Pod name incorrect in RenderedTaskInstanceFields
- Dominant language
- Python
- Stars
- 46.9k
- Forks
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- Avg merge
- 2d 10h
- Merged PRs (30d)
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Description
### Apache Airflow version
2.5.0
### What happened
1. Start a task running with KubernetesExecutor
2. Open the **_/rendered-k8s?dag_id=...&task_id=..._** endpoint in the web UI
3. Copy the metadata.name
4. `kubectl logs pod/$name`
5. `Error from server (NotFound): pods "example-sla-dag-sleep-20-1bc7f8d6892849eaac4642c4177e2eab" not found`
By inspecting the
### What you think should happen instead
Pod name presented in **Rendered K8s Pod Spec** should match the pod name used for running task. Otherwise pod name should not be presented at all.
This is not only a problem for users of the UI, also in the code it can be useful to have the real pod-id.
I'm in the process of troubleshooting strange errors with task adoption, where there are frequently orphaned tasks found. Currently there appears to be no way to go from TI to pod_id, the adoption-process instead goes the other way, using pod labels to find TIs. So for any TIs that were not found in the adoption, one can not find if they at any point have had matching pods or not.
### How to reproduce
_No response_
### Operating System
Ubuntu 22.04
### Versions of Apache Airflow Providers
_No response_
### Deployment
Other Docker-based deployment
### Deployment details
_No response_
### Anything else
_No response_
### 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)
Contributor guide
Research direction
Start with the /rendered-k8s?dag_id=...&task_id=... endpoint and the KubernetesExecutor path that produces Rendered K8s Pod Spec. Compare its metadata.name with the pod actually used for the task, then verify that the UI exposes the real pod name or omits it rather than showing a misleading value.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- kubernetes, python
- Domain
- backend, devops
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100