Release v10.11.0

[jtherrmann]

TODO:

• Validate in hyp3-test
  • Run an already-archived ARIA_S1_GUNW job, a non-archived ARIA_S1_GUNW job, and a job of a different type; confirm jobs behave as expected and credits get refunded
  • Test with infinite credits
  • An archived job can be fetched and displayed via the SDK
  • An archived job looks mostly correct in Vertex after succeeding; browse image and file size displays correctly, product download link works
  • Run the default batch of each job type: https://hyp3-test-api.asf.alaska.edu/jobs?user_id=jtherrmann&name=20250806 (6/7 have succeeded, and the INSAR_ISCE_MULTI_BURST is still running)
  • Verify the ScaleCluster changes (just by looking at the CloudFormation stack in edc-uat)
• Fix changelog

---

Started with 9880 credits.

Submitted an already-archived ARIA_S1_GUNW job, a non-archived ARIA_S1_GUNW job (changed one of the dates), and an INSAR_ISCE_BURST job, for a total cost of 60 + 60 + 1 = 121. My total credits decreased to 9759, as expected.

Response for the archived ARIA_S1_GUNW job:

{
  "job_id": "91834dc3-c2da-46dd-bf06-d5596b74319b",
  "user_id": "jtherrmann",
  "status_code": "PENDING",
  "execution_started": false,
  "request_time": "2025-08-06T18:53:21+00:00",
  "priority": 9879,
  "job_type": "ARIA_S1_GUNW",
  "name": "archived",
  "job_parameters": {
    "reference_date": "2019-12-31",
    "secondary_date": "2018-12-12",
    "frame_id": 11040
  },
  "credit_cost": 60
}

After a short wait, https://hyp3-test-api.asf.alaska.edu/jobs/91834dc3-c2da-46dd-bf06-d5596b74319b returns:

{
  "processing_times": [
    0
  ],
  "browse_images": [
    "https://grfn-public-prod.asf.alaska.edu/S1-GUNW-D-R-071-tops-20191231_20181212-135207-00119W_00035N-PP-fc9b-v3_0_1.png"
  ],
  "credit_cost": 0,
  "priority": 9879,
  "execution_started": true,
  "job_id": "91834dc3-c2da-46dd-bf06-d5596b74319b",
  "name": "archived",
  "request_time": "2025-08-06T18:53:21+00:00",
  "status_code": "SUCCEEDED",
  "user_id": "jtherrmann",
  "files": [
    {
      "size": 127563643,
      "url": "https://grfn.asf.alaska.edu/door/download/S1-GUNW-D-R-071-tops-20191231_20181212-135207-00119W_00035N-PP-fc9b-v3_0_1.nc",
      "filename": "S1-GUNW-D-R-071-tops-20191231_20181212-135207-00119W_00035N-PP-fc9b-v3_0_1.nc"
    }
  ],
  "job_parameters": {
    "secondary_date": "2018-12-12",
    "frame_id": 11040,
    "reference_date": "2019-12-31"
  },
  "expiration_time": "3022-03-13T18:53:42+00:00",
  "job_type": "ARIA_S1_GUNW"
}

And my credits have been increased to 9819, as expected.

Also ran the same test with my remaining_credits set to null (infinite credits), and confirmed everything worked as expected, and the step function execution succeeded.

[github-actions]

Developer checklist

• Indicated the level of changes to this package by affixing one of these labels:
  • major -- Major changes to the API that may break current workflows
  • minor -- Minor changes to the API that do not break current workflows
  • patch -- Patches and bugfixes for the current version that do not break current workflows
  • bumpless -- Changes to documentation, CI/CD pipelines, etc. that don't affect the software's version
• (If applicable) Updated the dependencies and indicated any downstream changes that are required
• Added/updated documentation for these changes
• Added/updated tests for these changes
• Verified changes in test deployment and summarized results, e.g. in PR description or comments on the related issue(s)
• If the step function code has changed, have you drained the job queue before merging?
  • For example, if the interface for a Lambda function has changed to expect different input,
    then currently running jobs (which use the old step function definition) will call the new
    function with the old input. So we must drain the job queue before deployment, so that the new
    function is only called by the new step function definition.

Reviewer checklist

• Have all dependencies been updated?
• Is the level of changes labeled appropriately?
• Are all the changes described appropriately in CHANGELOG.md?
• Has the documentation been adequately updated?
• Are the tests adequate?
• Have the changes been verified in the test deployment?