The outcome

Share an AI application without exposing credentials, private artifacts, unsafe handlers, or an unmaintained execution surface.

Step by step

A workflow you can repeat.

  1. 01

    Define audience, visibility, inputs, outputs, model and data rights, content rules, secrets, network needs, hardware, storage, availability, cost, retention, and abuse response.

  2. 02

    Create a minimal Studio repository, pin the SDK, base image and dependencies, validate all inputs, isolate user files, and exclude shell execution, debug routes, and credentials.

  3. 03

    Configure secrets through the platform, choose the smallest hardware, deploy a reviewed revision, and inspect build and runtime logs for data, token, dependency, and permission leaks.

  4. 04

    Test malformed and oversized files, adversarial prompts, concurrency, resource exhaustion, model failure, unsafe output, unauthorized access, dependency compromise, and clean restart.

  5. 05

    Document ownership and limitations, monitor logs and usage, rotate secrets, update by reviewed revision, retain rollback, and stop or delete abandoned Studios and stored artifacts.

Working standard

What good use looks like.

  • Never commit Studio secrets.
  • Validate and isolate every upload.
  • Stop abandoned deployments promptly.

Official references

Check the current product documentation.