SUMMARIZATION
Post-Deploy Honeycomb Trace Impact Summary on GitHub PRs
When a deploy webhook fires, compares Honeycomb trace metrics before and after the release, summarizes the latency and error impact with OpenAI.
How it runs
The automated pipeline, trigger to output.
- TriggerDeploy webhook arrives with release SHA and PR numberHTTP webhook
- ActionQuery Honeycomb for pre- vs post-deploy trace metricsHoneycomb
- LogicCheck post-deploy traffic is sufficient to judge
- ActionWrite before/after impact verdict with deltasOpenAI
- OutputPost impact summary as GitHub PR commentGitHub
What it does
Triggered by a deploy event, it waits for a short bake window, then asks Honeycomb how the just-shipped release moved trace latency and error rates compared to the pre-deploy baseline. OpenAI turns the comparison into a clear ship-verdict, and the summary is posted as a comment on the GitHub PR that triggered the deploy.
When to use it
Use it to close the loop between merging code and seeing its real production impact. Instead of hunting through Honeycomb after every release, the PR itself gains a comment saying whether the change was clean, neutral, or a regression.
How it works
- 1A deploy webhook arrives carrying the release SHA and PR number.
- 2Honeycomb is queried for affected-service metrics across the pre- and post-deploy windows.
- 3A logic step decides whether enough post-deploy traffic has accrued to judge impact.
- 4OpenAI writes a short before/after verdict with the key latency and error deltas.
- 5The summary is posted as a comment on the originating GitHub pull request.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect GitHubRepos, issues, pull requests, actions.
- 4Connect HTTP webhookTrigger any URL on agent actions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
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