Creating software is as much about the process as it is about the product. In recent years, we’ve seen the speed of innovation reach new heights due to more efficient development and quality control. DevOps has further accelerated development by combining software and operations in unified, self-improving teams. With automation taking care of rote tasks, developers can now tackle more difficult issues, resulting in even greater software quality and faster development. The need for speed to market is vital; a month or two can make or break a product launch. Then again, if a product isn’t tested thoroughly in the rush to get to market, flaws can slip through and an organization’s revenue and reputation can take a serious hit. In the U.S., software failures in businesses’ operations systems cost a total of almost . The problem is that it can be a bottleneck and create major delays in the release cycle. In fact, A revealed that it is the top reason that releases are delayed.
In the past, the waterfall approach was common. Tests usually took place after code was written; carried out by testers who had no interaction with the original developers. As a result, bugs that could have taken moments to correct during development required days or even weeks to fix afterward. Even worse, the complexity of the finished software and its many dependencies meant that fixing a localized bug could introduce additional problems that needed to be fixed after another round of testing, further delaying the release.
But even in a modern DevOps environment, testers and developers are still speaking entirely different languages. By and large, testers do not code and software developers are not expert testers. The two teams typically converse through multiple logs, event viewers and other operating system tools. It creates a great deal of friction and slows down the process.
DevOps represented a big improvement over waterfall methods but, even so, it’s far from a set-in-stone process. It, too, has evolved and right now, shift left testing has moved into the spotlight.
In this approach, the guiding philosophy is to test early and often, beginning very early in the development cycle and continuously throughout every stage whenever there’s an opportunity. As a result, bugs are caught early when the relevant code is still fresh in the developers’ minds, so it’s easier to fix. In the end, businesses are able to release higher quality software much faster and more frequently.
When it comes to the DevOps process, it’s not always clear where and how to automate the process. The following looks at how that can be incorporated into DevOps based on four different environments in a continuous delivery (CD) pipeline.
These environments include local development (usually a coder’s personal device), a continuous integration (CI) or development server, test servers for user interface (UI) testing and the production environment itself. Each has stages with requirements that must be met for code to advance.
Whenever any new software features or capabilities are entertained, though, developers and the QA team should begin by answering the question, “How can this be tested?”
Once code is created, it must be able to be built without error, passing all unit tests and local verification.
This stage is particularly important because the development environment echoes the requirements of production; if it works here it’ll likely also work for the customer.
At this stage, running early regression and developer verification tests ensures the build is ready while providing feedback about the reliability of the environment. It’s useful to have individual test cases as part of more than one schedule. This enables developers to test minor parts of the software without undergoing regression tests of all product features. These tests should be automated and triggered as part of the same process.
Developers should have the ability to perform basic tests on their own code. After all, the sooner a flaw is identified, the easier it is to eradicate. Just as testers are not experts in coding, neither are developers expert testers. To shift left and effectively integrate tests at all stages of the development life cycle, it must be automated. This will allow developers to test larger quantities of code earlier and more frequently.
Once through this stage, the software can advance to the test environment.
This is where a variety of product tests take place, including those for function, load and performance. Passing this stage entails completing all automated functional UI tests, verification of visual appearance, an inspection of server logs and performance evaluation.
This is where most regression tests are conducted and automation is crucial for scheduled tests to be triggered.
Next, the product moves into the production stage.
Tests still occur in this stage to pinpoint any remaining bugs. Automated tests are then run against the production environment to closely mirror interactions with real end users. At this point, it’s highly unlikely there will be major issues but, if there are, running tests at earlier stages could very well be the culprit.
Throughout the process, ideally, testers will use a visual, no-code tool to create these automated tests. In this way, testers are able to more rapidly and intuitively implement test automation without having to tap into programming resources. Additionally, the integrated documentation of the actions taken during automation will be interactively connected to visual documentation of the test results. The upshot is that testers and developers gain a shared language for both building test automation and troubleshooting the issues it identifies.
Effective, scalable tests are crucial to delivering the reliable, high-quality software that today’s businesses rely on for day-to-day operations. This is why DevOps and development teams need to integrate tests at all stages of software development. Shift left speeds up the creation of better quality software, which provides a significant market advantage. After all, it’s not just about software quality; it can show which companies are best prepared to meet market demands.
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