How to deploy with Helm* Chart#

This section shows how to deploy the Live Video Search sample application using Helm chart.

Prerequisites#

Before you begin, ensure that you have the following:

  • Kubernetes* cluster set up and running.

  • The cluster must support dynamic provisioning of Persistent Volumes (PV). Refer to the Kubernetes Dynamic Provisioning Guide for more details.

  • Install kubectl on your system. See the Installation Guide. Ensure access to the Kubernetes cluster.

  • Helm installed on your system. See the Installation Guide.

  • Storage Requirement: Ensure enough storage is available in the cluster for PVC-backed services.

See also: System Requirements.

Helm Chart Installation#

To set up the end-to-end application, acquire the chart and install it with the required values and scenario overrides.

1. Acquire the Helm chart#

There are 2 options to get the charts in your workspace:

Option 1: Get the charts 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/live-video-search --version <version-no>

Refer to release notes for details on the latest version to use.

Step 2: Extract the .tgz file#

After pulling the chart, extract the .tgz file:

tar -xvf live-video-search-<version-no>.tgz

This creates a directory named live-video-search containing chart files. Navigate to the extracted directory:

cd live-video-search

Option 2: Install from Source#

Clone the repository and navigate to the chart directory:

git clone https://github.com/open-edge-platform/edge-ai-suites.git edge-ai-suites
cd edge-ai-suites/metro-ai-suite/live-video-analysis/live-video-search/chart

2. Configure Required Values#

The application requires a few user-provided values. Use user_values_override.yaml as the single user-edit file:

nano user_values_override.yaml

Update these required values:

Key

Description

Example Value

global.credentials.minioRootUser

MinIO user

<your-minio-user>

global.credentials.minioRootPassword

MinIO password

<your-minio-password>

global.credentials.postgresUser

PostgreSQL user

<your-postgres-user>

global.credentials.postgresPassword

PostgreSQL password

<your-postgres-password>

global.credentials.mqttUser

MQTT user

<your-mqtt-user>

global.credentials.mqttPassword

MQTT password

<your-mqtt-password>

global.env.embeddingModelName

Embedding model used by search stack

CLIP/clip-vit-b-32

Common optional values:

Key

Description

Example Value

global.registry

Optional image registry override

intel

global.tag

Shared image tag

latest

global.vssStackTag

Override tag for VSS stack services

1.3.2

global.smartNvrStackTag

Override tag for Smart NVR services

1.2.4

global.proxy.httpProxy

HTTP proxy

http://proxy-example.com:000

global.proxy.httpsProxy

HTTPS proxy

http://proxy-example.com:000

global.usePvc

Use PVC-backed storage paths for MME/DataPrep

true or false

global.keepPvc

Retain PVCs on uninstall

true or false

global.gpu.multimodalEmbeddingEnabled

Enable MME on GPU

true or false

global.gpu.vdmsDataprepEnabled

Enable DataPrep on GPU

true or false

global.gpu.key

GPU resource key from device plugin

gpu.intel.com/xe / gpu.intel.com/i915

global.gpu.device

Device mode for GPU deployment

GPU

frigate.usbCameraDevice

USB device path (used with USB profile)

/dev/video0

Note: Scenario selection is profile-driven. Use override profiles for mode switching (default_override.yaml, rtsp_test_override.yaml, usb_camera_override.yaml) instead of setting mode switches in user_values_override.yaml.

Tag Resolution Note: global.tag is the fallback image tag. If global.vssStackTag is non-empty, VSS-side services use it instead of global.tag. If global.smartNvrStackTag is non-empty, Smart NVR-side services use it instead of global.tag. Leaving stack-specific tags empty makes those services inherit global.tag.

Device Note: global.env.embeddingDevice defaults to CPU in chart values and is internally resolved for non-GPU mode.

GPU Note: If enabling GPU for search embeddings, set both global.gpu.multimodalEmbeddingEnabled=true and global.gpu.vdmsDataprepEnabled=true, and also set global.gpu.key and global.gpu.device.

3. Build Helm Dependencies#

Run from the chart directory:

helm dependency build

4. Set and Create a Namespace#

  1. Set a namespace variable:

    my_namespace=lvs

  2. Create namespace:

    kubectl create namespace $my_namespace

NOTE: All subsequent steps assume my_namespace is set in your shell.

5. Deploy the Helm Chart#

Deploy one of the following use cases.

Note: Before switching use cases, uninstall the existing release if it is already running: helm uninstall lvs -n $my_namespace

Use Case 2: RTSP Test Mode#

helm install lvs . -f user_values_override.yaml -f rtsp_test_override.yaml -n $my_namespace

Use Case 3: USB Camera Mode#

helm install lvs . -f user_values_override.yaml -f usb_camera_override.yaml -n $my_namespace

Use Case 4: GPU-enabled MME + DataPrep#

First update user_values_override.yaml:

  • global.gpu.multimodalEmbeddingEnabled: true

  • global.gpu.vdmsDataprepEnabled: true

  • global.gpu.key: <gpu-resource-key>

  • global.gpu.device: GPU

Then deploy with your selected scenario profile (example: default):

helm install lvs . -f user_values_override.yaml -f default_override.yaml -n $my_namespace

Step 6: Verify the Deployment#

kubectl get pods -n $my_namespace
kubectl get svc -n $my_namespace

Before proceeding, ensure:

  1. Pods are in Running state.

  2. Containers are in ready state.

Note: init-resources runs as a Kubernetes Job. Its pod can show 0/1 Completed (for example, lvs-live-video-search-init-resources-xxxxx 0/1 Completed), which is expected. Use kubectl get jobs -n $my_namespace and confirm lvs-live-video-search-init-resources shows COMPLETIONS 1/1 and STATUS Complete.

If needed, inspect specific workloads:

kubectl describe pod <pod-name> -n $my_namespace
kubectl logs <pod-name> -n $my_namespace

Step 7: Accessing the application#

Nginx service runs as a reverse proxy in one of the pods and is exposed via NodePort by default. Get the host IP and NodePort using:

lvs_hostip=$(kubectl get pods -l app=nginx -n $my_namespace -o jsonpath='{.items[0].status.hostIP}')
lvs_port=$(kubectl get service nginx -n $my_namespace -o jsonpath='{.spec.ports[0].nodePort}')
echo "http://${lvs_hostip}:${lvs_port}"

Copy the printed URL and open it in your browser to access the Live Video Search Application.

If you prefer local access without NodePort:

kubectl port-forward svc/nginx 12345:80 -n $my_namespace

Open http://localhost:12345.

Step 8: Update Helm Dependencies#

If subchart dependencies change:

helm dependency build

Step 9: Uninstall Helm chart#

helm uninstall lvs -n $my_namespace

PVC retention on uninstall is controlled by global.keepPvc.

When global.keepPvc: true, PVC-backed data is retained across uninstall/reinstall and pod restarts. This includes persisted application state (for example, stored query-related data in backing services) and converted OpenVINO model assets stored on persistent volumes.

If you want a clean reset, delete all PVCs for the lvs release:

kubectl delete pvc -n "$my_namespace" -l app.kubernetes.io/instance=lvs

Troubleshooting#

  • Pods stay Pending or not Ready: Check storage provisioning, node capacity, and device plugin availability (for GPU mode).

  • Node allocation/scheduling issues caused by PVC affinity conflicts (often from old PVCs): Delete old release PVCs and redeploy:

    kubectl delete pvc -n "$my_namespace" -l app.kubernetes.io/instance=lvs

  • Search not returning expected results: Verify global.env.embeddingModelName and confirm clips are ingested.

  • USB mode does not detect camera: Confirm device path and override frigate.usbCameraDevice in user_values_override.yaml when not using /dev/video0.

  • GPU deployment fails validation: Ensure both MME and DataPrep GPU flags are aligned, and both global.gpu.key and global.gpu.device are set.