DEVOPS

Sentry Error-Spike AI Triage and Dedup to Linear

On a Sentry error-spike alert, an agent reads the stack trace, checks for an existing duplicate issue.

CategoryDevOps
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry error-spike alert firesSentrySentry
  • ActionAgent fetches stack trace and breadcrumbsSentrySentry
  • ActionSearch Linear for duplicate by fingerprintLinearLinear
  • LogicBranch on existing vs new failure
  • ActionComment on existing or file new Linear ticketLinearLinear
  • OutputPost one-line digest to SlackSlack

What it does

When Sentry detects a spike in a new error, this workflow uses an agent to read the stack trace and breadcrumbs, draft a plain-English summary of the likely cause, and decide whether the spike is a duplicate of an existing investigation. Duplicates get a comment; genuinely new failures get a fresh Linear ticket with severity and the Sentry link.

When to use it

Use it when error-spike alerts pile up faster than engineers can read them, and the same root cause keeps spawning redundant tickets. Best for teams using Sentry for error monitoring and Linear for engineering work tracking.

How it works

  1. 1Sentry fires an alert when an issue crosses its spike threshold.
  2. 2The agent fetches the full stack trace, tags, and recent breadcrumbs from Sentry.
  3. 3It searches Linear for an open ticket referencing the same fingerprint or file.
  4. 4A branch decides: existing ticket found vs. new failure.
  5. 5If found, it comments on the Linear ticket with the new occurrence count and timeframe.
  6. 6If new, it files a Linear ticket with an AI root-cause summary, severity, and Sentry link.
  7. 7The final step posts a one-line digest to the team's Slack channel.

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 SlackChannels, DMs, threads, mentions.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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