The outcome

Provide predictable inference for steady or customized workloads without leaving idle resources unmanaged.

Step by step

A workflow you can repeat.

  1. 01

    Measure serverless traffic, latency, errors, utilization pattern, and cost, then define the dedicated endpoint's service objective.

  2. 02

    Confirm model eligibility, license, hardware choices, regional needs, expected replicas, and hourly cost under each scaling scenario.

  3. 03

    Create a staging endpoint with credentials stored in a secret manager and exercise it through the same inference API.

  4. 04

    Load-test realistic concurrency, cold starts, scaling, timeouts, failures, and output quality before routing production traffic.

  5. 05

    Roll out gradually, monitor utilization and spend, and stop or resize unused endpoints using a documented rollback path.

Working standard

What good use looks like.

  • Justify dedicated capacity with measurements.
  • Load-test before cutover.
  • Stop idle endpoints deliberately.

Official references

Check the current product documentation.