SUMMARIZATION

Daily Sentry Deploy-vs-Deploy Stability Digest to Slack

Runs every morning, compares yesterday's production release against the prior one across Sentry crash-free and error-rate metrics.

CategorySummarization
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily morning schedule
  • ActionIdentify latest and prior releasesSentrySentry
  • ActionFetch release-health stats for bothSentrySentry
  • ActionRank movers and summarize deltasOpenAI
  • OutputPost stability digest to SlackSlack

What it does

Delivers a once-a-day readout of how the latest production release is performing against the one before it. It compares crash-free session rate, new issue count, and error-rate burn, then ranks the biggest movers and explains each in one line so the team starts the day knowing whether the last deploy helped or hurt.

When to use it

Use it when you ship daily and want a standing stability check-in without anyone manually diffing Sentry dashboards. Good for engineering channels that already do async standup.

How it works

  1. 1A scheduled trigger fires each morning.
  2. 2The flow identifies the most recent release and the immediately prior release in Sentry.
  3. 3Release-health and issue stats are pulled for both, and the deltas are computed.
  4. 4An LLM writes a ranked digest highlighting regressions, improvements, and the single largest budget-burn change.
  5. 5The digest is posted to the configured Slack channel with links back to Sentry.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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