Smooth and reliable deployments are key to maintaining user satisfaction and business continuity. Change Failure Rate provides valuable insights into how frequently deployments lead to failures. This guide is for engineering leaders, DevOps teams, and software managers seeking to understand and reduce Change Failure Rate (CFR).
We cover what CFR is, how to calculate it, why it matters, and actionable strategies to improve it. By the end, you’ll have a clear understanding of how to measure, interpret, and reduce CFR for more stable software delivery.
What are DORA Metrics?
In 2015, Gene Kim, Jez Humble, and Nicole Forsgren founded the DORA (DevOps Research and Assessment) team to evaluate and improve software development practices. The aim is to improve the understanding of how organizations can deliver faster, more reliable, and higher-quality software.
DORA metrics help in assessing software delivery performance based on four key (or accelerate) metrics. A comprehensive overview of DORA metrics can further illustrate how these indicators drive software delivery success:
Deployment Frequency
Lead Time for Changes
Change Failure Rate
Mean Time to Recover
While these metrics provide valuable insights into a team's performance, understanding CFR is crucial. It measures the effectiveness of software changes and their impact on production environments. Mastering the four key DORA metrics for software delivery performance helps put CFR into proper context.
Overview of Change Failure Rate
Change Failure Rate (CFR) measures deployment failures requiring fixes or rollbacks. It is calculated as (Failed Changes / Total Changes) x 100. CFR reflects the stability and reliability of the entire software development and deployment lifecycle, making it one of the most critical DevOps metrics for deployment reliability.
A lower change failure rate enhances user experience and builds trust by reducing failures.
It protects your business from financial risks, revenue loss, customer churn, and brand damage.
Lower change failures help to allocate resources effectively and focus on delivering new features.
How to Calculate Change Failure Rate?
To calculate Change Failure Rate, follow these steps:
Identify Failed Changes: Track the number of changes that resulted in failures (requiring fixes or rollbacks) during a specific timeframe.
Determine Total Changes Implemented: Count the total changes or deployments made during the same period.
Apply the formula: CFR = (Number of Failed Changes / Total Number of Changes) × 100
Example Calculation:
Failed Changes = 2
Total Changes = 30
Using the formula: (2/30) × 100 = 6.67%
Therefore, the Change Failure Rate for that period is 6.67%.
What is a Good Failure Rate?
An ideal failure rate is between 0% and 15%. This is the benchmark and standard that engineering teams need to maintain. Low CFR equals stable, reliable, and well-tested software.
When the Change Failure Rate is above 15%, it reflects significant issues with code quality, testing, or deployment processes. This leads to increased system downtime, slower deployment cycles, and a negative impact on user experience.
Hence, it is always advisable to keep CFR as low as possible.
How to Correctly Measure Change Failure Rate?
Be sure to define what constitutes a failure for your team to ensure accurate CFR measurement. Also, exclude 'fix-only' deployments from CFR calculations.
1. Define Failure Criteria
Clearly define what constitutes a ‘Change’ and a ‘Failure,’ such as service disruptions, bugs, or system crashes.
Ensure the team is aligned and consistently collecting data with clear metrics.
2. Capture and Label Data
Define the scope of changes to include in CFR calculation.
Specify details for deciding the success or failure of changes.
Use a Change Management System to track or log changes in a database.
Tools like JIRA, GIT, or CI/CD pipelines can automate and review data collection.
3. Measure Change Failure, Not Deployment Failure
Deployment Failure: Failures during the process of deploying code or changes to a production environment.
Change Failure: Failures after deployment when the changes themselves cause issues in the production environment.
Focus on improving processes rather than troubleshooting unrelated issues.
4. Analyze Trends
Analyze failures continuously over different time periods (weekly, monthly, quarterly).
Look for trends and patterns to reveal recurring issues.
Use these insights to prioritize areas for improvement and inform strategic decisions.
5. Understand the Limitations of DORA Metrics
DORA Metrics provide valuable insights into software development performance and identify high-level trends.
They may not capture nuances such as the complexity of changes or severity of failures.
Use them alongside other metrics for a holistic view.
Filter out failures caused by external factors such as third-party service outages or hardware failure.
This ensures CFR accurately reflects your team's performance.
How to Reduce Change Failure Rate?
Identify the root causes of failures and implement best practices in testing, deployment, and monitoring. Here are effective strategies to minimize CFR:
1. Automate Testing Practices
Implement automated testing during each phase of the development lifecycle.
Catch issues early and often to improve code quality.
Make test results accessible for clear focus on crucial aspects.
2. Deploy Small Changes Frequently
Make small deployments at frequent intervals.
Easier testing and bug detection reduce risks of failures.
Frequent deployments provide quicker feedback to team members and engineering leaders.
Use real-time monitoring and alerting systems to detect issues early.
Resolve problems quickly to minimize the impact of failures.
Improves overall system reliability and provides immediate feedback on application performance and user experience.
6. Cultivate a Learning Culture
Encourage continuous improvement and knowledge sharing within the development team.
Conduct post-incident reviews and share key insights.
Foster collaboration, accountability, and continuous improvement.
How Does Typo Help in Reducing CFR?
Since the definition of Failure is specific to teams, there are multiple ways this metric can be configured. Here are some guidelines on what can indicate a failure:
A deployment that needs a rollback or a hotfix: Any Pull Request having a title/tag/label that represents a rollback/hotfix merged to production can be considered a failure.
A high-priority production incident: Any ticket in your Issue Tracker with a title/tag/label representing a high-priority production incident can be considered a failure.
A deployment that failed during the production workflow: Typo can integrate with your CI/CD tool and consider any failed deployment as a failure.
To calculate the final percentage, divide the total number of failures by the total number of deployments (this can be picked either from the Deployment PRs or from the CI/CD tool deployments).
Conclusion
Measuring and reducing the Change Failure Rate is a strategic necessity. It enables engineering teams to deliver stable software, leading to happier customers and a stronger competitive advantage. With tools like Typo, organizations can easily track and address failures to ensure successful software deployments, especially when implementing DORA DevOps metrics in large organizations.
