Deployment Frequency is the number of times software is deployed to production. It ensures that software is delivered early and often. This metric tracks how quickly a team can release new features and measures the speed and agility of an organization’s engineering team. It can be a very good indicator of a team’s response time, cohesiveness, capabilities and overall efficiency.
It is one of the measures of software delivery performance also known as Development Velocity.
Benefits of implementing Deployment Frequency?
Organizations are evolving and improving products sooner than those that solely rely on traditional software development and infrastructure management processes.
Deployment Frequency metrics help a team to:
- Measure productivity and agility—that is, how quickly a team can release new features or fix issues. Understand what actions to take to streamline the process
- Improve the efficiency, quality and stability of their systems
- Make data driven decisions
- Identify trends and patterns
- Continuously improve their processes
Let’s try to understand Deployment Frequency in more detail.
Deployment Frequency: As mentioned earlier, it simply the number of times an engineering team successfully releases software to production. This metric supports the fundamental value proposition of agile methodology, that the goal of a modern software delivery organization is to deliver software continuously to maximize value to the end user.
Releasing small changes allows end users to provide feedback and helps a team to decide whether they are on the right track, which will inform future decision-making about functionality.
It is a key metric to measure Software Delivery Performance.
How to measure Deployment Frequency?
It can be measured by counting the number of times a team makes deployments during a particular period. Teams can choose to measure deployments per week or per day.
From the pipeline tool (Azure DevOps, Jenkins, etc.) find out the number of builds deployed into production successfully.
The higher the number, the better the performance of a team is.
Based on this metric, performance of a DevOps team can be divided into four categories as per the following benchmark:
- Elite Performers: On demand – multiple time per day
- High Performers: Between once in a week and once in a month
- Medium Performers: Between once in a month and once in six months
- Low Performers: More than six months
Why should we measure Deployment Frequency?
Feedback is essential in software engineering. Without it, a team can only make best guesses about what is working.
Throughout the entire software delivery process, there are numerous examples that utilize early and fast feedback to drive incremental changes. A good development team employs a test-driven development (TDD) approach for early feedback.
This involves writing test cases first, then the application logic, which encourages the developers to continuously test and rewrite their code until the tests pass.
This early feedback strategy can be seen in continuous integration pipelines as well, where testing pyramids run smaller, faster tests first and run longer, larger tests last.
Both of these approaches encourage developers to catch faulty code earlier in the process rather than at the end. It makes sense to implement these strategies to production deployments to guide feature development and protect the stability of the product.
If a small batch of faulty code is released, it will be easier to revert that change quickly than a release that contains a week’s worth of changes.
In essence, having a higher deployment frequency gives a team the ability to be more agile in making changes.
High-performing engineering organizations should aim to deploy to production multiple times a day.
These high performers can easily release small features and provide quick fixes, making them more reactive to their customers and having an edge on the competition.
Causes of low Deployment Frequency
Low Deployment Frequency could be due to other elements interfering with the development activities.
Some reasons could be:
- Bulk changes sent for deployment: The changes introduced in the code are extensive and may require complex development and testing efforts. It is crucial for an engineering leadership to check whether their teams are combining changes into bigger portions which is causing delays.
Focusing on smaller increments helps teams deploy faster and ensures that end-users benefit from value more frequently.
- Lack of human resources/skillset: Changes in the team structure may result in a decreased Deployment Frequency. For example, if one engineer leaves and is replaced by another one, a low Deployment Frequency indicates that the team needs additional support to get back on track.
Leadership has to use this metric as an indicator of a team’s success and take advantage of opportunities to assess the combination of people, skills and talent that they bring to the table.
- Inefficiencies in development process: Deployment Frequency is negatively impacted by bottlenecks, dependencies and the usage of inappropriate tools that don’t support team members in completing their tasks. Use the right technology to accomplish higher throughput and velocity.
- Complicated Processes: Some processes include unnecessary steps that make deployment activity more complicated and complex which may result in low Deployment Frequency.
Leadership has to take a step back and look at the overall process to identify ways of simplifying the process (by getting rid of unwanted steps) and automate the deployment.
How to optimize Deployment Frequency?
Optimizing and reducing Deployment Frequency can be beneficial for a DevOps team and for the success of business.
A higher deployment frequency comes as a result of good engineering practices underneath.
A mix of technical and cultural practices will lead to an increase in deployment frequency. Some of them are having automation in place, reducing the size of change and developer ownership in the release process.
Build a robust CI/CD pipeline – High-performers in the deployment frequency category have a robust CI/CD system in place.
To deploy multiple times in a day, a team needs to have an automated build pipeline to reduce the overhead and toil of releasing software to end users.
Having this pipeline in place builds confidence when making changes and that confidence leads to more frequent changes.
By implementing CI/CD, speeding up the delivery process and reducing manual tasks, deployment frequency can be increased substantially.
Reduce the size of builds – A robust CI/CD system paves the way for getting code built and release faster, but it takes time for engineering departments to adapt and leverage this capability.
If the team has a tendency to work on large pull requests that lead to lots of changes in a single Git commit, it’s going to be hard to deploy frequently even after implementing the tools.
Technical leadership has to encourage the engineering team to push smaller batch sizes as it has following benefits:
- It’s easier for developers to review code. With large pull requests, code reviewers may get overwhelmed by the sheer amount of change whereas smaller requests narrow that focus.
- Reverting bad code becomes simpler. For smaller changes, teams can identify the bugs much faster than for larger changes.
- Emphasizes code quality. A smaller build leads to better focus on providing maintainable and well-tested code.
Combine Changes into Release Trains – Release trains combine multiple changes and are coordinated by an RTE (Release Train Engineer) till deployment. Though the process is not a simple one, it brings significant value to the end-users with new features and fixes with a higher frequency.
Reduce Technical Debt – Technical debt left unmonitored and unresolved is an essential factor that slows down the software deployment process. Constantly reducing technical debt and removing bugs helps to increase deployments, contributing to enhancing Deployment Frequency values.
Encourage Ownership Culture – An organization should have the right culture built in to increase deployment frequency and deliver value to customers faster.
From product managers to developers, QA teams to DevOps teams, observe where there might be bottlenecks in the process that prevent a team from shipping code quickly.
For example, do developers have more autonomy over the process with the use of feature flags? Are developers waiting for QA teams to test or waiting for infrastructure to be ready from DevOps teams?
If that is the case, there’s probably some opportunity to enable developers to be more involved with the process.
Deployment frequency is not a panacea for software development. Just because a team can deploy multiple times a day doesn’t mean value was provided to customers.
However, building up the automation and the culture to support on-demand deployments is the right step to building an organization that is equipped to change and learn from its failures.
Deployment frequency is an excellent metric to track and strive for improvement as it encourages establishing key underlying components of a strong engineering organization.
A team should not only thrive to become an elite performer but also has to deliver better business value frequently.
Kaiburr helps every product engineering team to measure their performance near real time using industry standard KPIs like those shown below –
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