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FeatureFactory

Engineering Metrics

Engineering metrics that engineers actually trust

Velocity, quality, cycle time and DORA in one place - every number shows its formula, source and time window.

Velocity without vanity

Track throughput and flow using signals engineers actually respect - not story-point theater or lines-of-code leaderboards.

Cycle time, stage by stage

See exactly where work stalls - coding, review, or deploy - so you fix the bottleneck instead of guessing at it.

DORA out of the box

Deployment frequency, lead time for changes, change failure rate and time to restore, computed from your Git and CI data.

Quality alongside speed

Pair velocity with review depth, defect signals and rework so shipping faster never quietly means shipping worse.

Transparent methodology

Every metric shows its formula, data source and time window - no black-box scores you have to defend to skeptical engineers.

AI-aware attribution

Separate AI-generated and human-authored changes so you can measure whether coding agents actually move your numbers.

One place for velocity, quality and flow

Most teams stitch engineering metrics together from four half-configured dashboards, a spreadsheet and a gut feeling. FeatureFactory puts velocity, cycle time, quality and DORA in one place, computed from the same underlying Git and CI data so the numbers actually reconcile.

That means you can answer real questions in one view: are we shipping faster this quarter, and did quality hold? Where is work getting stuck - in coding, in review, or in deploy? Is a specific service dragging down lead time for the whole platform?

Because every chart shares a definition and a source, conversations shift from arguing about whose dashboard is right to deciding what to fix. Explore the full measurement product to see how the signals connect.

Transparent methodology engineers trust

Engineers reject metrics they cannot audit - and they are right to. FeatureFactory shows the formula, data source and time window behind every metric, so anyone can trace a number back to the pull requests and deployments that produced it.

We deliberately avoid black-box "productivity scores" and never rank individuals. Metrics are reported at the team and system level and are meant to drive improvement, not surveillance. If you are new to the space, start with our guide on what the DORA metrics are and how to read them.

The result is a scoreboard your team helps interpret rather than one imposed on them. Curious how it fits together end to end? Take the product tour or read how it works.

Related tools & solutions

Frequently asked questions

The most durable set is the four DORA metrics - deployment frequency, lead time for changes, change failure rate and time to restore - paired with cycle time and a quality signal like rework or review depth. FeatureFactory tracks all of them from your existing Git and CI data, so you get a balanced view of speed and stability rather than a single misleading number.

From our design partners

“We finally have one number for whether the AI-written PRs are actually good. It changed how we staff reviews.”
SStaff EngineerSeries B fintech
“Plan from real signal, ship with agents, then see if the metric moved. That loop is the whole point.”
EEng ManagerDeveloper tools
“The measurement is transparent and the code is ours. That was the dealbreaker with the enterprise options.”
VVP EngineeringHealthcare SaaS

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