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How to deploy with Helm

This guide provides step-by-step instructions for deploying the Model-Download Microservice using Helm.

Prerequisites

Before you begin, ensure that you have the following prerequisites:

Steps to deploy with Helm

Following steps should be followed to deploy Model-Download using Helm. You can install from source code or pull the chart from Docker hub.

Steps 1 to 2 varies depending on if the user prefers to build or pull the Helm details.

Option 1: Install from Docker Hub

Step 1: Pull the Specific Chart

Use the following command to pull the Helm chart from Docker Hub:

helm pull oci://registry-1.docker.io/intel/model-download-chart --version <version-no>

🔍 Refer to the Docker Hub tags page for details on the latest version number to use for the application.

Step 2: Extract the .tgz File

After pulling the chart, extract the .tgz file:

tar -xvf model-download-chart-<version-no>.tgz

This will create a directory named model-download-chart containing the chart files. Navigate to the extracted directory.

cd model-download-chart

Option 2: Install from Source

Step 1: Clone the Repository

Clone the repository containing the Helm chart:

# Clone the latest on mainline
  git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries
# Alternatively, Clone a specific release branch
  git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries -b <release-tag>

Step 2: Change to the Chart Directory

Navigate to the chart directory:

cd edge-ai-libraries/microservices/model-download/chart

Common Steps

Step 3: Configure the values.yaml File

Edit the values.yaml file located in the chart directory to set the necessary environment variables. Ensure you set the proxy settings as required

Below is a summary of key configuration options available in the values.yaml file:

Parameter Description Example Value Required
env.HUGGINGFACEHUB_API_TOKEN Hugging Face access token hf_xxx Yes
env.GETI_WORKSPACE_ID GETI workspace ID Yes, For GETI connection
env.GETI_HOST GETI connection host address Yes, For GETI connection
env.GETI_TOKEN GETI Personal Access token Yes, For GETI connection
env.GETI_SERVER_API_VERSION GETI API version v1 Yes, For GETI connection
env.GETI_SERVER_SSL_VERIFY Enables SSL certificate validation for HTTPS/HTTP GETI hosts False Yes, For GETI connection
service.nodePort Sets the static port (in the 30000–32767 range) 32000 Yes
env.ENABLED_PLUGINS Comma-separated list of plugins to enable (e.g., huggingface,ollama,ultralytics, openvino and geti) or all to enable all available plugins all Yes
image.repository image repository url intel/model-download Yes
image.tag latest image tag latest Yes

Note: Refer to the chart's values.yaml for a full list of configurable parameters.

Step 4: Deploy the Helm Chart

Deploy the Model-Download Helm chart:

helm install model-download . -n <your-namespace>

Step 5: Verify the Deployment

Check the status of the deployed resources to ensure everything is running correctly

kubectl get pods -n <your-namespace>
kubectl get services -n <your-namespace>

Step 6: Access the Application

Open the application swagger documentation in a browser at http://<node-ip>:<node-port>/api/v1/docs

Step 7: Uninstall Helm chart

To uninstall helm charts deployed, use the following command:

helm uninstall <name> -n <your-namespace>

Verification

  • Ensure that all pods are running and the services are accessible.
  • Access the application dashboard and verify that it is functioning as expected.

Troubleshooting

  • If you encounter any issues during the deployment process, check the Kubernetes logs for errors: 
    kubectl logs <pod-name>
  • If the PVC created during a Helm chart deployment is not removed or auto-deleted due to a deployment failure or being stuck, it must be deleted manually using the following commands: 
    # List the PVCs present in the given namespace
kubectl get pvc -n <namespace>

# Delete the required PVC from the namespace
kubectl delete pvc <pvc-name> -n <namespace>

Related links