Weekly deployment summary

Q: What are the DORA metrics?

DORA (DevOps Research and Assessment) tracks deploy frequency, lead time for changes, change failure rate, and time to restore. Together they're the most widely used measure of engineering team performance.

Q: What is a good deployment frequency?

Elite teams deploy multiple times per day. High-performing teams deploy weekly or daily. The right cadence depends on architecture and risk tolerance — what matters more is steady frequency with low change-failure rate.

Weekly automated deployment summary. AI tracks deploy frequency, lead time, change-failure rate, and rollback count from your CI / CD and GitHub data.

Use this template How automations work

Runs weekly Scheduled Delivered to Slack, Email

Weekly deployment summary

Active

Trigger

Runs weekly

Instructions

Summarize engineering deployments from the past 7 days.

Delivery

Slack · Email

Example output

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

Weekly deployment summary Runs weekly · Sent to Slack, Email

Sample output

DORA metrics, this week

Deploys

41 +5 (36)

Lead time

31h -3h (34h)

Change failure

4.9% -0.4 pts (5.3%)

MTTR

22 min -5 min (27 min)

DORA metrics — this week

Deploys: 41 (vs. 36 trailing-4-week avg).
Lead time: 31 hours (target <48h) ✓
Change failure rate: 4.9% (target <5%) ✓
MTTR: 22 minutes (target <30m) ✓

Incidents. Two rollbacks this week, both within 30 minutes of deploy. One real bug (P2, source picker), one false positive (alarm threshold too tight, retuning).

Bottleneck watch. api-gateway lead time is up 3 weeks in a row (8h → 14h → 22h) — likely review latency on the platform team. Worth a Monday sync.

The prompt

Copy, paste, customize.

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

Instructions

Summarize engineering deployments from the past 7 days.

Cover the four DORA metrics:

**Deploy frequency.** Total deploys, by service, vs. last week.
**Lead time for changes.** Median time from PR open → production.
**Change failure rate.** Percent of deploys that resulted in a rollback or incident.
**Time to restore.** Median time from incident open → resolution.

Add:

**Major releases.** Features or large changes that went live, with the PR / issue links.

**Rollbacks.** Any deploy that was rolled back, with the cause in one sentence.

**At risk services.** Services whose lead time or failure rate is trending worse for 3+ weeks.

Numbers first.

Data sources