open-telemetry / open-telemetry/opentelemetry-python-contrib
PoolExecutor metrics
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1.1k
- Forks
- 1.1k
- Avg merge
- 4d 15h
- Merged PRs (30d)
- 16
Description
What problem do you want to solve?
In python, both sync and async worlds, there are ThreadPoolExecutors and ProcessPoolExecutors.
These executors have a max_workers parameter that constraints them. If an app hits that amount of workers, exhaustion happen which manifests as degraded performance.
Describe the solution you'd like
Having metrics of that can be useful for app developers to identify bottlenecks and determine better capacity
Implementation can be inspired by https://stackoverflow.com/questions/48572648/how-to-monitor-pythons-concurrent-futures-processpoolexecutor
Describe alternatives you've considered
Instrumenting those metrics in my app code
Additional Context
No response
Would you like to implement a fix?
None
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or instrumentation package is named. Start by locating the repository's Python instrumentation entry points and existing metric patterns for synchronous and asynchronous components. The issue is done when the supported executor cases, metric definitions, and validation approach are agreed and implemented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- observability
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100