What is change failure rate?

Imagine your software deployment process as a relay race, where the smooth handoff of the baton, your code, from one runner to the next—your development and operations teams—is critical for crossing the finish line successfully. The Change Failure Rate (CFR) serves as the key metric, much like a coach’s stopwatch, that measures the efficiency and reliability of these exchanges.

This guide examines CFR, tracing its evolution from a straightforward measure to a complex and essential gauge in today’s fast-paced tech environments. We’ll explore strategies leading companies employ to enhance these transitions, ensuring each leg of the race strengthens the next, driving organizational success and minimizing disruptions.

Introduction to change failure rate

Defining change failure rate

Change failure rate is the percentage of deployments to a production environment that fail, leading to service impairments or the need for remediation solutions. A deployment failure can be anything from a degraded service to a complete service outage, necessitating “fix-only” patches.

Importance of CFR in DevOps practices

In DevOps, CFR reflects software delivery performance and directly impacts customer experience and operational costs. High-performing DevOps teams maintain a low CFR to ensure high-quality software delivery and minimal service disruptions.

Change failure rate as a DORA metric

Change failure rate (CFR) is one of the four key metrics identified by the DORA (DevOps Research and Assessment) team as essential for understanding and improving DevOps practices and capabilities.

CFR complements the other DORA metrics—Deployment Frequency, Mean Lead Time for Changes, and Mean Time to Recovery—by providing insights into the reliability and risk associated with changes made to production environments. Together, these metrics offer a comprehensive view of an organization’s software delivery performance, highlighting areas of strength and opportunities for improvement in the DevOps lifecycle.

Measuring change failure rate

CFR calculation

The failure rate metric is calculated by dividing the number of failures in production by the total number of production deployments within a given period and expressing it as a percentage:

CFR=(Number of Deployment FailuresTotal Number of Deployments)×100%CFR=(Total Number of DeploymentsNumber of Deployment Failures)×100%

Tools and techniques for accurate measurement

Accurate change failure rate calculations rely on robust incident management tools that log all deployment activities and track unexpected outcomes. Continuous monitoring and frequent frequent assessments are vital to understanding and improving CFR.

Factors influencing change failure rate

Several variables affect CFR, including:

• Deployment Frequency: If not managed properly, high deployment frequency can increase the risk of failures. Engineering leaders often use the frequency metric to gauge the stability of deployment processes.
• Code Quality: Poor code quality and inadequate testing before deployment significantly contribute to high CFR. Implementing thorough code review processes and adequate test coverage can mitigate these risks.
• Manual Processes: Manual deployment workflows and manual testing are more susceptible to human error, leading to higher failure rates. Automating testing processes helps reduce the risk of failure.

Strategies for optimizing change failure rate

To improve CFR, organizations can adopt several strategies:

• Automated testing and continuous integration: Implementing continuous testing within the deployment lifecycle ensures that every integration is tested automatically, reducing the likelihood of deploying problematic code to production.
• Canary and blue/green deployments:Canary deployments and blue/green deployment strategies involve gradually rolling out changes to a small subset of users before full deployment, allowing teams to detect and remediate issues early with minimal impact.
• Proactive Incident Management: Utilizing advanced incident management tools can help quickly address and rectify any failures in production, thereby improving the quality of deployments and reducing the CFR.

Impact and real-world application of CFR

Business and operational impact

A high CFR indicates potential issues in the deployment process or code quality, leading to increased financial costs from service outages and maintenance costs. Conversely, a low CFR indicates efficient DevOps practices, which correlate strongly with better business outcomes and enhanced software engineering team performance.

Case studies and industry examples

Tech leaders and high-performing teams in top tech companies often achieve and maintain lower CFR by employing rigorous DevOps practices, such as continuous delivery, comprehensive testing practices, and automated deployment processes. These practices reduce the frequency and impact of deployment failures and contribute to the organization’s overall DevOps maturity.

Exploring change failure rate: Insights from industry leaders

During an engaging conversation on LinkedIn led by Abi Noda, industry professionals discussed their methodologies for calculating the change failure rate, each customized to their unique operational contexts. This discussion provided insights into the diverse approaches companies use to measure and manage deployment failures, showcasing the flexibility and complexity of this crucial metric.

Diverse definitions across companies

The discussion revealed that different companies have distinct definitions and methods for calculating CFR based on their needs. Here are some of the varied methods that we found.

• Company 1 measures CFR by counting git reverts or pipeline rollbacks relative to the total number of deployments. They adapt this metric for mobile platforms by monitoring point releases, focusing on immediate metrics that may only partially capture broader impacts.
• Company 2 defines CFR as the percentage of deployments resulting in customer-impacting service degradation. This approach, while comprehensive, is sometimes challenging to apply due to a high volume of deployments relative to the frequency of incidents.
• Company 3 uses a ratio of P0 incidents over production deploys, tracked through advanced tools like PagerDuty and Spinnaker, emphasizing the severity of incidents.
• Company 4 opts for simplicity, assessing CFR through a straightforward count of weekly incidents, avoiding the complexities of percentage-based metrics.

DevEx leaders weigh in

Several commenters on the thread offered valuable insights into effective CFR measurement and management:

• Diogo Correia from Pipedrive mentioned an incident-based CFR alongside a Bug Discovery Rate, offering a nuanced view beyond mere incident counting.
• Val Akkapeddi of Collectors discussed the importance of choosing metrics that reflect system performance, cautioning against striving for perfection pre-release.
• Max Kanat-Alexander from LinkedIn emphasized designing metrics aligned with specific business outcomes, ensuring that measurements are actionable and directly tied to business goals.
• Steve Feldman of Marriott recommended measuring change failures and successes to view deployment impacts from multiple angles comprehensively.

The lively LinkedIn discussion underscores no universal method for measuring CFR. Each organization must develop its approach based on its operational environment, risk tolerance, and business objectives. Metrics should track failures and foster proactive improvements in processes and software quality.

Adopting tools and practices such as continuous integration, automated testing, and canary deployments can reduce CFR by allowing software development teams to detect and resolve issues early. This approach aligns with the wisdom shared by Keith Mann and others in the thread, highlighting the importance of not getting overly fixated on definitions at the expense of seizing opportunities for improvement.

This discussion illustrates the value of a flexible, adaptive approach to CFR measurement, which is crucial for maintaining high-performing teams and achieving superior business outcomes in the fast-evolving software development landscape.

CFR is a key performance indicator that offers critical insights into the effectiveness of the deployment process, code quality, and overall DevOps performance. By understanding and optimizing CFR, organizations can ensure successful deployments, create high-quality software, and significantly improve operational and business performance. As part of a suite of DORA metrics, CFR helps software leaders make informed decisions to drive continuous improvement and achieve high operational excellence.