Enhancing engineering impact with metrics
Engineering Metrics
Oct 5, 2023
In the fast-paced realm of software engineering, understanding and optimizing the performance of the engineering team is critical for achieving organizational objectives and satisfying stakeholders. This involves an intricate mix of various factors, including engineering metrics, development process streamlining, and efficient decision-making. In this post, we will explore how organizations can enhance engineering impact through the strategic use of metrics, process optimization, and fostering a culture of continuous improvement.
Leveraging Engineering Metrics for Productivity Assessment
Effective measurement is at the heart of any improvement initiative. Engineering metrics provide a quantifiable view of the team's performance, aiding in understanding productivity, quality, and efficiency. Metrics such as cycle time, lead time, lines of code, story points, and pull request metrics offer valuable insights into the team's productivity and efficiency.
Optimizing Development Processes for Efficiency
Streamlining the development process is fundamental to enhancing engineering impact. By identifying and reducing bottlenecks, minimizing downtime, and improving cycle time, an organization can ensure that projects are delivered on time and within the allocated timeframe. Automation of repetitive tasks and efficient code review processes also play a vital role in optimizing the development workflow.
Fostering a Culture of Continuous Improvement
To measure and enhance engineering impact effectively, fostering a culture of continuous improvement is essential. Encouraging engineering leaders and team members to actively participate in initiatives that aim to measure productivity, implement best practices, and enhance code quality can drive meaningful change. Regular reviews, both at the individual and team levels, can lead to actionable insights and improvements.
Aligning Metrics with Business Goals
Understanding and aligning engineering metrics with business goals is crucial. Key Performance Indicators (**KPIs**) that directly influence customer satisfaction, the delivery of new features, and overall product quality should be prioritized. Establishing a clear baseline and setting achievable benchmarks helps in tracking progress and making informed decisions.
Effective Allocation of Resources and Initiatives
Efficient allocation of resources, both human and technical, is vital for optimizing engineering impact. Understanding how to distribute the engineering team's efforts across various engineering projects and initiatives ensures that the right focus is placed on critical areas. This process involves strategic decision-making by engineering managers to align with the organization's vision and goals.
Utilizing Dashboards for Real-time Insights
Implementing dashboards that display real-time metrics and productivity data can significantly impact team performance. These dashboards should be designed to provide an at-a-glance view of relevant metrics, aiding in quick decision-making and identifying areas for improvement.
Conclusion
Enhancing engineering impact within an engineering organization requires a comprehensive approach that encompasses effective engineering metrics, process optimization, and a culture of continuous improvement. BuildPulse Engineering Metrics enables you to do just that - benchmark DORA metrics, code velocity, and quality, but also go beyond with our developer copilot. By aligning these efforts with business goals, fostering efficient workflows, and embracing automation, organizations can drive increased productivity, better code quality, and improved customer satisfaction. The strategic use of metrics and a commitment to continuous enhancement empowers engineering teams to deliver exceptional results, on time and within the desired quality standards, thus elevating the overall software engineering process.
FAQ
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!