Daily error monitoring

Q: 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.

Q: 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.

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)

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

No P0s open.

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