ENGINEERING

Latency regression triage: Honeycomb + Sentry digest to Slack with file-or-skip decision

On each slow-trace alert, correlates Honeycomb timing with live Sentry errors and posts a triage card to Slack with interactive buttons so an on-call engineer decides whether…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHoneycomb slow-trace alert (webhook)Honeycomb
  • ActionFetch correlated Sentry errors for the windowSentrySentry
  • LogicBranch on error-linked vs latency-only
  • ActionPost triage card with File/Snooze/Dismiss to SlackSlack
  • OutputOn File: open GitLab issue with joined contextGitLabGitLab

What it does

Keeps a human in the loop. Instead of auto-filing tickets for every latency blip, this workflow assembles the correlated Honeycomb + Sentry evidence into a Slack triage card and lets the on-call engineer choose: file a GitLab issue, snooze, or dismiss as noise. Only confirmed regressions become tickets.

When to use it

Use when your latency triggers are noisy enough that auto-ticketing would bury the team, but you still want the correlation work done up front. Best for on-call rotations that want a fast yes/no decision with full context attached.

How it works

  1. 1A Honeycomb trigger fires on a trace that breaches the latency budget.
  2. 2The workflow fetches matching Sentry errors for the service and time window.
  3. 3It branches on whether any correlated errors were found, tagging the card as 'error-linked' or 'latency-only'.
  4. 4A Slack message posts the trace summary, top errors, and File / Snooze / Dismiss actions.
  5. 5On 'File', a GitLab issue is opened with the same joined context and the deciding engineer assigned.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HoneycombDistributed traces and queries.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect GitLabRepos, MRs, pipelines, registry.
  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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