The temptation to dive into user experience design without actually testing to see if your efforts are taking you in the right direction may be weighing on you right now, especially if there are other pressures that are prompting you to push forward with a project as quickly as possible. However, good UX testing can make for a great end product that is not only more satisfying for end users, but is also easier to manage, maintain and update at the backend.

We’ve written about the importance of testing before. If you’re in development, you’re no doubt familiar with agile methodology. But sometimes a test-driven approach seems at odds with going fast. And how do you best communicate the importance of testing to everyone on your team? If you’ve felt frustrated with test-driven development or don’t have buy-in from your team, behavior-driven development is there to help.

There are two ways to test software. The first and most obvious is to simply allow users to test functionality by using the software as it was intended. This is the method likeliest to produce the most useful and practical results. The other method is by automating testing. This requires a second piece of software designed to provide input and analyze output from the original application.

In this article you will learn how to generate Jaeger model classes and gRPC services from protobuf definitions. The generated code can be used to write integrations or it can be used in tests to query tracing data from Jaeger-query service. This is the use case we are going to look at in more detail.

The idea of applying artificial intelligence and machine learning to more rapidly and accurately resolve IT incidents and manage alerts has been gaining steam in the past year. While AIOps, as it’s frequently called, has spawned an entirely new market of startups, many enterprise IT leaders are playing a cautious hand so far – and for good reason. There are risks, though. If an AIOps tool goes wrong out of the gates, IT and executive trust diminishes.