At the SauceCon 2019 conference, Sauce Labs today revealed it has acquired Screener to add a visual testing tool to its portfolio of automated testing tools.
Lubos Parobek, vice president of product for Sauce Labs, said the addition of Screener will make it possible for DevOps teams to not only test functions and performance using existing Sauce Labs tools, but also now confirm things such as the colors of a visual element of an application are being rendered correctly, for example.
In addition to building their own visual tests, DevOps teams can employ Screener to automate the running on those tests and store baselines in the cloud to create a visual testing life cycle.
At the same time, Sauce Labs announced the general availability of Sauce Headless, which leverages container technologies to make it possible to leverage a cloud service through which developers can now run tests via a Chrome or Firefox browser every time they commit code. Parobek said the goal is to make it easier for organizations to embrace continuous testing as an extension of the pipelines constructed using a continuous integration/continuous deployment (CI/CD) platform.
The acquisition of Screener, he said, is part of an ongoing Sauce Labs effort to extend the reach of its testing portfolio beyond functional testing. Sauce Labs earlier this month launched Sauce Performance, its first set of application performance testing tools.
The rise of DevOps is challenging traditional approaches to application testing as organizations move to combine various types of testing into a single continuous process. To meet that requirement, Sauce Labs is expanding its portfolio of automated testing tools at a time when the emergence of microservices-based applications is significantly increasing the level of dependency between all the components that make up an application. That increased level of dependency will require DevOps teams to rely more on automated testing tools. In fact, Parobek said the day is not far off when DevOps teams will include digital assistants that leverage machine learning algorithms to enable DevOps teams to continuously run those tests at the right moment in an extended DevOps pipeline. Those digital assistants will not replace the need for human testers anytime soon, but they will augment their capabilities to make is feasible to implement continuous testing at scale, he noted.
In the meantime, as application testing continues to shift further left in the DevOps process, more developers will be building and running their own tests during earlier stages of the application development process. At some point, either another developer or dedicated tester still will need to evaluate that code to provide an unbiased opinion. But the number of common mistakes making it into the latter stages of the application development process should be substantially reduced. Ultimately, that shift to the left should result not only in more development projects meeting deadlines, but just as significantly higher levels of overall application quality. The challenge now, of course, is figuring out how to implement a best DevOps practice that pushes application testing as far to the left as possible.