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Daily error monitoring

An AI-powered daily error report. Reads Sentry / Datadog every morning and tells you what broke yesterday — prioritized by user impact.

Use this template How automations work
Runs daily Scheduled Delivered to Slack
Daily error monitoring
Active

Trigger

Runs daily

Instructions

Generate a daily error monitoring report covering the past 24 hours.

Delivery

Slack

Example output

A realistic sample of what this automation delivers — your version draws on your data.

Daily error monitoring Runs daily · Sent to Slack
Sample output

Errors yesterday: 412 events, 38 affected users (vs. 401/42 average).

New issues (P1)

  • TypeError: Cannot read properties of undefined (reading 'rowId') — automations editor, 14 events, 9 users. First seen at 2:14 AM after the v1.42.0 deploy. Owner: @sam.
  • Stripe.WebhookSignatureError — billing, 3 events, 3 customers. Likely related to the new secret rotation last night.

Regressions

  • QueryTimeoutError: postgres is back, last seen Apr 4. 22 events on the chat surface, all on dashboards over 10M rows.

Top by impact (last 7 days)

  1. AbortError: signal aborted — 142 users, mostly transient.
  2. AISourceConnectError — 38 users, owner @amelia, fix landing today.

No P0s open.

Generated by Basedash AI from your connected data sources Engineering
The prompt

Copy, paste, customize.

Drop this into a Basedash automation. AI fills in the numbers from every source you've connected.

Instructions 
Generate a daily error monitoring report covering the past 24 hours.

Cover:

**Top errors.** Five errors with the most users affected. For each: error name, count, users affected, first-seen, last-seen, link to Sentry / Datadog.

**New errors.** Errors that first appeared in the last 24 hours. Highlight any that affected > 100 users.

**Regressions.** Errors that previously resolved have re-appeared.

**Critical paths.** Any error in checkout, signup, login, or core API endpoints — even if user count is low.

**Action.** Suggest the single most impactful fix.

Keep it under 250 words. The on-call engineer should be able to read it on their phone.
Data sources

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Basedash automations read across every connected source in a single run. These are the ones this template tends to use most.

Frequently asked questions

How do you prioritize production errors?

By user impact (how many users hit the error) and severity (does it block a critical path like signup or checkout). New errors and regressions get extra priority because they're usually caused by a recent deploy.

How can I summarize Sentry alerts daily?

Connect Sentry (or Datadog) to Basedash and schedule a daily AI automation. It reads the last 24 hours of errors, ranks them by impact, and writes a 250-word digest delivered to your on-call channel each morning.

Keep going

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