Databricks Model Serving
Databricks Model Serving endpoint lifecycle and ops.
by databricks
The skill
Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); Knowledge Assistants/Supervisor Agents (databricks-agent-bricks); MLflow evaluation (databricks-mlflow-evaluation).
This skill's licence does not allow redistribution, so the store does not show its text. Read it at the source.
Use this skill
Connect your agent to the Skill Store MCP server and ask for it by ref: databricks/databricks-model-serving-9142700571.
Details
- Publisher
- databricks
- Category
- Data & Analytics › Machine learning & training
- Updated
- 2026-10-19
References
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