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.

Access to the helm charts - use one of the below options#

  • Use helm charts available at edge-ai-libraries/microservices/time-series-analytics/helm

  • 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://registry-1.docker.io/intel/time-series-analytics-microservice --version 1.0.0

    2. unzip the package using the following command

      tar -xvzf time-series-analytics-microservice-1.0.0.tgz

    • Get into the helm directory

      cd time-series-analytics-microservice

Install helm charts#

Note:

  • Uninstall the helm charts if already installed.

  • 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 as follows with helm install command

cd edge-ai-libraries/microservices/time-series-analytics/helm # path relative to git clone folder
# Copy the config.json file to helm directory
cp ../config.json .
# Install helm charts
helm install time-series-analytics-microservice . -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

Ingesting Temperature Data into the Time Series Analytics Microservice#

Run the following script to ingest temperature data into the Time Series Analytics Microservice:

cd edge-ai-libraries/microservices/time-series-analytics # path relative to git clone folder
pip3 install -r simulator/requirements.txt
python3 simulator/temperature_input.py --port 30002

Verify the Temperature Classifier Results#

Run following commands to see the filtered temperature results:

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

Uninstall helm charts#

helm uninstall time-series-analytics-microservice -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:

    POD_NAME=$(kubectl get pods -n apps -o jsonpath='{.items[*].metadata.name}' | tr ' ' '\n' | grep deployment-time-series-analytics-microservice | head -n 1)
kubectl describe pod $POD_NAME $ -n apps # shows details of the pod
kubectl logs -f $POD_NAME -n apps | grep -i error


# Debugging UDF errors if container is not restarting and providing expected results
kubectl exec -it $POD_NAME -n apps -- /bin/bash
$ cat /tmp/log/kapacitor/kapacitor.log | grep -i error