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---
title: "DORA - Change Failure Rate"
description: >
DORA - Change Failure Rate
sidebar_position: 21
---
## What is this metric?
The percentage of changes that were made to a code that then resulted in incidents, rollbacks, or any type of production failure.
## Why is it important?
Unlike Deployment Frequency and Lead Time for Changes that measure the throughput, Change Failure Rate measures the stability and quality of software delivery. A low CFR reflects a bad end-user experience as the production failure is relatively high.
## Which dashboard(s) does it exist in
DORA dashboard. See [live demo](https://grafana-lake.demo.devlake.io/grafana/d/qNo8_0M4z/dora?orgId=1).
## How is it calculated?
The number of failures per the number of deployments. For example, if there are five deployments in a day and one causes a failure, that is a 20% change failure rate.
Below are the benchmarks for different development teams from Google's report. However, it's difficult to tell which group a team falls into when the team's change failure rate is `18%` or `40%`. Therefore, DevLake provides its own benchmarks to address this problem:
| Groups | Benchmarks | DevLake Benchmarks |
| -----------------| ----------------| -------------------|
| Elite performers | 0%-15% | 0%-15% |
| High performers | 16%-30% | 16-20% |
| Medium performers| 16%-30% | 21%-30% |
| Low performers | 16%-30% | > 30% |
<p><i>Source: 2021 Accelerate State of DevOps, Google</i></p>
<b>Data Sources Required</b>
This metric relies on:
- `Deployments` collected in one of the following ways:
- Open APIs of Jenkins, GitLab, GitHub, etc.
- Webhook for general CI tools.
- Releases and PR/MRs from GitHub, GitLab APIs, etc.
- `Incidents` collected in one of the following ways:
- Issue tracking tools such as Jira, TAPD, GitHub, etc.
- Bug or Service Monitoring tools such as PagerDuty, Sentry, etc.
- CI pipelines that marked the 'failed' deployments.
<b>Transformation Rules Required</b>
This metric relies on:
- Deployment configuration in Jenkins, GitLab or GitHub transformation rules to let DevLake know what CI builds/jobs can be regarded as `Deployments`.
- Incident configuration in Jira, GitHub or TAPD transformation rules to let DevLake know what CI builds/jobs can be regarded as `Incidents`.
<b>SQL Queries</b>
If you want to measure the monthly trend of change failure rate as the picture shown below, run the following SQL in Grafana.
![](/img/Metrics/cfr-monthly.jpeg)
```
with _deployments as (
-- get the deployment count each month
SELECT
date_format(finished_date,'%y/%m') as month,
COUNT(distinct id) AS deployment_count
FROM
cicd_tasks
WHERE
type = 'DEPLOYMENT'
and result = 'SUCCESS'
GROUP BY 1
),
_incidents as (
-- get the incident count each month
SELECT
date_format(created_date,'%y/%m') as month,
COUNT(distinct id) AS incident_count
FROM
issues
WHERE
type = 'INCIDENT'
GROUP BY 1
),
_calendar_months as(
-- deal with the month with no incidents
SELECT date_format(CAST((SYSDATE()-INTERVAL (month_index) MONTH) AS date), '%y/%m') as month
FROM ( SELECT 0 month_index
UNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3
UNION ALL SELECT 4 UNION ALL SELECT 5 UNION ALL SELECT 6
UNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9
UNION ALL SELECT 10 UNION ALL SELECT 11
) month_index
WHERE (SYSDATE()-INTERVAL (month_index) MONTH) > SYSDATE()-INTERVAL 6 MONTH
)
SELECT
cm.month,
case
when d.deployment_count is null or i.incident_count is null then 0
else i.incident_count/d.deployment_count end as change_failure_rate
FROM
_calendar_months cm
left join _incidents i on cm.month = i.month
left join _deployments d on cm.month = d.month
ORDER BY 1
```
If you want to measure in which category your team falls into as the picture shown below, run the following SQL in Grafana.
![](/img/Metrics/cfr-monthly.jpeg)
```
with _deployment_count as (
-- get the deployment deployed within the selected time period in the top-right corner
SELECT
COUNT(distinct id) AS deployment_count
FROM
cicd_tasks
WHERE
type = 'DEPLOYMENT'
and result = 'SUCCESS'
and $__timeFilter(finished_date)
),
_incident_count as (
-- get the incident created within the selected time period in the top-right corner
SELECT
COUNT(distinct id) AS incident_count
FROM
issues
WHERE
type = 'INCIDENT'
and $__timeFilter(created_date)
)
SELECT
case
when deployment_count is null or incident_count is null or deployment_count = 0 then NULL
when incident_count/deployment_count <= .15 then "0-15%"
when incident_count/deployment_count <= .20 then "16%-20%"
when incident_count/deployment_count <= .30 then "21%-30%"
else "> 30%"
end as change_failure_rate
FROM
_deployment_count, _incident_count
```
## How to improve?
- Add unit tests for all new feature
- "Shift left", start QA early and introduce more automated tests
- Enforce code review if it's not strictly executed