val-lavrentiev opened a new issue, #51569:
URL: https://github.com/apache/airflow/issues/51569
### Apache Airflow version
3.0.1
### If "Other Airflow 2 version" selected, which one?
_No response_
### What happened?
A failed task instead of being restarted stays forever in the "queued"
state. Scheduler according to the logs tries to schedule it only once (for some
unknown reason):
```
Jun 10 10:51:26 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:26.588+0000] {_client.py:1026} INFO - HTTP Request: PUT
https://airflow-server.com/execution/task-instances/01975940-1bb5-7690-a48f-7b09540f8373/heartbeat
"HTTP/1.1 204 No Cont>
Jun 10 10:51:31 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:31.498+0000] {scheduler_job_runner.py:2128} INFO - Adopting
or resetting orphaned tasks for active dag runs
Jun 10 10:51:31 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:31.614+0000] {_client.py:1026} INFO - HTTP Request: PUT
https://airflow-server.com/execution/task-instances/01975940-1bb5-7690-a48f-7b09540f8373/heartbeat
"HTTP/1.1 204 No Cont>
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:36.795+0000] {_client.py:1026} INFO - HTTP Request: PUT
https://airflow-server.com/execution/task-instances/01975940-1bb5-7690-a48f-7b09540f8373/heartbeat
"HTTP/1.1 204 No Cont>
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler | 2025-06-10
10:51:36 [debug ] Received message from task runner [supervisor]
msg=RetryTask(state='up_for_retry', end_date=datetime.datetime(2025, 6, 10, 10,
51, 36, 773750, tzinfo=TzInfo(UTC)), rendered_m>
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:36.839+0000] {_client.py:1026} INFO - HTTP Request: PATCH
https://airflow-server.com/execution/task-instances/01975940-1bb5-7690-a48f-7b09540f8373/state
"HTTP/1.1 204 No Conten>
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler | 2025-06-10
10:51:36 [debug ] Received message from task runner [supervisor]
msg=SetRenderedFields(rendered_fields={'op_args': [], 'op_kwargs': {},
'bash_command': 'direnv allow /data/ephemeral/airflow-ap>
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:36.857+0000] {_client.py:1026} INFO - HTTP Request: PUT
https://airflow-server.com/execution/task-instances/01975940-1bb5-7690-a48f-7b09540f8373/rtif
"HTTP/1.1 404 Not Found"
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler | 2025-06-10
10:51:36 [warning ] Server error [airflow.sdk.api.client]
detail=None
Jun 10 10:51:36 ip-10-0-0-77 start.sh[1369546]: scheduler | 2025-06-10
10:51:36 [error ] API server error [supervisor]
detail={'detail': 'Not Found'} message='Not Found' status_code=404
Jun 10 10:51:51 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:51:51.976+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:52:22 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:52:22.126+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:52:52 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:52:52.272+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:53:23 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:53:23.490+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:53:53 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:53:53.628+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:54:24 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:54:24.826+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:54:54 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:54:54.965+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:55:26 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:55:26.180+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:55:57 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:55:57.145+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:56:27 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:27.533+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:56:31 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:31.570+0000] {scheduler_job_runner.py:2128} INFO - Adopting
or resetting orphaned tasks for active dag runs
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:49.831+0000] {scheduler_job_runner.py:450} INFO - 1 tasks up
for execution:
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
<TaskInstance:
cdp_profiles_send_to_dest.run_export_json_and_send_to_destination
scheduled__2025-06-09T07:00:00+00:00 [scheduled]>
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:49.831+0000] {scheduler_job_runner.py:522} INFO - DAG
cdp_profiles_send_to_dest has 0/16 running and queued tasks
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:49.832+0000] {scheduler_job_runner.py:661} INFO - Setting the
following tasks to queued state:
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
<TaskInstance:
cdp_profiles_send_to_dest.run_export_json_and_send_to_destination
scheduled__2025-06-09T07:00:00+00:00 [scheduled]>
Jun 10 10:56:49 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:49.834+0000] {scheduler_job_runner.py:767} INFO - Trying to
enqueue tasks: [<TaskInstance:
cdp_profiles_send_to_dest.run_export_json_and_send_to_destination
scheduled__2025-06-09T07:00:00+0>
Jun 10 10:56:58 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:56:58.093+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:57:29 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:57:29.518+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:57:59 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:57:59.976+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
Jun 10 10:58:31 ip-10-0-0-77 start.sh[1369546]: scheduler |
[2025-06-10T10:58:31.508+0000] {dag.py:2509} INFO - Setting next_dagrun for
content_classifier_evaluation to 2025-06-09 00:00:00+00:00,
run_after=2025-06-11 00:00:00+00:00
```
### What you think should happen instead?
After a fail a task is restarted.
### How to reproduce
We use default parameter apart from:
```
export AIRFLOW_HOME={{ airflow_v2_home }}
export AIRFLOW__API__BASE_URL=https://airflow-server.com
export AIRFLOW__CORE__EXECUTOR=LocalExecutor
export AIRFLOW__CORE__LOAD_EXAMPLES=false
export AIRFLOW__CORE__PARALLELISM=32
export AIRFLOW__CORE__SIMPLE_AUTH_MANAGER_ALL_ADMINS=True
export AIRFLOW__CORE__DAGS_FOLDER=/apps/airflow/dags
export
AIRFLOW__SECRETS__BACKEND=airflow.providers.amazon.aws.secrets.secrets_manager.SecretsManagerBackend
export AIRFLOW__SECRETS__BACKEND_KWARGS='{"region_name": "eu-west-1",
"connections_prefix": "", "variables_prefix": "", "config_prefix": ""}'
export AIRFLOW__SCHEDULER__CREATE_CRON_DATA_INTERVALS=True
export AIRFLOW__DATABASE__SQL_ALCHEMY_CONN=postgresql://{{
airflow_v2_postgres_user }}:{{ airflow_v2_postgres_password }}@{{
airflow_v2_postgres_host }}/{{ airflow_v2_postgres_database }}
# workaround for airflow v3.0.1 to avoid scheduler jwt expiration errors
export AIRFLOW__API_AUTH__JWT_CLI_EXPIRATION_TIME=315360000
export AIRFLOW__API_AUTH__JWT_EXPIRATION_TIME=315360000
export AIRFLOW__EXECUTION_API__JWT_EXPIRATION_TIME=315360000
export AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK=True
```
We also has an issue with JWT token expiration errors which we for now
circumvented with the longer expiration time setting (for this perhaps we can
raise a separate issue later)
Installation script on ec2 instance (arm, Ubuntu):
```
. /etc/profile.d/nix.sh
&& . /etc/profile.d/Z50-devbox.sh
&& devbox global add uv overmind direnv s5cmd pixi
&& mkdir -p /apps/airflow/apps
&& mkdir -p /apps/airflow/dags
&& uv venv /apps/airflow/.venv --python 3.11
&& uv pip install --python {{ airflow_v2_home }}/.venv/bin/python
--constraint
https://raw.githubusercontent.com/apache/airflow/constraints-3.0.1/constraints-3.11.txt
'apache-airflow[amazon,slack,standard]'
asyncpg
psycopg2-binary
```
### Operating System
Ubuntu 22.04.5 LTS
### Versions of Apache Airflow Providers
_No response_
### Deployment
Official Apache Airflow Helm Chart
### Deployment details
_No response_
### Anything else?
_No response_
### Are you willing to submit PR?
- [x] Yes I am willing to submit a PR!
### Code of Conduct
- [x] I agree to follow this project's [Code of
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
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