PrakshiGoyal10 opened a new pull request, #69998: URL: https://github.com/apache/airflow/pull/69998
On Airflow 3 the "Repair a single task" and "Repair All Failed Tasks" links on DatabricksWorkflowTaskGroup tasks were gated off, so on-call users had to leave Airflow and repair failed runs in the Databricks UI. This restores repair-from-Airflow on Airflow 3: - Register a FastAPI app on the API server that performs the repair, authorized with Dag-run edit access and authenticated via either the UI's bearer token (XHR) or its `_token` cookie (plain navigation), so a repair link clicked in the browser is authorized. - Resolve the set of failed tasks from the live Databricks run state rather than Airflow's metadata DB (new hook helper `get_run_failed_task_keys`), and call `repair_run` with `rerun_dependent_tasks` so downstream tasks resume too. - Clear the repaired task instances and their downstream instances, mapping Databricks task keys to Airflow `task_id`s via the same `md5(dag_id__task_id)` scheme used by the operators, which works on the serialized Dag. - Remove the Airflow 3 gates on the plugin registration and the per-operator extra links so the repair buttons render again. Verified end-to-end against a real Databricks workflow on serverless and job clusters: a failed task plus its `upstream_failed` downstream both return to success after clicking repair. --- ##### Was generative AI tooling used to co-author this PR? - [X] Yes — Claude Code (Opus 4.8) Generated-by: Claude Code (Opus 4.8) following [the guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#gen-ai-assisted-contributions) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
