HAMi DRA Webhook

A Kubernetes mutating webhook that converts GPU device resources to Dynamic Resource Allocation (DRA) ResourceClaims.

Overview

This webhook automatically transforms Pod specifications that request GPU resources (e.g., nvidia.com/gpu) into DRA ResourceClaims, enabling dynamic resource allocation for GPU workloads in Kubernetes.

Features

• Automatic Resource Conversion: Converts GPU resource requests to ResourceClaims
• Resource Cleanup: Automatically removes GPU resources from Pod specs and creates corresponding ResourceClaims
• Annotation Support: Supports device selection via Pod annotations (UUID, device type)
• Metrics Monitoring: Optional monitor component that collects and exposes GPU resource metrics via Prometheus

Installation

Prerequisites

• Kubernetes version >= 1.34 with DRA Consumable Capacity featuregate enabled
• CDI must be enabled in the underlying container runtime (such as containerd or CRI-O).
• NVIDIA GPU Driver 440 or later

Configure and install with Helm

You need cert-manager installed before installing the webhook. If you don't want to use cert-manager, set certs.certManager.enabled=false and provide your own certificate via certs.custom.crt and certs.custom.key.

Add the HAMi-DRA Helm repository:

helm repo add hami-dra https://project-hami.github.io/HAMi-DRA
helm repo update

Install the chart:

helm install hami-dra hami-dra/hami-dra

To upgrade to the latest version in the future:

helm repo update
helm upgrade hami-dra hami-dra/hami-dra

If you are not using gpu-operator provided containerd drivers, you can use the following command to install the webhook:

helm install hami-dra hami-dra/hami-dra \
  --set drivers.nvidia.containerDriver=false

Then use the same as hami.

Hygon DCU

For clusters running Hygon DCU with k8s-dcu-dra-driver, see docs/hygon-dcu.md.

Configuration

Device Resources

Configure device resources via --set flags or a custom values.yaml. The default resource names are:

resourceName: "nvidia.com/gpu"
resourceMem: "nvidia.com/gpumem"
resourceCores: "nvidia.com/gpucores"

Monitor Component

The monitor component is an optional feature that collects and exposes GPU resource metrics via Prometheus. It is enabled by default.

Quick Start:

Set the monitor service to NodePort so we can access it outside the cluster:

monitor:
  enabled: true
  service:
    type: NodePort
    nodePort:
      metrics: 31995

Access metrics:

# With NodePort
curl http://<node-ip>:31995/metrics

You will see metrics like this:

For detailed configuration, metrics documentation, and Prometheus integration, see MONITOR.md.