The power of sprint velocity

Engineering Metrics

Oct 12, 2023

In today's fast-paced software development landscape, understanding and optimizing the engineering process is paramount. Central to this is the concept of 'sprint velocity', a metric that offers profound insights into an engineering team's performance and efficiency. But what is sprint velocity, and how does it fit into a broader, data-driven engineering culture?

Agile and Scrum: The Cornerstones of Modern Software Engineering

Agile Methodology: Agile is a dynamic approach to software development, emphasizing adaptability, stakeholder collaboration, and a focus on customer satisfaction. It's a methodology that ensures software engineering teams can swiftly respond to changes, aligning the end product with stakeholders' expectations.

Scrum: A popular subset of Agile, Scrum divides the development process into 'sprints'. These are short, focused periods where specific milestones or deliverables are targeted. Each sprint is a testament to the team's productivity and the engineering organization's overall efficiency.

Sprint Velocity Unveiled

Sprint velocity quantifies the work an engineering team can tackle during a single sprint. It's gauged using 'story points', estimations of effort or time for a task. However, while story points provide a baseline, they aren't the sole measure of progress. This is where the disconnect often lies in many engineering teams.

The Importance of Sprint Velocity:

  1. Optimization: Sprint velocity offers a lens into the team's workflow, highlighting areas for optimization.

  2. Stakeholder Communication: It aids in setting realistic expectations for deliverables and timelines.

  3. Continuous Improvement: By consistently measuring and analyzing sprint velocity, engineering teams can drive continuous improvement, ensuring that the development process is always evolving and adapting.

Bridging the Gap: Code Velocity Metrics

Traditional planning tools, while useful, often miss the mark when it comes to capturing the true essence of progress. They focus on story points, which, though valuable, don't provide a complete picture. To bridge this gap, engineering metrics like lines of code, pull requests, code review processes, and more need to be integrated into the sprint velocity assessment.

Code Velocity Metrics: These metrics delve deeper, connecting business tasks with their technical counterparts. By incorporating metrics such as pull requests, code review feedback, and lines of code, engineering teams can achieve a holistic understanding of a project's status, ensuring that business goals and technical progress are in sync.

Components of Sprint Velocity

Several elements constitute sprint velocity:

  1. Story Points: Estimations of effort or time, providing a foundational measure of progress.

  2. Cycle Time: Captures the time from task inception to completion, indicating team efficiency.

  3. Code Review: Ensures code quality and adherence to best practices.

  4. Engineering Metrics: Metrics like lines of code, pull requests, and benchmarks that offer a granular view of technical progress.

Cultivating a Data-Driven Approach

For sprint velocity to be truly impactful, a data-driven culture is essential. Dashboards and visualization tools can consolidate diverse data sources, offering a comprehensive project overview. This not only aids in decision-making but also ensures alignment with business goals and stakeholder expectations.

Furthermore, regular reviews with team members and engineering leaders can refine the sprint velocity metric. By fostering open communication and involving engineers in the conversation, the metric remains relevant, actionable, and reflective of the team's true capabilities.


In conclusion, sprint velocity, when harnessed correctly, can revolutionize software engineering processes. It bridges the gap between business objectives and technical progress, ensuring alignment and clarity. BuildPulse Engineering Metrics can amplify this approach, providing the insights needed to drive engineering productivity to new heights.


What is the difference between a flaky test and a false positive?

A false positive is a test failure in your test suite due to an actual error in the code being executed, or a mismatch in what the test expects from the code.

A flaky test is when you have conflicting test results for the same code. For example, while running tests if you see that a test fails and passes, but the code hasn’t changed, then it’s a flaky test. There’s many causes of flakiness.

What is an example of a flaky test?

An example can be seen in growing test suites - when pull request builds fail for changes you haven’t made. Put differently, when you see a test pass and fail without any code change. These failed tests are flaky tests.

What are common causes of flakiness?

Broken assumptions in test automation and development process can introduce flaky tests - for example, if test data is shared between different tests whether asynchronous, high concurrency, or sequential, the results of one test can affect another. 

Poorly written test code can also be a factor. Improper polling, race conditions, improper event dependency handling, shared test data, or timeout handling for network requests or page loads. Any of these can lead to flaky test failures and test flakiness.

End-to-end tests that rely on internal API uptime can cause test flakiness and test failures.

What's the impact of flaky tests?

Flaky tests can wreck havoc on the development process - from wasted developer time from test retries, to creating bugs and product instability and missed releases, time-consuming flaky tests can grind your development process to a halt.

What is the best way to resolve or fix flaky tests?

Devops, software engineering, and software development teams will often need to compare code changes, logs, and other context across test environments from before the test instability started, and after - adding retries or reruns can also help with debugging. Test detection and test execution tooling can help automate this process as well. 

BuildPulse enables you to find, assess impact metrics, quarantine, and fix flaky tests.

What are some strategies for preventing flaky tests?

Paying attention and prioritizing flaky tests as they come up can be a good way to prevent them from becoming an issue. This is where a testing culture is important - if a flaky test case is spotted by an engineer, it should be logged right away. This, however, takes a certain level of hygiene - BuildPulse can provide monitoring so flaky tests are caught right away.

What type of tests have flaky tests?

Flaky tests can be seen across the testing process - unit tests, integration tests, end-to-end tests, UI tests, acceptance tests.

What if I don't have that many flaky tests?

Flaky tests can be stealthy - often ignored by engineers and test runs are retried, they build up until they can’t be ignored anymore. These automated tests slow down developer productivity, impact functionality, and reduce confidence in test results and test suites. Better to get ahead while it’s easy and invest in test management.

It’s also important to prevent regressions to catch flakiness early while it’s manageable.

What languages and continuous integration providers does BuildPulse work with?

BuildPulse integrates with all continuous integration providers (including GitHub Actions, BitBucket Pipelines, and more), test frameworks, and workflows.

Combat non-determinism, drive test confidence, and provide the best experience you can to your developers!

How long does implementation/integration with BuildPulse take?

Implementation/integration takes 5 minutes!

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