AI & RAG
Weekly digest of recurring failure patterns across postmortems
Clusters the past quarter of indexed postmortems by root-cause similarity and posts a weekly digest of the most repeated failure patterns and their fixes to a Slack channel.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires Monday morning
- ActionPull last 90 days of postmortem embeddings and metadata from PostgresPostgres
- LogicCluster incidents by root-cause similarity, weighted by severity
- ActionWrite up the top recurring failure patterns and their fixesOpenAI
- OutputPost the digest to the reliability Slack channelSlack
What it does
Turns your postmortem archive into a trend report. Once a week it groups recent incidents by how similar their root causes are, ranks the clusters by frequency and severity, and writes up the top recurring failure patterns with the remediations that resolved them.
When to use it
Use it for reliability reviews and sprint planning. Instead of treating each incident as a one-off, the digest surfaces the systemic problems worth a real engineering investment, backed by the specific incidents in each cluster.
How it works
- 1A weekly schedule triggers the flow every Monday morning.
- 2It pulls the last 90 days of postmortem embeddings and metadata from Postgres.
- 3A clustering step groups incidents by root-cause vector similarity and counts cluster size weighted by severity.
- 4The model writes a digest of the top clusters: the pattern, how often it recurred, and what fixed it, with incident links.
- 5The digest posts to the reliability Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect OpenAIModels, embeddings, files.
- 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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