ -n apps

    Note You need to run the above commands only after performing the Helm install.

Verify the wind turbine anomaly detection results

Please follow the steps per helm deployment at link

Uninstall helm charts

helm uninstall ts-wind-turbine-anomaly -n apps
kubectl get all -n apps # it takes few mins to have all application resources cleaned up

Troubleshooting

  • Check pod details or container logs to catch any failures:

    kubectl get pods -n apps
kubectl describe pod <pod_name> -n apps # shows details of the pod
kubectl logs -f <pod_name> -n apps # shows logs of the container in the pod