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Analytics

This guide steps you through instrumenting your code with Sentry's 3rd-party analytics infrastructure.

Big Query

Send events to Big Query and run queries in Redash.

Create a new file in src/sentry/analytics/events using the key in snake case as the filename.

In this file, you will need to register the event with attributes (for validation).

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from sentry import analytics

class CodeownersAssignment(analytics.Event):
    type = "codeowners.assignment" # replace with your key

    attributes = (
        analytics.Attribute("organization_id"),
        analytics.Attribute("project_id"),
        analytics.Attribute("group_id"),
        # more attributes
    )

analytics.register(CodeownersAssignment)

Now in the code that you want instrumented, use the analytics.record function with the registered key.

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from sentry import analytics

analytics.record(
    "codeowners.assignment", # replace with your key
    organization_id=project.organization_id,
    project_id=project.id,
    group_id=group.id,
    # more attributes
)

Metrics

Track aggregrate stats with Metrics. For example, this can be used to track aggregate response codes for an endpoint.

Import the metrics library and use the metrics.inc function. The key needs to be unique.

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from sentry.utils import metrics

metrics.incr(
    "codeowners.create.http_response", # needs to be unique
    sample_rate=1.0,
    tags={"status": status},
)

If you don't put a sample rate, you get 1 in 10 events. If the service is expected to have low traffic, we can start with a sample rate of 1.

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