Building quality software requires efficient and effective software testing processes. To achieve this, it’s important to make sure your test management tool has the capabilities to support your team’s current, and future, testing needs. By following this three-step approach, you can narrow down your choices and find your perfect fit. Break out your notepad and follow along to see if your team’s needs are best described by options A, B, or C.

Software testing can feel like you're walking a tightrope—striving to uphold impeccable quality standards while the clock ticks towards your next release. It’s a daunting challenge to make sure every test is planned and executed with speed, all while hoping there are no blind spots in your process. Enter test management. It’s a great way to ensure your tests remain organized, efficient, and consistent. And of course, so you can report on this hard work to leadership.

As software systems become increasingly complex, observability — the ability to understand a system's internal state based on its external outputs — has become a critical practice for developers and operations teams. Traditional observability approaches struggle to keep up with the scale and complexity of modern applications. As the amount of telemetry data grows, it becomes expensive and complex to navigate. Enter AI and its promise to revolutionize observability.

Agile software development places significant value on faster processes and better-quality outcomes, but there are a lot of different techniques that teams can leverage to achieve these goals. For many, automation integration has become a major priority, but there are several benefits to be seen from manual operations like exploratory testing. Let's take a look at what advantages exploratory testing can bring to agile environments.