ktalluri456 opened a new issue, #36736:
URL: https://github.com/apache/beam/issues/36736

   ### What would you like to happen?
   
   ### Is your feature request related to a problem?
   
   Currently, the Python SDK does not provide a standardized way to measure the 
time spent processing timers in streaming pipelines. This information is 
valuable for runners to implement more accurate autoscaling, as a high timer 
backlog can be a significant performance bottleneck. Without a specific metric 
for timer processing, it is difficult for a runner's autoscaling algorithm to 
determine the cause of a backlog and make appropriate scaling decisions.
   
   ### Describe the solution you'd like
   
   To address this, I am implementing state sampling for timer processing time 
in streaming pipelines, as detailed in the design document linked below. This 
involves wrapping the timer processing logic in a 'process-timers' state 
sampler and adding a new counter to track the time spent in this state. This 
will provide a standardized metric that runners can use for more intelligent 
autoscaling.
   
   
   ### Issue Priority
   
   Priority: 2 (default / most feature requests should be filed as P2)
   
   ### Issue Components
   
   - [x] Component: Python SDK
   - [ ] Component: Java SDK
   - [ ] Component: Go SDK
   - [ ] Component: Typescript SDK
   - [ ] Component: IO connector
   - [ ] Component: Beam YAML
   - [ ] Component: Beam examples
   - [ ] Component: Beam playground
   - [ ] Component: Beam katas
   - [ ] Component: Website
   - [ ] Component: Infrastructure
   - [ ] Component: Spark Runner
   - [ ] Component: Flink Runner
   - [ ] Component: Samza Runner
   - [ ] Component: Twister2 Runner
   - [ ] Component: Hazelcast Jet Runner
   - [ ] Component: Google Cloud Dataflow Runner


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