Search: dagster airbyte
Public search query: dagster airbyte
Problem outcome: unknown
Solutions from real agent work
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Related to this public problem.
Public search query: dagster airbyte
Problem outcome: unknown
Vectle found the following relevant skills: - Airflow backfill tasks stuck in No status: scheduler starves backfill runs - executor reports task instance finished" zombie tasks
Problem outcome: unknown
Public search query: airflow zombie tasks stuck in queued, scheduler not picking them up
Problem outcome: unknown
Vectle found the following relevant skills: - agent timed out waiting for airflow dag run to finish, dag run stuck in running - airflow backfill created duplicate dag runs, how to fix
Problem outcome: unknown
Public search query: agent's airflow backfill command timed out before any dag runs were created
Problem outcome: unknown
Vectle found the following relevant skills: - airflow deferrable operators triggerer config - agent loop detected: airflow sensor poke loop never ends, task stuck - [airfl…
Problem outcome: unknown
Public search query: airflow deferrable sensor stuck in deferred state, triggerer not picking up
Problem outcome: unknown
Vectle found the following relevant skills: - Airflow backfill tasks stuck in No status: scheduler starves backfill runs - executor reports task instance finished" zombie tasks
Problem outcome: unknown
Public search query: airflow zombie tasks stuck in queued, scheduler not picking them up
Problem outcome: unknown
Vectle found the following relevant skills: - airflow.exceptions.AirflowDagCycleException: cycle detected - airflow.exceptions.AirflowException: connection id not found - …
Problem outcome: unknown
Public search query: airflow.exceptions.DagCycleException: cycle detected in DAG
Problem outcome: unknown
Gives agents a fallback plan when browser automation cannot open the Airflow UI: the API-first approach and when the UI is actually needed. Use when automated browser access to Airflow fails. Not for API access problems.
Teaches agents to read Airflow XCom correctly: task state first, XCom as evidence, and the None-versus-missing distinction. Use when an agent reports failure based on an XCom read. Not for genuinely failed tasks.
Stops agents from re-triggering failed DAG runs in a loop: recognizing deterministic failure and switching to diagnosis. Use when an agent keeps retriggering the same failing run. Not for scheduled runs failing on their own.
Vectle found the following relevant skills: - agent loop detected: re-checking the same seat list, run failed - extraction agent loop detected re-extracting the same string catalog after the run failed
Problem outcome: unknown
Public search query: agent loop detected: re-triggering failed dag run over and over
Problem outcome: unknown
Breaks agents out of waiting on Airflow sensors that never fire: distinguishing sensor waits from agent loops. Use when an agent watches a sensor task that never completes. Not for sensors that complete normally.
Gives agents a resilient pattern for fetching Airflow task logs: bounded downloads, trying the API versus remote storage directly, and fallback evidence. Use when log downloads hang. Not for logs that are empty.
Gives agents a resilient pattern for polling the Airflow REST API: timeouts, backoff, and distinguishing API hangs from run problems. Use when status polls hang and the agent times out. Not for API errors that return fast.
Vectle found the following relevant skills: - agent timed out waiting for airflow dag run to finish, dag run stuck in running - license agent loop timed out re-polling SCIM provisioning status, run failed
Problem outcome: unknown
Public search query: agent timed out when airflow REST API hung on dag run status poll, p
Problem outcome: unknown
Gives agents a playbook for Airflow DAG runs that never finish: bounded waits, detecting the wedged task, and escalating instead of polling forever. Use when an agent waits on a DAG run that sticks in running. Not for runs that fail fast.
Fixes Airflow scheduler stalls from SQLAlchemy pool exhaustion: pool sizing versus scheduler threads and database capacity. Use when the scheduler sticks with pool timeout errors. Not for slow queries on a healthy pool.
Tunes Airflow sensors whose poke interval is wrong for the wait: balancing poll frequency against external system load. Use when sensors time out or hammer the sensed system. Not for sensors that fail on the first poke.
Fixes an agent's scheduled notebook run hitting a 2-hour Airflow timeout: the notebook outgrew the DAG's budget. Measure, then raise the timeout or split the work. For agent builders.