Performance Metrics Glossary: Key Terms
Definition of Deployment frequency
What is deployment frequency?
Deployment frequency is a key DevOps and software delivery performance metric that measures how often an organization successfully releases code to production. It represents the cadence at which software changes are deployed to live environments where they provide value to end users. High-performing technology organizations typically aim for frequent, small deployments rather than large, infrequent ones to reduce risk and deliver value faster.
Deployment frequency is one of the four critical metrics identified in the DORA (DevOps Research and Assessment) research, alongside lead time, change failure rate, and mean time to recovery. Organizations with high deployment frequency can often deploy multiple times per day, while lower-performing teams might deploy monthly or quarterly. This metric is valuable because it directly correlates with an organization's ability to respond to market changes and customer needs quickly.
What is the difference between cycle time and deployment frequency?
Cycle time and deployment frequency are metrics that measure different aspects of the software delivery process. Cycle time measures the duration it takes for a piece of work to flow through the development process, while deployment frequency measures how often deployments occur. Cycle time begins measuring from the moment work begins until it is deployed to production with a focus on the speed of delivery for individual work items. Deployment frequency does not focus on the size or scope of each deployment but rather on the rhythm of release.
A team can have a short cycle time but low deployment frequency if they complete work quickly but combine changes for infrequent releases. Likewise, a team might have high deployment frequency but longer cycle times if they release small changes on a regular basis while larger features take longer to complete.
How to calculate deployment frequency?
Calculating deployment frequency is a process that involves tracking how often code is successfully deployed to production over a specific time period, such as weekly or monthly. For example, if a team deploys to production 20 times in a 30-day period, their monthly deployment frequency would be 20 deployments per month, or approximately 0.67 deployments per day.
Many teams find it useful to categorize their deployment frequency into bands according to the DORA metrics framework: multiple deployments per day (elite), between once per day and once per week (high), between once per week and once per month (medium), or between once per month and once every six months (low). When calculating deployment frequency, it is important to count only successful deployments that make it to production, not failed attempts or deployments to testing environments. Additionally, some companies distinguish between different types of deployments, such as feature deployments versus hotfixes, to gain more nuanced insights into their release patterns.
How to improve deployment frequency?
Teams can apply several strategies to improve deployment frequency. These steps involve changes to workflows and cultural changes to facilitate an environment that promotes a good deployment frequency on a regular basis.
- Implement continuous integration and continuous delivery (CI/CD) pipelines.
- Break down work into smaller, more manageable chunks that can be delivered in stages.
- Automation throughout a workflow.
- Standardize environments across development, testing, and production.
- Shift to microservices architecture where appropriate.
- Foster a culture that values small, frequent changes over large batches of work.
- Track and reduce approval bottlenecks in the deployment process.
- Implement monitoring and observability tools to quickly identify issues post-deployment.
Teams need to take time to understand their processes and identify areas for improvement. In this sense, it is also important to consider how metrics are used to measure development team efficiency. They should be understood as signals rather than a spotlight on a specific issue.
How does Enji support a good deployment frequency?
Enji helps teams apply all of the steps mentioned above to their workflows to achieve and maintain a healthy deployment frequency. AI features work in the background to keep teams focused on tasks and moving them through their workflow.
- Automated alerts: Teams customize alerts to identify tasks that have stayed in a certain status for too long.
- AI Copilot: Enji's AI assistant helps managers find bottlenecks and provides insights into improving deployment based on project data.
- Code metrics: Enji collects data on individual and group engineering performance to help teams visualize their processes and make necessary adjustments.
These and other Enji features provide data and insights that teams can immediately apply to their processes to create more value and increase deployment frequency.
Key Takeaways
- Deployment frequency measures how often code is successfully deployed to production environments.
- It is one of the four DORA metrics used to assess DevOps performance, alongside lead time, change failure rate, and mean time to recovery.
- High-performing teams deploy multiple times per day, while low performers may deploy monthly or quarterly.
- Deployment frequency should be balanced with other metrics like stability and quality to ensure overall system health.
- To calculate deployment frequency, count successful deployments to production over a given time period.
- Improving deployment frequency requires investment in automation, testing, and DevOps practices, which leads to improved cycle time and reduced lead time.
- High deployment frequency enables faster market feedback and more rapid adaptation to customer needs.
- Enji supports healthy deployment frequencies with automated alerts and AI-powered analytics.
Last updated in April 2025