The outcome

Create a staged model endpoint whose permissions, behavior, capacity, and operational limits are known.

Step by step

A workflow you can repeat.

  1. 01

    Define the task, data classification, approved Azure region, benchmark, latency and throughput target, safety policy, and budget.

  2. 02

    Create an isolated Foundry project, assign least-privilege RBAC and managed identity, and keep control-plane and application access separate.

  3. 03

    Review model provenance, terms, deployment options, regional availability, pricing, and integrated content-filter behavior before deployment.

  4. 04

    Run the same factual, adversarial, safety, structured-output, latency, throttling, and failure tests against shortlisted models.

  5. 05

    Publish only the approved deployment, route secrets through managed identity or Key Vault, enable monitoring and quotas, and retain rollback settings.

Working standard

What good use looks like.

  • Isolate work by project.
  • Test each model and deployment type.
  • Prefer managed identity over embedded keys.

Official references

Check the current product documentation.