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Is your feature request related to a problem? Please describe.
I would like to know time taken & success/failure ration for a service call from lambda function.
Describe the solution you'd like
Currently Metrics annotation only supports capturing cold start, it would be really if we can get time/success/failure count for the method being executed(similar to DCM/DLM :)).
Describe alternatives you've considered
Currently we are using Guava's stopwatch & manually instrumenting the code.
The text was updated successfully, but these errors were encountered:
Hi @vigneshtdev Thanks for opening the issue. Since this belongs to core utility Metrics, I would like to hear thoughts from Python folks as well. Moving this to roadmap for further discussion.
@heitorlessa Thoughts on this? Adding built in support for Metrics annotation/decorator to capture success/failure/duration metrics conditionally like cold start
One reason I can think of is with the default metrics provided by lambda it's difficult to distinguish between failures occurring in static block & failures in handleRequest
Errors – The number of invocations that result in a function error. Function errors include exceptions thrown by your code and exceptions thrown by the Lambda runtime. The runtime returns errors for issues such as timeouts and configuration errors.
Also in case these annotations can be used on non-handleRequest methods then we can analyse individual service calls easily
Is your feature request related to a problem? Please describe.
I would like to know time taken & success/failure ration for a service call from lambda function.
Describe the solution you'd like
Currently Metrics annotation only supports capturing cold start, it would be really if we can get time/success/failure count for the method being executed(similar to DCM/DLM :)).
Describe alternatives you've considered
Currently we are using Guava's stopwatch & manually instrumenting the code.
The text was updated successfully, but these errors were encountered: