DevOps Metrics for Jira — Documentation

All four DORA metrics on any Jira dashboard — calculated from the Jira data you already have, no CI/CD setup.

1. Overview

DevOps Metrics for Jira puts the four key delivery metrics from the DORA research (DevOps Research & Assessment) on any Jira dashboard:

• Deployment frequency — how often you ship,
• Lead time for changes — how long work takes from start to done,
• Change failure rate — the share of releases that caused problems,
• Time to restore (MTTR) — how quickly you recover when something breaks.

Everything is calculated from Jira work items — releases, status transitions, bugs and incident tickets. No CI/CD integration, no second product. Every number carries a DORA benchmark band (Elite / High / Medium / Low), a plain-language sentence, and a “How we calculate it” popup.

2. Quick start

Step 2 — Pick your project

Open the gadget's Edit (pencil) menu. Step 1 of the wizard lists the projects you can browse — pick one (Pro: up to 10, combined into one view).

Step 3 — Accept the recommendation

The wizard inspects your project. If it finds released Jira versions, it recommends Releases as your deployment definition — including how many it found. Click “Use recommended settings” and you're done; the first analysis runs in the background and the tiles fill with your real numbers.

3. Configuration

What counts as a deployment?

• Releases (default, recommended): every Jira version marked as released with a release date counts as one deployment.
• Issues reaching a status: every issue that first reaches one of the statuses you pick counts as one deployment — for teams that don't maintain releases.

Advanced PRO

• Incident types: which issue types count as incidents for Time to restore (default: bug/incident-like types).
• Sub-tasks: include or exclude them from lead time & throughput (default: excluded).

AI rollout (optional)

Step 3 of the wizard powers the AI Impact tab: rollout date, the labels that mark AI-assisted issues, which AI signals to use, and up to five custom chart markers.

Everything can be changed later — reopen the wizard any time via the gadget's ••• / pencil menu. Changing definitions triggers a clean recalculation.

4. How the metrics are calculated

Buckets are ISO weeks; display periods (30 days … 12 months) aggregate weekly data. Durations use medians (P50) — robust against outliers.

Benchmark bands follow the published DORA research (the classic Elite/High/Medium/Low model). The thresholds are fixed on purpose — consistent yardsticks beat configurable ones.

5. Data quality & exclusions

The footnote under every view shows what the numbers are based on — e.g. “Based on 142 completed issues · 12 releases · 8 excluded”. Click Details for the full breakdown:

• Issues that never passed through In progress (lead time not measurable),
• issues with inconsistent dates, and sub-tasks (if excluded),
• released versions without a release date,
• how each change-failure bug was attributed (version link vs time proximity).

6. AI Impact PRO

Set your AI rollout date (Copilot, Rovo, Claude, Cursor…) and the AI Impact tab compares equal periods before and after on all four metrics, with a deterministic plain-language verdict (rule-based — no LLM). A second view compares AI-involved issues vs other issues completed in the same period.

AI involvement is detected via three configurable signals (OR-combined), each individually switchable:

• App-account activity — a Rovo agent, Automation for Jira or another app touched the issue's workflow,
• labels — defaults: ai-assisted, copilot, rovo,
• issue types — if your team maintains an “AI task” type.

7. The Metric Card gadget PRO

The second gadget, DORA Metric Card, shows a single metric big and readable from across the room — value, benchmark band, trend arrow and sparkline. Built for TV dashboards: put four cards side by side and the whole floor sees where delivery stands. It inherits the definitions you configured in the Overview gadget for the same project.

8. Exports PRO

• PNG — a presentation-ready report image of the overview (or the current trend chart) for the QBR deck. One click, no dialog.
• CSV — the weekly aggregates behind the charts, for your own analysis.
• Copy as text — a Markdown summary table including the plain-language sentences, ready to paste into Confluence, Slack or e-mail.

9. Free vs Pro

Free covers sites with up to 10 users; larger sites get a free trial. See the Marketplace listing for per-user pricing.

10. FAQ & Troubleshooting

The gadget shows “Sample data”

That's the built-in demo shown before configuration. Open Edit (pencil), pick your project, done.

Deployment frequency is zero

In Releases mode the app counts versions marked released (with a release date). If your team doesn't maintain releases, switch the deployment definition to “Issues reaching a status” in the wizard.

“Analyzing your project history…” takes a while

The first run reads up to 12 months of completed issues (capped at the most recent 10,000). This happens once; afterwards the gadget loads instantly and refreshes incrementally.

Lead time shows “—” or excludes many issues

Lead time needs a transition into an In progress status. Issues created straight into Done can't be measured — they still count for throughput, and the Details popup lists them.

Change failure rate seems high/low

Check the Details popup: it shows how bugs were attributed to releases (fix/affected version vs. 14-day time proximity). Setting affected versions on bugs makes CFR most accurate. With fewer than 5 releases in the period the tile adds a “treat as directional” note.

“You don't have access to this project's data”

The app enforces Jira project permissions per viewer: you only see metrics for projects you can browse. Ask your Jira admin for access, or pick another project.

The AI Impact tab asks for a date even though I saved one

Make sure the date was set in step 3 of the wizard and saved. The date picker on the tab itself is a quick preview only.

11. Support