Prioritize Intelligent Bug Triage: Improve bug triage by harnessing data insights and leveraging automation and AI.
Minimize Friction from Unhealthy Tests: Address unreliable tests by tracking performances and applying a data-driven approach.
Optimize for Failing Fast in Testing: Prioritize high-impact tests and parallelize test execution.
Improve Collaboration with DRIs: Assign Directly Responsible Individuals (DRIs) to enhance efficiency and deliver personalized test alerts.
This blog was originally featured on The CTO Club
As a Chief Technology Officer (CTO), you’re battling contradictory demands while trying not to stanch innovation.
From tighter budget constraints to the need for digital transformation and battling rising competition, the challenges your organization faces aren’t solved overnight.
But how can you realistically deliver quality products faster while cutting budget bloat? Some of these battles can be better won with thoughtful continuous integration (CI) approaches.
CTOs oversee the design and maintenance of development and test automation frameworks to streamline release processes. Regardless of your continuous integration maturity level, even the most cutting-edge teams can fall short of the following four areas.
Here are my recommendations for addressing the most common challenges, enabling your CI to support innovation better.
Imagine the continuous integration process as the engine of a car. The constant stream of code changes from developers acts as the pistons, driving the engine forward. These individual contributions must be seamlessly integrated to power the overarching mechanism, akin to turning a massive propeller.
In an ideal world, if every code change was flawless, developers could directly commit to the production branch, bypassing the intricate machinery of the CI process.
However, the reality is that code changes often have imperfections. This is where testing comes into play, acting as a quality control mechanism. Just as engines produce friction and heat, the CI process encounters challenges in the form of test failures. These failures, similar to jammed pistons, need prompt attention and resolution.
While encountering test failures in CI is a given, the efficiency of your bug triage process can significantly influence the success of your CI pipeline.
Harness Data for Insights: Leverage the rich data from your test suite to identify patterns, trends, and anomalies. Intelligent bug triage tools transform raw error logs into succinct insights. Instead of sifting through vast amounts of test result data manually get a faster, clearer picture of the underlying issues affecting your CI process.
Embrace Automation and AI: Look beyond manual bug severity and priority tech to AI solutions for better understanding of whether an issue has surfaced before. Leverage AI to create concise summaries of software error logs, helping your SDET and test automation engineers to quickly offer rapid insights into the root causes of test failures.
By adopting these strategies, CTOs can ensure a more streamlined and efficient CI pipeline, driving better outcomes for their development teams and the organization as a whole.
Think of unreliable tests as sand in the gears of your engine. They create unnecessary friction and, if left unchecked, can bring the entire system to a halt. It's comparable to neglecting a flashing check engine light in your car.
One of the most common culprits of unreliable tests is "flakiness." In today's fast-paced CI environments, the push for swift code deployment often magnifies the issue of flaky tests. These inconsistent tests disrupt the software delivery pipeline, strain project schedules, and cast shadows of doubt over test dependability, diverting precious developer time and energy.
The root causes of flaky tests often lie in either imperfect test design or external environmental factors. Many teams adopt strategies to manage these tests, such as:
Re-running tests until they pass.
Moving them further down the pipeline.
Isolating them for individual runs.
However, these measures can inadvertently decelerate both the CI process and the pace at which developers work. The key to navigating this challenge is observability and tracking of past test performances. By identifying tests prone to flakiness, teams can bolster confidence in their test suite and address the core issues.
Innovative teams are already paving the way in this domain. For instance, Spotify has crafted a mathematical model linking flakiness to other test failures, while Dropbox meticulously analyzes its test data to pinpoint the underlying issues.
While addressing flaky tests is crucial, overcorrection can be counterproductive. Striking the right balance is imperative, and the best way to achieve this equilibrium is through a data-driven approach. This method helps discern which test inconsistencies require immediate attention and which can be momentarily set aside.
Traditionally, the testing approach has been comprehensive: run every test, every time. The guiding principle was to be exhaustive. However, with the emergence of AI, we can now strategically focus on tests that are more likely to identify failures.
Addressing test triage will significantly reduce CI pipeline bloat, but determining which tests are pivotal can nip inefficiencies in the bud.
To enhance the speed and efficiency of your test suite, embrace the philosophy of failing fast. Here are some techniques to consider:
Prioritize by Business Impact: Identify and prioritize test cases that cover crucial functionalities. Ensure these high-impact tests are executed at the outset.
Parallelize Test Execution: Instead of a linear, sequential test run, leverage tools like TestNG or JUnit to execute multiple tests concurrently. This approach eliminates idle waiting periods and maximizes test throughput.
Intel DAOS took this approach with their test selection. By selectively executing tests related to modified source code, the team accelerated their development cycles, saving over 2,000 hours each month.
For a smooth CI process, it's essential to manage pull requests efficiently. Teams often monitor which test suites are active for their PRs and act accordingly upon completion. However, this can lead to frequent interruptions; crucial test notifications might get overlooked amidst a cluttered CI system or lost in overflowing email inboxes.
A solution to this challenge is the concept of a “Directly Responsible Individual” (DRI). While this principle can be applied across various domains, it's particularly beneficial for CI.
Incorporating DRIs within teams offers several advantages:
Eliminates Ambiguity: Assigning a DRI ensures clarity in roles, preventing the common pitfall of overlooked tasks (because everyone assumes someone else will handle them).
Avoids Redundant Efforts: With a designated DRI, there's no risk of multiple team members inadvertently working on the same task.
Boosts Efficiency and Cost-Effectiveness: Clear DRI roles optimize communication, ensuring only relevant individuals are involved in discussions, thereby conserving time and resources.
Facilitates Decisive Action: With DRIs, leaders can delegate tasks more effectively, preventing decision-making logjams and enhancing overall team productivity.
Moreover, to address the challenge of missed test notifications in CI, delivering personalized test alerts directly to the DRI can expedite the triage process and minimize unnecessary notifications for the rest of the team.
An efficient CI improves software quality, speeds up releases, and detects issues earlier in a collaborative pipeline. For those combatting the cost of cloud or those limited to hardware constraints, parallelization of test runs isn’t enough to speed up feedback.
Fine-tune your CI to target common friction points like triage, flakiness, test selection, and notification to reduce risk and the likelihood of errors later in your development cycles.
Enabling more intelligent, data-driven issue identification and collaboration should be included in your CI optimization plan to ensure you get the best ROI on your CI efforts.