Parallel testing enables teams to run multiple tests simultaneously, providing several benefits to QA teams that improve cost, efficiency and confidence.
Parallel tests are not a perfect solution to testing problems as they come with challenges such as dependency issues, limited resources, text environment complexities, troubleshooting limitations, and management and maintenance expenses.
Traditional parallel testing is costly as it requires significant financial investment in hardware and infrastructure, while dynamic parallelization is a more cost-effective approach that reduces wait times for testing and improves efficiency. It also helps to identify ineffective or flaky tests and keeps the team informed.
Software development is all about efficiency — teams want to achieve the best possible outcome with the least effort possible. When it comes to testing, efficiency comes at a premium. Running large, complex test suites costs resources, time, and computing power.
Parallel tests empower teams to maximize testing efficiencies and address time constraints.
With parallel tests, devs run concurrent tests across multiple different environments and devices to reduce testing time. Parallel tests allow teams to significantly speed up testing processes but can come with limitations and increased complexity within your tests.
Parallel tests are most effective when you need to test a large number of cases or configurations. It’s also best when testing multiple environments or versions of your software, but how exactly can you benefit from them?
Parallel tests allow teams to run tests concurrently. By adopting this approach, QA teams gain quite a few advantages.
Increased speed and efficiency. Your dev teams can run multiple tests simultaneously, reducing overall testing time. And with a faster test cycle, you can collect more data and give feedback sooner, so teams can iterate and find solutions sooner.
Reduced testing time and costs. As you’d expect, a faster testing cycle will result in shorter test times overall. And because parallel testing enables teams to run multiple concurrent tests, you’ll save on resources too.
Improved test coverage. With parallel testing, teams have a wider berth when testing for unique scenarios. It allows them to seek out and test unique edge cases that aren’t as practical as traditional testing.
Increased confidence in test results. Combining all of these benefits also boosts your teams' testing confidence. Thanks to the faster speeds and shorter feedback loops, your QA teams can write and perfect their test suites, leading to better confidence and trust.
Parallel tests improve feedback speed and efficiency by allowing dev teams to run multiple tests simultaneously, resulting in shorter testing times and reduced costs. Parallel tests also improve test coverage by testing unique edge cases, increasing confidence in test results by allowing QA teams to write and perfect their test suites.
While parallel tests might seem like the complete answer to bloated test cycles, they aren’t a cure all. Standard approaches to parallel tests have significant caveats that teams should understand before altering their test approaches.
Sadly, parallel tests aren’t the catch-all solution to all of your testing woes. It still offers some unique struggles your team may need to prepare for including dependency issues, limited resources, text environment complexities, troubleshooting limitations, and most significantly of all, management and maintenance expenses.
Parallel tests require multiple instances of an application or system to run concurrently. Often these instances share resources or have dependencies on each other, which leads to conflicts and errors. A common scenario like this would be if two instances of an application try to access the same database at the same time, causing a deadlock. This makes it difficult to accurately identify and isolate issues. If a test is dependent on the output of another test, the order in which parallel tests are executed can also cause issues.
Parallel testing requires a complex test environment setup. This includes configuring multiple systems, networking, and setting up testing tools to support parallel testing. This added complexity can lead to higher chances of environmental issues and delays in testing.
Because of this, keeping your testing environments up to date and correctly configured is a challenge. Each environment your team uses needs to be set up with all the requirements for every test you plan to run, so the more complex the setups that you have to replicate for each parallel environment, the higher the risk of configuration snafus.
Because of the nature of parallel tests, it’s often difficult to identify issues or errors. With multiple tests running simultaneously, it becomes harder to pinpoint the root cause of a failure. Debugging and troubleshooting parallel tests requires more advanced tools that not all teams may have access to.
While teams turn to parallel tests to speed up delivery, you have to weigh that benefit against the issues with debugging to see if they add value or headaches to your testing workflows.
Unfortunately, managing these different environments comes at a premium, whether it’s other hardware or software tools. Managing and maintaining parallel tests requires additional coordination and resources. This can include additional staff to manage and monitor tests, specialized hardware and software tools and maintenance of those tools.
These additional costs can be challenging for smaller organizations or teams with limited budgets. Your team’s infrastructure needs to be able to handle this volume of testing. Otherwise, you miss out on the benefits of parallel tests.
Traditional parallel testing involves running multiple tests simultaneously on different processors or machines. This method is expensive as it requires significant financial investment in hardware and infrastructure. In contrast, dynamic parallelization is a more cost-effective approach in which tests are split into subsets that can be executed in parallel, reducing wait times for testing and improving efficiency.
Launchable takes dynamic parallelization to the next level by leveraging AI to predict which tests are likely to fail and generating subsets accordingly. This approach enables teams to identify issues earlier in the testing cycle, reducing the risk of bugs and improving overall quality. Additionally, the use of AI helps to minimize compute costs by optimizing the subsets generated for maximum efficiency. Launchable's Predictive Test Selection enables teams to ship higher-quality software faster while minimizing costs.
Adopting parallel tests can be a huge boon to your testing efforts. But, like most things in life, it comes with its issues. While it speeds up your testing effort and can reduce costs, it also makes your testing environments more complex and requires a beefy infrastructure.
Thankfully, that doesn’t mean it’s not a practical way to improve your testing. And by using Launchable, you can minimize those drawbacks and speed up your testing process with the power of machine learning.