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datarobot-workload-api

Skill

Use when the user wants to create, configure, scale, debug, observe, or roll out container workloads on DataRobot's Workload API. Triggers include: deploying a container as a managed service, listing/starting/stopping workloads, changing replica counts or autoscaling, picking CPU/GPU compute bundles

0Debugging

Install

git clone https://github.com/datarobot-oss/datarobot-agent-skills.git ~/.claude/skills/datarobot-workload-api

What is datarobot-workload-api?

Use when the user wants to create, configure, scale, debug, observe, or roll out container workloads on DataRobot's Workload API. Triggers include: deploying a container as a managed service, listing/starting/stopping workloads, changing replica counts or autoscaling, picking CPU/GPU compute bundles, injecting DataRobot credentials as env vars, diagnosing workloads that are stuck / errored / crash-looping (CrashLoopBackOff, ImagePullBackOff, OOMKilled, probe failures, exec format error), pulling application logs / OpenTelemetry traces / metrics / request stats, creating or iterating container artifacts, building images server-side, locking artifacts for production, or doing a zero-downtime rolling artifact replacement.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~182 tokens of context used while enabled, before you invoke anything

Documentation

README · ~10 min read

DataRobot Workload API

Run container images as managed, autoscalable services on DataRobot. One skill, four jobs — pick the section by user intent:

  1. Create / configure / scale — deploy a container; change replicas, resources, autoscaling, bundle; inject credentials
  2. Diagnose — workload is stuck, errored, or crash-looping
  3. Observe — logs, traces, metrics, service stats for a running workload
  4. Artifact lifecycle — iterate drafts, build images, lock for production, roll out new versions

Prerequisites

DATAROBOT_ENDPOINT (must end in /api/v2) and DATAROBOT_API_TOKEN must be set. Run datarobot-setup if not. Auth header: Authorization: Bearer ${DATAROBOT_API_TOKEN}. The Workload API is not in the datarobot Python SDK — call REST directly.

Transport. Examples use Python httpx (pip install httpx). The API is plain HTTP, so equivalent calls work via curl or the pulumi-datarobot Pulumi provider declaratively. The skill teaches the model; transport is interchangeable.

Bundled scripts

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