ENGINEERING
Post-Merge Log Volume Recheck After Downsampling PR
After a log-level PR merges, waits a day then re-queries Axiom to confirm the targeted stream's volume actually dropped.
How it runs
The automated pipeline, trigger to output.
- TriggerLabeled log-noise PR mergesGitHub
- ActionRe-query Axiom for post-merge volumeAxiom
- LogicCompare drop against expected reduction
- ActionPost verification comment on PRGitHub
- OutputAlert Slack if volume did not fallSlack
What it does
Closes the loop on log-noise fixes. When a downsampling or log-level PR merges, it measures whether the change had the intended effect by comparing the stream's volume before and after, so silent no-op fixes get caught.
When to use it
Use it whenever you ship log-noise PRs and want proof they worked. It prevents the common failure where a level change targets the wrong logger or gets overridden by config and noise quietly continues.
How it works
- 1A GitHub merge event for a PR labeled `log-noise` triggers the workflow.
- 2It records the targeted stream and its pre-merge baseline from the PR body.
- 3After a built-in delay it re-queries Axiom for the same stream's post-merge volume.
- 4A logic step compares the drop against the expected reduction.
- 5It posts a verification comment on the PR; if volume did not fall, it pings Slack so someone reopens the fix.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect AxiomLog streams, queries, dashboards.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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