It is the burden of all development teams to speed up their development life cycle without sacrificing quality in the quest for faster releases. Because of this, the CI/CD pipeline, one of the foundational pieces of DevOps, includes lots of testing methods.
To help you streamline your testing methodology, we’re focusing on Continuous Integration testing- the quality assurance that happens at the beginning of your development lifecycle. Read on to discover our Field Guide to all things CI Testing, so you can boost your CI/CD pipeline and empower your teams to launch faster and more fearlessly.
Refresh on CI (and CD/CD)
The CI/CD pipeline serves as an “assembly line” for software, automating pass-offs between different areas of development to avoid bottlenecks.
CI stands for Continuous Integration, which focuses on the first half of development by testing the developers’ written code in real-time, then compiling these artifacts into a central repository and transforming them into builds.
Then, these builds are passed along to the next stage CD, Continuous Delivery or Continuous Deployment. Continuous Delivery automatically delivers the builds to a testing environment, where their functionality is tested. Continuous Deployment goes a step further and deploys the builds into production if the automated tests performed in the test environment go well.
Continuous Deployment generally fits best with a more mature DevOps culture, as it requires robust and trustworthy testing within the test environment and circumvents human intervention throughout the entire SDLC. Continuous Delivery is best for teams who are just starting to use a CI/CD pipeline. It allows humans to quality-check and approve the builds before they get deployed into the real world, but still features great automation tools to get to that point.
What Is Continuous Integration Testing
Testing in the Continuous Integration workflow allows for rapid feedback at an earlier stage in development. It stops the progression of the artifact if minimum quality requirements aren’t met, allowing the developer to correct the code while the artifact is still fresh on their minds.
In practice, it looks like quick quality checks that automatically run against each developer’s code, as soon as they attempt to merge the changes into that central repository. Think of Continuous Integration testing as the bouncer standing at the door of your code repository. Your repository should only allow vetted and approved artifacts to enter, so if the bouncer sees that an artifact doesn’t meet testing criteria, they won’t let it inside the repository.
Importance of Continuous Integration Testing
But, it might be counterintuitive to think of CI testing as a necessary piece of the development process before the builds even reach the testing stage. (After all, Continuous Integration happens long before the code even hits the test environment during Continuous Delivery!) Waiting until the last minute can cause big issues for developers. The biggest one: the longer you wait to fix problems, the bigger they’ll become as the artifacts progress down the line. It becomes a snowball effect.
Often, development teams see the test environment and QA team as the ultimate rescuer of their software. They might say something like, “even if my code contains some quality issues, these problems will get caught in the test environment and fixed at that point.”
You shouldn’t rely on your test environments and QA team to swoop in and save your software at the last second, like the eagles at the end of the Lord of the Rings trilogy.
Instead, Continuous Integration testing should be your reliable hero, allowing your developers to fix their code errors quickly and in real-time, before the errors cause issues during later stages of development.
Types of Continuous Integration Testing
There are a few distinct types of Continuous Integration testing, to ensure that any issues in your software builds are caught as soon as possible:
Unit Tests focus on the blocks/methods of code that change with every developer’s commit. It looks at the smallest factor in the equation: each single unit of code. By testing every unit of code against set parameters, it ensures that each code unit adheres to quality standards. Plus, unit tests are very lightweight to perform, as they work with such small quantities of code.
Integration tests are more wide brush than unit tests, focusing on testing a few of those code units together, to ensure that their interactions work correctly. They verify that the unit interactions will not break when used in real-world user scenarios.
Code Quality Tests
Code quality tests look at the overall quality of the source code, serving as a gate to check in or merge code. It’s important to note that the definition of “quality” varies from team to team, depending on the team’s context and infrastructure.
Risk & Security Tests
Risk and security tests ensure two factors: the compliance of licenses for any open source components that the developer chose to use, and the mitigation of risk through code analysis. It ensures that security is integrated early into the SDLC for the same reason that all other early tests are performed: to prevent the need for backtracking and fixing issues later down the line.
Continuous Integration Testing Tools
Now that we’ve covered the why behind CI testing, let’s discuss a few solutions that can be added to your Continuous Integration toolkit and make your automated testing practices the best they can be:
Predictive Test Selection - Launchable’s ML identifies and runs tests with highest probability of failing based on code and test metadata, speeding up the development feedback loop.
Avo Assure- Avo Assure is a scriptless, test automation platform that enables you to check the quality of every element of your business application - from the visual layer, through the underlying service processes and messages, and databases.
SmartBear- Smartbear provides a whole host of products, created for different use cases when implementing continuous testing. It’s a great way to tailor your testing suite to your business’s specific needs, by concentrating on specialized testing, such as API or UI performance.
Tricentis Platform- Tricentis’s continuous testing tool enables testing across the SDLC, including in the CI stage. They leverage AI to create an intelligent automated testing platform.
Qase- Ranked as a Spring 2022 High Performer by G2, this product enables teams to work together with a simple, clean interface and collaboration.
When evaluating tools, it’s also important to consider if you want to natively test within your build agent/runner, or use a third party by submitting data, code, or an artifact to a third party from the Continuous Integration process. For example, when scanning a container, the image would be introspected by an external process (e.g. container scanning software). It ultimately depends on what your system’s infrastructure looks like.
Shift Left and Continuous Integration Testing
Ultimately, Continuous Integration testing supports the concept of shift left, or moving processes to be early in the SDLC. A “shift left” mentality prevents the time and cost waste of needing to backtrack and fix problems later downstream. By shifting left, CI testing creates:
Happier developers, because they no longer have to retroactively fix downstream code that was written a long time ago
Happier QA and security teams, because they no longer have to be the “bad guys” who tell the developers about said issues, and because they don’t have large, “snowballed” problems to mitigate.
Faster releases, as lots of the testing is done and accounted for before the code even reaches the test environment.
Launch Fearlessly: Continuous Integration Testing with Launchable
At Launchable, we empower teams to run tests intelligently throughout the CI/CD pipeline, allowing them to narrow down which tests they’re performing and only focus on the ones that really matter and function well. By helping teams pick the best tests for their business needs, we allow them to minimize false positives/negatives, avoid flaky testing, and save time by only running the tests that matter to each situation.
For example, Launchable’s Predictive Test Selection allows for shifting left with unit testing. By using machine learning, Launchable ranks unit tests for each code change and creates a unique subset based on this ranking, meaning that only some pieces of your testing suite will be run against each unit. We aim to cut down on the number of tests performed with Predictive Test Selection, saving time for your developers.