ENGINEERING
Weekly top-offender queries warehoused with deploy attribution
Every week this aggregates the worst query regressions from Honeycomb, attributes each to the deploy that introduced it.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionAggregate top regressed queries from HoneycombHoneycomb
- ActionAttribute each regression to a GitHub deployGitHub
- LogicShape attributed regressions into scorecard rows
- ActionAppend rows to BigQuery for trendingBigQuery
- OutputPublish weekly summary to NotionNotion
What it does
Builds a durable, trended record of query performance instead of one-off alerts. It ranks the week's worst-offending queries, attributes each regression to a deploy, lands the rows in BigQuery for long-term trending, and publishes a readable Notion summary for the team.
When to use it
Use it when leadership or a platform team wants week-over-week visibility into query health and accountability for which releases moved the numbers — the data behind a performance review or SLO retro.
How it works
- 1A weekly schedule kicks off the aggregation.
- 2It queries Honeycomb for the top regressed queries over the past seven days.
- 3For each it matches the GitHub deploy that introduced the slowdown.
- 4A logic step shapes the attributed regressions into scorecard rows.
- 5It appends those rows to a BigQuery table for historical trending.
- 6It publishes a formatted weekly summary to a Notion page for the team.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect BigQueryDatasets, queries, schemas.
- 4Connect NotionPages, databases, comments.
- 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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