TICKET MANAGEMENT
Hourly recount of affected users across clustered Sentry issues
On a schedule, this aggregates the unique-user totals from every Sentry issue linked to each umbrella bug, writes the fresh total to Postgres.
How it runs
The automated pipeline, trigger to output.
- TriggerHourly schedule
- ActionRead umbrella-to-issue mappingsPostgres
- ActionSum unique users per umbrella from SentrySentry
- ActionWrite recomputed totals + flag big moversPostgres
- OutputPost affected-user digest to SlackSlack
What it does
Recomputes the true affected-user count for each umbrella bug by summing the unique users across all of its clustered Sentry issues. It keeps your impact numbers accurate even as new crashes attach to a cluster, and surfaces which umbrellas are growing fastest.
When to use it
Use it when affected-user counts drift because they were only ever incremented on first link, not recounted. A scheduled rollup gives leadership a trustworthy severity ranking each hour.
How it works
- 1A schedule fires every hour.
- 2The flow reads the umbrella-to-Sentry-issue mapping from Postgres.
- 3For each umbrella it queries Sentry for the current unique-user count of every linked issue and sums them.
- 4It writes the recomputed total back to Postgres and flags umbrellas whose count jumped beyond a threshold since the last run.
- 5It posts a digest to Slack ranking umbrellas by affected users, highlighting the fastest risers.
Set it up
What you configure once, before turning it on.
- 1Connect SentryErrors, performance, releases.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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