# DORA Metrics Explained: The Complete Guide (2026)

## TL;DR

- **DORA metrics are four metrics for measuring software delivery performance:** Deployment Frequency, Lead Time for Changes, Mean Time to Recovery (MTTR), and Change Failure Rate.
- **They were introduced by Dr. Nicole Forsgren, Jez Humble, and Gene Kim in the 2018 book [_Accelerate_](https://itrevolution.com/product/accelerate/)** and are backed by years of research across thousands of engineering organizations.
- **DORA metrics remain the most widely adopted engineering measurement framework in the industry.** Their contribution -- giving engineering leaders a shared, research-backed language for delivery performance -- was transformational.
- **In 2026, the AI coding era has partially broken the assumptions underneath DORA.** For a detailed analysis, see [Why DORA Metrics Break in the AI Era](/content/developer-productivity/why-dora-metrics-break-ai-era/index.html).
- **The path forward is evolution, not abandonment.** Keep DORA as a foundation. Extend it with AI attribution, code durability, and complexity-adjusted throughput to account for AI-generated code.

## What Are DORA Metrics?

DORA metrics are a set of four metrics that measure software delivery performance. They were developed by the DevOps Research and Assessment (DORA) team.

The four metrics are:

1. **Deployment Frequency (DF)** -- how often code is deployed to production
2. **Lead Time for Changes (LT)** -- how long it takes from code commit to code running in production
3. **Mean Time to Recovery (MTTR)** -- how quickly the team recovers from a failure in production
4. **Change Failure Rate (CFR)** -- what percentage of deployments cause a failure in production

## The History of DORA

### The Research Program (2014-2018)

The DORA research program was founded by Dr. Nicole Forsgren, Jez Humble, and Gene Kim. The annual [State of DevOps Reports](https://dora.dev/) became essential reading for engineering leaders.

### _Accelerate_ (2018)

The definitive synthesis of DORA's research came in 2018 with the publication of [_Accelerate: The Science of Lean Software and DevOps_](https://itrevolution.com/product/accelerate/). It laid out the four metrics and the research methodology.

| Metric | Elite | High | Medium | Low |
| --- | --- | --- | --- | --- |
| Deployment Frequency | On demand (multiple per day) | Between once per day and once per week | Between once per week and once per month | Between once per month and once every 6 months |
| Lead Time for Changes | Less than one hour | Between one day and one week | Between one week and one month | Between one month and six months |
| Mean Time to Recovery | Less than one hour | Less than one day | Between one day and one week | Between one week and one month |
| Change Failure Rate | 0-15% | 16-30% | 31-45% | 46-60% |

### Google Acquisition and Ongoing Research (2018-Present)

In 2018, DORA was acquired by Google Cloud. The DORA team has continued to publish annual State of DevOps Reports.

## The Four Metrics in Detail

### 1. Deployment Frequency (DF)
**What it measures:** How often your organization deploys code to production.

### 2. Lead Time for Changes (LT)
**What it measures:** The elapsed time from when a developer commits code to when that code is running in production.

### 3. Mean Time to Recovery (MTTR)
**What it measures:** How quickly your team restores service after a production incident.

### 4. Change Failure Rate (CFR)
**What it measures:** The percentage of deployments that result in a failure requiring remediation.

## What DORA Gets Right

DORA metrics are grounded in multi-year, multi-thousand-organization research. They provided a common vocabulary for discussion in engineering performance.

## Where DORA Stands in 2026: What Has Changed

DORA metrics measure delivery outcomes, not developer activity. MTTR remains reliable, while Deployment Frequency and Lead Time have become misleading due to AI adoption.

## Extending DORA for AI-Native Teams

**Key Extensions:**
1. **Keep MTTR and CFR**
2. **Add Code Turnover Rate**
3. **Replace DF and LT with Complexity-Adjusted Throughput**
4. **Add AI Attribution**
5. **Track Innovation Rate**

## DORA in Practice: Implementation Guidance

1. **Start with the basics of Deployment Frequency and Lead Time**.
2. **Record incident times for MTTR**.
3. **Count failed deployments for Change Failure Rate**.

### Common Pitfalls
- Treating DORA as a leaderboard.
- Ignoring context.
- Using DORA for individual performance evaluation.

## Frequently Asked Questions

### What are DORA metrics?
DORA metrics are four metrics for measuring software delivery performance: Deployment Frequency, Lead Time for Changes, Mean Time to Recovery, and Change Failure Rate.

### Who created DORA metrics?
DORA metrics were created by the DevOps Research and Assessment team, led by Dr. Nicole Forsgren, Jez Humble, and Gene Kim.

### Are DORA metrics still relevant in 2026?
Partially. MTTR remains relevant while Deployment Frequency and Lead Time have become misleading.

### How do you start tracking DORA metrics?
Start with existing data from your CI/CD platform and incident management tools.

### Should you replace DORA metrics with something else?
No -- extend, do not replace. DORA's principles remain sound.