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# Summary
We sometimes run into errors and having these traced makes it easier to
know which ones have failed for later analysis.
This pull request enhances the `queue_exception_handling` function in
`pipeline.py` by integrating OpenTelemetry tracing and adding detailed
metrics to improve observability of task queue error processing.
### Observability Enhancements:
* Added OpenTelemetry tracing to `queue_exception_handling`
* Introduced metrics to track task queue processing, including:
- Total number of tasks (`mck.agent.queue.tasks_total`).
- Count of tasks with exceptions (`mck.agent.queue.exceptions_count`).
- Success rate of tasks (`mck.agent.queue.success_rate`).
- Types of exceptions encountered (`mck.agent.queue.exception_types`).
- Boolean flag indicating if exceptions were found
(`mck.agent.queue.has_exceptions`)
* Updated logging to provide more granular details about exceptions
encountered in the task queue
## Proof of Work
<!-- Enter your proof that it works here.-->
## Checklist
- [ ] Have you linked a jira ticket and/or is the ticket in the title?
- [ ] Have you checked whether your jira ticket required DOCSP changes?
- [ ] Have you checked for release_note changes?
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---------
Co-authored-by: Anand <[email protected]>
Co-authored-by: Anand Singh <[email protected]>
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