The outcome

Create a secured, observable model endpoint with explicit dependencies, resources, and scaling behavior.

Step by step

A workflow you can repeat.

  1. 01

    Define the endpoint contract, model and data licenses, GPU and memory needs, dependency image, secrets, latency, and cost targets.

  2. 02

    Implement a small Ray Serve application with typed validation, bounded batching, health checks, and idempotent request handling.

  3. 03

    Create a versioned service configuration covering compute, applications, runtime environment, autoscaling, and bearer-token access.

  4. 04

    Deploy to a non-production project and test startup, normal and malformed requests, concurrency, node loss, logs, and metrics.

  5. 05

    Record the service version and configuration, then promote only after output quality, load, security, and cost checks pass.

Working standard

What good use looks like.

  • Use configuration files for production.
  • Keep bearer-token protection enabled.
  • Test the service under realistic load.

Official references

Check the current product documentation.