Deployment frequency, lead time, change failure rate, and release risk — computed from the data your teams already produce. Current enough to act on, not a spreadsheet describing last quarter.
ArcRelease turns engineering delivery metrics into something you can act on before the quarter ends. Deployment frequency, lead time, change failure rate, and release risk are computed from data your teams already produce across 8 connected tools — including Jira, GitHub, and PagerDuty — so nobody rebuilds a DORA spreadsheet by hand.
I get asked why we are slow, and the honest answer is that I do not know which stage the time is going into.
Every team reports green until the quarter ends, and then I find out change failure rate doubled in one service.
My DORA metrics live in a spreadsheet somebody rebuilds by hand every month. By the time I read them, they describe the past.
Delivery metrics compute themselves from tools your teams already use, broken out by service and by team rather than averaged into meaninglessness. You see the change failure rate move in the week it moves, and you can name the release that caused it instead of discovering the trend in a quarterly review.
Gaja does not hand you a risk score and ask you to trust it. Each GO, NO-GO or CONDITIONAL verdict cites the signals behind it: which dependency is blocking, which gate is unsigned, which freeze is active, and what the release history says.
From systems your teams already use. Deployment frequency and lead time come from your CI and source control, change failure rate comes from correlating deploys with PagerDuty or incident records, and release risk comes from Gaja scoring each release against dependency, gate, and incident history. Nobody fills in a form to produce them.
They follow the DORA definitions, with the caveat every honest vendor should state: lead time and change failure rate depend on how cleanly your teams link work to deploys. ArcRelease shows the linkage coverage behind each number, so you know whether a metric rests on 95 percent of your releases or on half of them.
Not by design. Metrics resolve to services and releases, not to individuals, and there is no per-developer leaderboard. Delivery metrics used as a performance ranking reliably produce gamed numbers and worse engineering, so the product deliberately does not make that easy.
Continuous. ArcRelease ingests from webhooks and APIs as work happens, so the trend you look at on Tuesday includes Monday. The point is that the number arrives while the quarter is still changeable, rather than in a deck assembled by hand three weeks after the behaviour you would want to correct.
Tell us about your release process. Connect your stack in ten minutes, run a Gaja preflight on a real release, and see the reasons behind the verdict.
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