paralleliq-dstack-plugin 0.2.0

dstack plugin that surfaces piqc GPU waste scanning when a GPU fleet or run is applied

paralleliq-dstack-plugin

A dstack plugin that surfaces piqc — Paralleliq's open-source GPU waste scanner — whenever a GPU fleet or run is applied to a dstack project.

What it does

When a user runs dstack apply on a fleet or task that requests GPU resources, the plugin prints a one-time message showing how to run a GPU waste scan against the cluster:

╔══════════════════════════════════════════════════════════════════╗
║  Paralleliq — GPU fleet detected                                 ║
║                                                                  ║
║  Run a free GPU waste scan on this cluster:                      ║
║                                                                  ║
║  kubectl apply -f https://.../deploy/rbac.yaml                   ║
║  kubectl apply -f https://.../deploy/scan-job.yaml               ║
║  kubectl logs -n kube-system job/piqc-scan                       ║
║                                                                  ║
║  github.com/paralleliq/piqc  ·  paralleliq.ai                   ║
╚══════════════════════════════════════════════════════════════════╝

The two kubectl commands:

1. Apply RBAC — creates a ServiceAccount, ClusterRole, and ClusterRoleBinding scoped to what piqc needs
2. Run the scan — launches a one-shot K8s Job using ghcr.io/paralleliq/piqc:latest

Results appear in the job logs. The job auto-deletes after 10 minutes.

Why kubectl instead of a dstack task?

piqc needs cluster-wide Kubernetes API access — to list pods, deployments, and nodes, and to exec into pods to run nvidia-smi. dstack does not currently support specifying a serviceAccountName in task configuration, so a dstack task would run with the namespace default service account and have no cluster permissions.

Using standard K8s manifests lets piqc work correctly on any Kubernetes cluster, dstack-managed or not.

Installation

Install on the server where dstack is running:

pip install paralleliq-dstack-plugin

dstack discovers plugins automatically via Python entry points — no additional configuration required.

Requirements

• dstack >= 0.19 (server-side installation)
• kubectl access to the cluster (for running the scan commands)

piqc

piqc is open-source. Source and docs: github.com/paralleliq/piqc

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Built by Paralleliq