Engineering Metrics Glossary

Name: DXSignal
Brand: DXSignal

Plain-English definitions of the metrics behind high-performing engineering teams — how each is measured, what good looks like, and why it matters.

Delivery

How often an organization successfully releases to production.

The four key measures of software delivery performance from the DORA research program.

Turning engineering data into decisions across delivery, quality, and experience.

The time from code committed to code running in production.

The percentage of deployments that cause a failure in production.

Code that is rewritten or deleted shortly after being written.

A composite score of how healthy a pull request is — size, review, and flow.

The estimated cost to fix code issues relative to the cost to build it.

How long it takes to restore service after a production failure.

The time from starting work on a change to delivering it.

The share of cycle time that work is actively being worked on versus waiting.

The time from opening a pull request to merging it, broken into stages.

The amount of work a team completes in a given period.

The number of work items being worked on at the same time.

How long builds take and how quickly CI gives developers feedback.

How it feels for developers to do their work — the friction in their daily flow.

A multi-dimensional model of developer productivity beyond delivery speed.

Code produced with help from AI coding tools like Copilot, Cursor, or Claude.

DXSignal turns your GitHub, GitLab, Jira, CI/CD, and incident data into these metrics — with AI-written insights on what to fix next.