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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
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
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