ENGINEERING

Guard merged PRs against latency regressions with a Honeycomb check

After a pull request merges and deploys, compares post-deploy span latency in Honeycomb to the pre-merge baseline and, if a regression is detected, comments on the PR and opens…

CategoryEngineering
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub pull_request merged event firesGitHubGitHub
  • ActionAfter settle delay, query Honeycomb for post-deploy span latencyHoneycomb
  • LogicCompare to pre-merge baseline; decide if regressed
  • ActionComment latency delta and offending query on the PRGitHubGitHub
  • OutputOpen follow-up GitHub issue linking PR and traceGitHubGitHub

What it does

When a PR merges and the deploy completes, it waits for traffic to flow, then compares the affected endpoint's latency in Honeycomb against the baseline captured before the merge. If latency regressed, it attributes the blame to the PR and reports back on the PR itself.

When to use it

When you want a lightweight performance gate that catches regressions slipping past CI — the kind that only show under real production load. Best for teams that deploy on merge and want accountability tied directly to the PR that shipped the change.

How it works

  1. 1A GitHub `pull_request` merged event fires the workflow.
  2. 2After a settle delay, query Honeycomb for the endpoint's post-deploy p99 and the slowest span breakdown.
  3. 3A logic step compares against the stored pre-merge baseline and decides if the regression exceeds the tolerance.
  4. 4If regressed, comment on the merged PR with the latency delta and the offending query.
  5. 5Open a GitHub issue linking the PR, the trace, and the suspect query for follow-up.

Set it up

What you configure once, before turning it on.

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

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