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Posted to commits@airflow.apache.org by "chAnvesh (via GitHub)" <gi...@apache.org> on 2025/08/13 18:01:19 UTC
[I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
chAnvesh opened a new issue, #54479:
URL: https://github.com/apache/airflow/issues/54479
### Apache Airflow version
main (development)
### If "Other Airflow 2 version" selected, which one?
_No response_
### What happened?
Hi,
**CONFIGURATION**
This is our airflow setup configuration and we are running it inside a K8s pod with Postgres as metadataDB and CeleryExecutor.
airflow info:
Apache Airflow
version | 3.0.2
executor | CeleryExecutor
task_logging_handler | airflow.utils.log.file_task_handler.FileTaskHandler
sql_alchemy_conn | postgresql+psycopg2://user:@localhost:5432/airflow
dags_folder | /opt/airflow/dags
plugins_folder | /opt/airflow/plugins
base_log_folder | /opt/airflow/logs
remote_base_log_folder |
System info
OS | Linux
architecture | x86_64
uname | uname_result(system='Linux', node='*********', release='6.2.0-32-generic', version='#32~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Aug 18 10:40:13 UTC 2', machine='x86_64')
locale | ('en_US', 'UTF-8')
python_version | 3.9.21 (main, Jun 27 2025, 00:00:00) [GCC 11.5.0 20240719 (Red Hat 11.5.0-5)]
python_location | /usr/bin/python3
Tools info
git | NOT AVAILABLE
ssh | OpenSSH_8.7p1, OpenSSL 3.2.2 4 Jun 2024
kubectl | NOT AVAILABLE
gcloud | NOT AVAILABLE
cloud_sql_proxy | NOT AVAILABLE
mysql | NOT AVAILABLE
sqlite3 | NOT AVAILABLE
psql | psql (PostgreSQL) 13.20
Paths info
airflow_home | /opt/airflow
system_path | /home/appuser/.local/bin:/home/appuser/bin:/opt/app/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:usr/bin/psql
We updated the JWT Expiration timers to 1 week to avoid authentication errors.
export AIRFLOW__EXECUTION_API__JWT_EXPIRATION_TIME=604860
export AIRFLOW__API_AUTH__JWT_EXPIRATION_TIME=604860
The Celery executor "visibility_timeout" we see is the default hard-coded value(NOT the default None value described in airflow.cfg or [celery providers documentation](https://airflow.apache.org/docs/apache-airflow-providers-celery/3.11.0/configurations-ref.html#visibility-timeout) )
broker_transport_options | {'visibility_timeout': 84600}
**PROBLEM**
We have a dag which has a 36hrs sleep period task. This task is getting killed after around ~23 hrs. And we do not have any CPU/Memory problems/deficiencies in the pod.
The same task was working perfectly fine in our older Airflow 2.10 release.
**LOGS:**
**SCHEDULER LOGS IN LOCALTIME(UTC+3:00):**
[2025-08-12T13:50:06.745+0300] {scheduler_job_runner.py:450} INFO - 1 tasks up for execution:
<TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [scheduled]>
[2025-08-12T13:50:06.745+0300] {scheduler_job_runner.py:522} INFO - DAG ETL_overload_dag has 0/10 running and queued tasks
[2025-08-12T13:50:06.746+0300] {scheduler_job_runner.py:661} INFO - Setting the following tasks to queued state:
<TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [scheduled]>
[2025-08-12T13:50:06.747+0300] {scheduler_job_runner.py:767} INFO - Trying to enqueue tasks: [<TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [scheduled]>] for executor: CeleryExecutor(parallelism=24)
[2025-08-12T13:50:06.781+0300] {scheduler_job_runner.py:810} INFO - Received executor event with state queued for task instance TaskInstanceKey(dag_id='ETL_overload_dag', task_id='sleep_until_ETL_overload', run_id='manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7', try_number=1, map_index=-1)
[2025-08-12T13:50:06.785+0300] {scheduler_job_runner.py:842} INFO - Setting external_id for <TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [queued]> to 1712b1a1-683d-4aa3-b8e4-b942823d017e
[2025-08-13T13:08:09.917+0300] {scheduler_job_runner.py:2128} INFO - Adopting or resetting orphaned tasks for active dag runs
[2025-08-13T13:13:09.975+0300] {scheduler_job_runner.py:2128} INFO - Adopting or resetting orphaned tasks for active dag runs
[2025-08-13T13:18:10.052+0300] {scheduler_job_runner.py:2128} INFO - Adopting or resetting orphaned tasks for active dag runs
[2025-08-13T13:20:07.481+0300] {scheduler_job_runner.py:810} INFO - Received executor event with state failed for task instance TaskInstanceKey(dag_id='ETL_overload_dag', task_id='sleep_until_ETL_overload', run_id='manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7', try_number=1, map_index=-1)
[2025-08-13T13:20:07.485+0300] {scheduler_job_runner.py:852} INFO - TaskInstance Finished: dag_id=ETL_overload_dag, task_id=sleep_until_ETL_overload, run_id=manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7, map_index=-1, run_start_date=2025-08-12 10:50:06.983034+00:00, run_end_date=None, run_duration=None, state=running, executor=CeleryExecutor(parallelism=24), executor_state=failed, try_number=1, max_tries=10, pool=default_pool, queue=default, priority_weight=22, operator=PythonOperator, queued_dttm=2025-08-12 10:50:06.746562+00:00, scheduled_dttm=2025-08-12 10:50:06.725380+00:00,queued_by_job_id=1, pid=164019
[2025-08-13T13:20:07.486+0300] {scheduler_job_runner.py:925} ERROR - DAG 'ETL_overload_dag' for task instance <TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [running]> not found in serialized_dag table
[2025-08-13T13:20:07.486+0300] {taskinstance.py:1882} ERROR - Executor CeleryExecutor(parallelism=24) reported that the task instance <TaskInstance: ETL_overload_dag.sleep_until_ETL_overload manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7 [running]> finished with state failed, but the task instance's state attribute is running. Learn more: https://airflow.apache.org/docs/apache-airflow/stable/troubleshooting.html#task-state-changed-externally
[2025-08-13T13:20:07.524+0300] {taskinstance.py:2005} INFO - Marking task as UP_FOR_RETRY. dag_id=ETL_overload_dag, task_id=sleep_until_ETL_overload, run_id=manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7, logical_date=, start_date=20250812T105006, end_date=20250813T102007
**CELERY EXECUTOR LOGS (UTC):**
STARTED AT
**2025-08-12 10:50:06.750815** [info ] Task execute_workload[1712b1a1-683d-4aa3-b8e4-b942823d017e] received [celery.worker.strategy]
2025-08-12 10:50:06.959275 [info ] [1712b1a1-683d-4aa3-b8e4-b942823d017e] Executing workload in Celery: token='eyJ***' ti=TaskInstance(id=UUID('01989de6-d041-7eec-80b8-e1c6c5da5a30'), task_id='sleep_until_ETL_overload', dag_id='ETL_overload_dag', run_id='manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7', try_number=1, map_index=-1, pool_slots=1, queue='default', priority_weight=22, executor_config=None, parent_context_carrier={}, context_carrier={}, queued_dttm=None) dag_rel_path=PurePosixPath('overload_control/ETL_overload_dag.py') bundle_info=BundleInfo(name='dags-folder', version=None) log_path='ETL_overload_dag/sleep_until_ETL_overload/manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7/1.log' type='ExecuteTask' [airflow.providers.celery.executors.celery_executor_utils]
2025-08-12 10:50:06.972550 [info ] Secrets backends loaded for worker [supervisor] backend_classes=['EnvironmentVariablesBackend'] count=1
KILLED AFTER
**2025-08-13 10:20:07.013034** [info ] Task execute_workload[1712b1a1-683d-4aa3-b8e4-b942823d017e] received [celery.worker.strategy]
2025-08-13 10:20:07.019987 [info ] [1712b1a1-683d-4aa3-b8e4-b942823d017e] Executing workload in Celery: token='eyJ***' ti=TaskInstance(id=UUID('01989de6-d041-7eec-80b8-e1c6c5da5a30'), task_id='sleep_until_ETL_overload', dag_id='ETL_overload_dag', run_id='manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7', try_number=1, map_index=-1, pool_slots=1, queue='default', priority_weight=22, executor_config=None, parent_context_carrier={}, context_carrier={}, queued_dttm=None) dag_rel_path=PurePosixPath('overload_control/ETL_overload_dag.py') bundle_info=BundleInfo(name='dags-folder', version=None) log_path='ETL_overload_dag/sleep_until_ETL_overload/manual__2025-08-12T10:50:06.216504+00:00_MNRKWnM7/1.log' type='ExecuteTask' [airflow.providers.celery.executors.celery_executor_utils]
2025-08-13 10:20:07.031539 [info ] Secrets backends loaded for worker [supervisor] backend_classes=['EnvironmentVariablesBackend'] count=1
**2025-08-13 10:20:07.051392 [warning ] Server error [airflow.sdk.api.client] detail={'detail': {'reason':
[celery_error.log](https://github.com/user-attachments/files/21759536/celery_error.log)
'invalid_state', 'message': 'TI was not in a state where it could be marked as running', 'previous_state': 'running'}}
2025-08-13 10:20:07.061038 [info ] Process exited [supervisor] exit_code=-9 pid=1877111 signal_sent=SIGKILL
2025-08-13 10:20:07.108748 [error ] Task execute_workload[1712b1a1-683d-4aa3-b8e4-b942823d017e] raised unexpected: ServerResponseError('Server returned error') [celery.app.trace]**
### What you think should happen instead?
The sleep task should have completed successfully after 36hrs and continued to the downstream tasks.
### How to reproduce
1. Run Airflow with Celery executor with the configuration provided
2. Create a task with more than 24 hrs sleep and run it
### Operating System
NAME="Red Hat Enterprise Linux" VERSION="9.6 (Plow)"
### Versions of Apache Airflow Providers
_No response_
### Deployment
Other
### Deployment details
We install airflow using PIP
### Anything else?
Everytime
### Are you willing to submit PR?
- [ ] 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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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "potiuk (via GitHub)" <gi...@apache.org>.
potiuk commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3986442662
@eddiemaru-101 We are unassigning you from this issue as part of our updated [assignment policy](https://github.com/apache/airflow/blob/main/contributing-docs/04_how_to_contribute.rst#contribute-code-changes).
This is not meant to discourage your contribution — quite the opposite! You are still very welcome to work on this issue and submit a PR for it. Simply comment that you are working on it and open a PR when ready.
We found that formal assignments were not working well, as they often prevented others from contributing when the assignee was not actively working on the issue.
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "jason810496 (via GitHub)" <gi...@apache.org>.
jason810496 closed issue #54479: Tasks gets killed with "TI was not in a state where it could be marked as running"
URL: https://github.com/apache/airflow/issues/54479
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "eddiemaru-101 (via GitHub)" <gi...@apache.org>.
eddiemaru-101 commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3190785924
I'd like to work on this issue.
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "boring-cyborg[bot] (via GitHub)" <gi...@apache.org>.
boring-cyborg[bot] commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3184925051
Thanks for opening your first issue here! Be sure to follow the issue template! If you are willing to raise PR to address this issue please do so, no need to wait for approval.
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "jason810496 (via GitHub)" <gi...@apache.org>.
jason810496 commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3995757161
Hi @chAnvesh,
May I ask you a few questions to help reproduce the error?
- If you’re using multiple schedulers, could you please share the following scheduler configuration so I can reproduce the issue?
- How many schedulers and API servers are you using in your deployment?
- The `[scheduler/scheduler_health_check_threshold]` configuration value.
- Which Airflow 2 version was your team using previously that did not encounter this error?
- What is your long‑running use case doing in the task (e.g., simply sleeping, polling for external state, performing actual compute work, etc.)?
Related issues/PRs that come to mind:
- https://github.com/apache/airflow/issues/57618
- https://github.com/apache/airflow/issues/58441
- https://github.com/apache/airflow/pull/60855
As a quick workaround before we identify and fix the root cause: if your task is just sleeping or polling for external state (for example, submitting a long‑running job to an external compute system), I recommend splitting the atomic task into two smaller tasks.
One task is only responsible for submitting the job, and another task waits for the external job to reach a terminal state (success/failure) **using a Trigger** (the task polling external state second _should_ use Trigger to avoid the above error behavior).
Thanks!
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "potiuk (via GitHub)" <gi...@apache.org>.
potiuk commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3272530727
No not really - but if you have similar issue posting detailed description, logs, circumstances and other evidences might help someone to diagnose it, so I encourage you to spend a quality time on describing your case and digging a bit.
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "eddiemaru-101 (via GitHub)" <gi...@apache.org>.
eddiemaru-101 commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3224173936
# Root Cause Analysis – Airflow 3.0 CeleryExecutor Issue in K8s
---
## Overview
After analyzing the logs and code, the root cause of this issue appears not to be related to `visibility_timeout`, but rather to logging configuration changes introduced in Airflow 3.0.
## Key Findings
### 1. Airflow 3.0 Logging Changes
**File:** `providers/celery/src/airflow/providers/celery/executors/default_celery.py` (lines 97-99)
```python
# In order to not change anything pre Task Execution API, we leave this setting as it was (unset) in Airflow2
if AIRFLOW_V_3_0_PLUS:
DEFAULT_CELERY_CONFIG.setdefault("worker_redirect_stdouts", False)
DEFAULT_CELERY_CONFIG.setdefault("worker_hijack_root_logger", False)
```
- These settings did not exist in Airflow 2.x
- Introduced in 3.0+ for Task SDK integration
### 2. The Real Problem
- **Airflow 2.x:** Celery managed all logging (default `True`)
- **Airflow 3.0+:** Changed to `False` for Task SDK compatibility
- **K8s Environment:** This change may cause worker instability for long-running tasks
### 3. Evidence from Logs
```
Process exited [supervisor] exit_code=-9 pid=1877111 signal_sent=SIGKILL
```
- SIGKILL indicates external termination (OS/K8s level)
- Not caused by Celery or Airflow internal timeout
- Likely related to logging handler conflicts in K8s environment
### 4. Core Conclusion
1. Worker fetches a message and starts executing the task
2. Long-running task + logging configuration (`False/False`) → stdout/stderr → IO buffer fills → worker blocks
3. K8s sends SIGKILL → Worker1 dies
4. `visibility_timeout` (24h) → message becomes visible again in the queue
5. Another worker can fetch the message and re-execute the task
**Summary:**
- Root cause of worker death: **stdout/stderr logging → K8s IO buffer saturation**
- `visibility_timeout` only controls **how long the message remains invisible before another worker can pick it up**
- Logging settings (`False/False`) and `visibility_timeout` do **not directly conflict**
## Why It Worked in Airflow 2.10
- Celery fully controlled logging (`worker_hijack_root_logger=True` by default)
- No Task SDK integration
- Stable logging behavior in K8s pods
## Why It Fails in Airflow 3.0.2
- Logging architecture changed for Task SDK compatibility
- K8s log collection may conflict with new logging behavior
- Long-running tasks (e.g., 36-hour tasks) expose instability
## Temporary Workarounds to Test
**Option 1: Override Celery Config**
```
# In airflow.cfg or environment variables
[celery]
extra_celery_config = {
"worker_hijack_root_logger": true,
"worker_redirect_stdouts": true
}
```
**Option 2: Task Time Limits**
```
[celery]
extra_celery_config = {
"task_soft_time_limit": 129600,
"task_time_limit": 133200,
"worker_max_tasks_per_child": 10
}
```
## Questions for Community
1. Has anyone experienced long-running task failures after upgrading to Airflow 3.0+ with CeleryExecutor in K8s?
2. Should logging configuration be environment-aware (e.g., detect K8s and use legacy logging for stability)?
3. Is there a better way to maintain Task SDK compatibility while ensuring stability for long-running tasks in containerized environments?
## Proposed Solutions
Instead of only adjusting `visibility_timeout`, a code change to detect execution environment and adjust logging settings may be needed:
- Detect K8s environment
- Apply appropriate Celery logging configuration
- Maintain Task SDK compatibility where possible
- Provide configuration override options
-"Please provide any helpful feedback.”
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "jason810496 (via GitHub)" <gi...@apache.org>.
jason810496 commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-4131010801
> Related issues/PRs that come to mind:
>
> * [Schedulers race condition when using with kubernetes executor #57618](https://github.com/apache/airflow/issues/57618)
> * [Celery: Running task marked as failed on broker redelivery #58441](https://github.com/apache/airflow/issues/58441)
> * [Raise `TaskAlreadyRunningError` when starting an already-running task instance #60855](https://github.com/apache/airflow/pull/60855) --> likely to fix the issue
> * [Handle executor events in `dag.test()` #41625](https://github.com/apache/airflow/pull/41625) --> potential reason that cause regression
Closed this one as all the above related issues just got resolved.
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "chAnvesh (via GitHub)" <gi...@apache.org>.
chAnvesh commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3271298071
Hello, is there any update on this issue?
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "datasc24 (via GitHub)" <gi...@apache.org>.
datasc24 commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3771911094
Hello !
Did you manage to solve this issue ?
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "chAnvesh (via GitHub)" <gi...@apache.org>.
chAnvesh commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3275347489
Hi, sure, I can try reproducing it again. I added all the relevant information that I thought would be helpful.
Do you suggest providing any specific information for debugging it?
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "ashb (via GitHub)" <gi...@apache.org>.
ashb commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3236014037
I would be extremely surprised if logging changes have anything to do with this
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Re: [I] Tasks gets killed with "TI was not in a state where it could be marked as running" [airflow]
Posted by "potiuk (via GitHub)" <gi...@apache.org>.
potiuk commented on issue #54479:
URL: https://github.com/apache/airflow/issues/54479#issuecomment-3236146199
It does seem like totally hallucinated analysis by AI that is completely wrong.
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