ENGINEERING
Weekly Top-Offenders Query Digest to Slack
Every Monday, ranks production queries by total time consumed over the past week from pg_stat_statements and posts a prioritized Slack digest of the top time-sinks…
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly Monday schedule
- ActionRead total time per queryPostgres
- ActionLoad last week snapshotPostgres
- LogicRank and tag risers and new entrants
- OutputPost top-offenders digest to SlackSlack
- ActionSave this week snapshotPostgres
What it does
It gives the team a weekly leaderboard of where database time actually goes. Each Monday it reads `pg_stat_statements`, ranks normalized queries by total execution time (calls x mean), compares each against last week's totals, and posts a Slack digest. The message highlights the biggest time-sinks, callouts for queries trending worse, and any new entrants to the top 20.
When to use it
Use this for proactive performance hygiene rather than firefighting. It keeps the highest-leverage optimization targets visible so the team picks the right work, not just whatever paged most recently.
How it works
- 1A weekly schedule fires Monday morning.
- 2Read `pg_stat_statements` total_exec_time and calls per query.
- 3Load last week's snapshot and compute week-over-week deltas.
- 4A logic step ranks by total time and tags risers and new entrants.
- 5Post the formatted top-offenders digest to Slack.
- 6Reset stats and save this week's snapshot as next baseline.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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