Adjust sentry fingerprinting and Add metrics for API call durations and errors #157
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Sentry groups events by fingerprint. This change customizes the fingerprinting for NSX-T-related errors to avoid generating separate events for each API call with a unique ID. The replace operation does not work in-place, so the adjustment ensures consistent grouping.
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This commit introduces Prometheus metrics to capture details about outgoing API calls, including their duration and status codes. Additionally, a separate to track request-level errors such as connection timeouts and network failures. These metrics provide better observability into API behavior and help identify performance or reliability issues.
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| for resource_type, path in paths: | ||
| classified = RetryPolicy._get_resource_type(path) | ||
| print(resource_type, classified) |
Collaborator
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print() could be removed
| new_path = RetryPolicy._create_sentry_fingerprint(path=path, placeholder="<uuid>") | ||
| resource = RetryPolicy._get_resource_type(path) | ||
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| if "histogram:nsxv3_agent_api_calls" == str(metric): |
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You could use if str(RetryPolicy.API_CALLS) == str(metrics): or probably even without the str()
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| @staticmethod | ||
| def _update_metric(metric, **kwargs): | ||
| path = kwargs.get("path", '') |
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You have a lot of kwargs.get() with default arguments. How about removing the **kwargs and add them all explicitly with a default? It doesn't really look like you need the variability unspecific arguments.
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Adjust fingerprinting to reduce event noise for NSX-T API calls
Sentry groups events by fingerprint. This change customizes the fingerprinting
for NSX-T-related errors to avoid generating separate events for each API call
with a unique ID. The replace operation does not work in-place, so the adjustment
ensures consistent grouping.
Add metrics for API call durations and errors
This commit introduces Prometheus metrics to capture details about outgoing
API calls, including their duration and status codes. Additionally, a separate
to track request-level errors such as connection timeouts and network failures.
These metrics provide better observability into API behavior and help identify
performance or reliability issues.