ENGINEERING

Route Sentry error spikes to deduplicated Linear bugs by CODEOWNERS

When a Sentry issue's event rate spikes, finds or creates a single Linear bug for that fingerprint and assigns it to the owning team resolved from the repo's CODEOWNERS file.

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry issue event-rate spike alertSentrySentry
  • ActionFetch issue culprit path + fingerprintSentrySentry
  • LogicSearch Linear for existing fingerprint issueLinearLinear
  • ActionResolve owning team from CODEOWNERSGitHubGitHub
  • LogicBranch: create new vs. update existing
  • OutputCreate or update Linear bug with team assigneeLinearLinear

What it does

Turns noisy Sentry alert spikes into exactly one actionable Linear bug per error fingerprint, routed to the team that owns the failing code path according to your GitHub CODEOWNERS file. No duplicate tickets, no manual triage.

When to use it

Use it when on-call engineers are drowning in repeated Sentry alerts for the same crash, or when bugs land in a central inbox and someone has to hand-assign each one. Best for teams with a clear CODEOWNERS mapping and a Linear workspace organized by team.

How it works

  1. 1A Sentry alert fires when an issue's event frequency crosses your spike threshold.
  2. 2The flow reads the issue's culprit file path and existing fingerprint metadata.
  3. 3It searches Linear for an open issue tagged with that Sentry fingerprint to decide create-vs-update.
  4. 4It fetches CODEOWNERS from GitHub and resolves the owning team for the culprit path.
  5. 5If no Linear issue exists it creates one (title, stack trace, Sentry link) assigned to that team; otherwise it bumps the occurrence count on the existing one and reopens if closed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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