Testing in production involves evaluating software directly in a live environment as real users. It’s becoming increasingly common.

Imagine your app faces a sudden surge in users. Thousands log in at once. Can your system handle the pressure, or will it crash?

APIs are essential to modern applications, but managing access and security policies can be complex. Traditional access control mechanisms can fall short when flexible, scalable, and fine-grained control over who can access specific resources is needed. This is where OPA (Open Policy Agent) steps in. OPA provides a unified framework for consistently defining and enforcing policies across microservices, APIs, Kubernetes clusters, and beyond. Consistent policy management is essential for enterprises.

Let’s Take an e-commerce platform, where there are different services for user authentication, product catalog, and order processing. These services communicate through APIs. For example, the order processing service needs to get product details from the catalogue service. Contract testing ensures that the agreement between these services—specifying what data the order service expects from the product catalogue service—stays consistent.

Did you know that the AI market size is likely to reach USD 826.73 billion dollars by 2030? Yes, you read it right! The use of artificial intelligence can be seen in every field. AI in UX design is bringing about a revolution in the way users interact with technology. Traditionally, UX design relied on designer intuition, manual processes, and labor-intensive user testing. No doubt, the conventional approach had a positive impact on the user experience.

The end goal of the Testing Center of Excellence (TCOE) is to drive the shift from fragmented, project-based QA efforts to a unified governance structure. It was a pre-Agile innovation to bring testing from the “background” to the center of the SDLC. The arrival of Agile renders the traditional TCoEs obsolete.

There is a sense of growing maturity in the DevOps market that is also reflected by its evolving tools. For the past some time, I’ve also seen these tools expanding beyond the limited utilities of continuous integration and continuous delivery. They are now seeping into database management, QA automation, and even AI integration in the SDLC. However, I see no deviation in their efficiency that enables teams to transition smoothly from ITOps to DevOps.

In this article we’ll learn about Sheets in SwiftUI. We will explain when, and how, to use them, we’ll explain how they’re created and shown. We’ll also look at a few examples of their usage. Let’s get started!

In the fast-paced world of software development, the efficiency of build processes plays a crucial role in maintaining productivity and code quality. At ThoughtSpot, while Gradle has been effective, the growing complexity of our projects demanded a more sophisticated approach to understanding and optimizing our builds. This requirement prompted us to explore Build Analytics—harnessing data from our build processes to gain actionable insights.

What’s one thing all your favorite legal shows have in common? Whether it’s Suits or The Lincoln Lawyer, they rarely show the amount of paperwork lawyers have to handle on a daily basis. Understandably so, paperwork isn’t the most glamorous part of the job but that doesn’t mean it’s not crucial. In fact, lawyers deal with tens, if not hundreds, of documents on a daily basis during most parts of their job, such as discovery, research, or drafting.