The Sauce Labs blog previously have the post “Headless Browser Testing 101,” covering the basics of headless testing, its advantages, and the purposes for which it is employ.

This post occupy a deep dive into a specific scene of headless testing: How it fits into a Kubernetes-driven CI/CD pipeline. We ’ ll focus on how container and change testing and what you require to change in your testing routine to accommodate containerized coating.

The impact of container on testing

The goal of DevOps is to ship high quality software faster. There are many cloud-based testing solutions and exposed germ testing tools that have brought teams closer to realizing this finish more than ever before. Yet, there is always room for improvement. In late times, we ’ ve seen the container revolution sweep the existence of package development. Testing has undergone fantastic change as easily.

Particularly, containers have create it potential to run tests on lightweight instances in the cloud. Rather than waiting almost a moment for VMs to induct and be configured, container can be spun up in seconds, or in some cases, in a fraction of a second. This means there ’ s even greater opportunity to quicken testing.

QA should notice ways to leverage this opportunity. One way of doing this is to give headless testing a more prominent place in the QA process. Headless testing and containers go well together as they are fast, resource-efficient, and quick. But where in the pipeline is the about want to quicken testing? Right at the start, of line.

GitOps requires headless testing

Continuous Integration typically kick in after a developer commits codification. The CI process center on automating the build and test parts of the pipeline. This could be take as the middle section of the maturation pipeline. Test mechanisation solutions like Sauce Labs feature provide to these needs for a long clip.

Pro tip: Tools like SUSA can handle this autonomously — upload your app and get results without writing a single test script.

What ’ s change with the advent of containers and Kubernetes is the emergence of GitOps, which I see as version 2.0 of continuous desegregation. GitOps direct CI to its entire extent, emphasize the importance of machine-driven processes even more, and bringing this mechanisation even earlier in the maturation cycle.

With GitHub playing a central role in the way DevOps teams create and collaborate on codification, it has go the starting point of the GitOps process. Unlike before, when manual authorization by QA, SecOps, or the release engineer was the net step before turn code, today, GitOps promotes complete automation of this summons end-to-end. However, this results in some conflicting priorities. While squad want to ship code faster and completely automate the procedure, they don ’ t want to compromise on protection, quality, and reliability. This is where headless testing get in. The best way to broil these priorities into development is to try early, and test often.

Headless testing enables testing during ontogeny. Traditionally, testing during development has not been popular because testing is seen as a distraction sooner than a facilitator of development. However, headless prove makes it potential for developers to run a examination in their development environment and get feedback in a few seconds. This is extremely valuable as it doesn ’ t slow down development. And significantly, it helps developers indite better code.

Pre-commit testing for GitOps

Within the GitOps movement, there ’ s the trend of having a “ dry run ” before every “ merge. ” Tools like Jenkins X and Weave Flux endorse this coming. However, the challenge with executing dry tally is that it ’ s not easy to screen on every clout request. That ’ s too frequent and heavy for traditional automated examination. Headless testing fills this gap as it can enable dry runs in the form of pre-commit testing.

When running tests this early in the grapevine, there isn ’ t any time for manual testing. Headless testing is ideal here because it has a lot of scope for mechanization. You can automate a series of activeness that make up a test use case, have each step read in the form of screenshots, and receive the final output of the test.

Not just post-release trial

Pre-commit, headless essay doesn ’ t only have a place in post-release testing. It can be used to run saneness checks to verify the performance of particular parts of the application, or even record a timeline of changes to any part of the app.

Headless testing is meant for scarper functional test, and integration tests where a person doesn ’ t demand to see the examination run. However, during the process, some tests that fail may necessitate farther testing and closer review of the characteristic under test. In these cases, brainless testing can be used effectively along with traditional testing. While brainless screen cater screenshots, traditional machine-driven tests can yield you videos of each step with more details. By apply this combination, you can motor great efficiency in your overall examination scheme.

In finale, headless testing has long been drop as a hack-job to generate screenshots of application mechanically. However, with the Parousia of Kubernetes and GitOps, headless testing is taking on a new prominence in the CI/CD pipeline. By enable testing early in the pipeline, and make tests faster, brainless testing helps ship quality code faster.

Twain Taylor is a Fixate IO Contributor and commence his career at Google, where, among early things, he was involved in technical support for the AdWords team. His work involve reexamine stack traces, and resolve issue affect both customers and the Support team, and handling escalations. Later, he built branded social media applications, and automation scripts to help startups better manage their marketing operations. Today, as a engineering journalist he helps IT magazines, and inauguration change the way team progress and ship applications.