Systems | Development | Analytics | API | Testing

We’re excited to announce the general availability of Kong Insomnia 11! This release introduces third-party vault integrations for enhanced security, an all-new Git sync experience for more seamless collaboration, and support for multi-tabs to improve efficiency within the Insomnia application. Keep reading to learn more.

With the release of Node.js v23.6.0, developers can now use TypeScript natively without additional transpilation tools like ts-node or manual compilation steps. This milestone significantly streamlines development workflows, simplifying build processes and improving the overall developer experience by reducing complexity.

Dialyzer (DIscrepancy AnaLYZer for ERlang programs) is a powerful static analysis tool that helps developers identify potential issues in their Elixir code without executing it. It excels at finding type mismatches, unreachable code, and unnecessary functions through sophisticated flow analysis. In part one of this two-part series, we'll first get to grips with the basics of Dialyzer. In part two, we'll examine more advanced use cases.

The era of AI experimentation is over. Organizations want to see ROI. And they will—as long as they understand that the competitive edge isn’t in AI itself. With AI evolving rapidly, businesses need a clear strategy that cuts through the noise and generates ROI. This key strategy is to embed AI into core business processes. This post will cover five enterprise AI trends for the new era of AI and why process is the key to ROI. The most talked-about trend today is agentic AI.

In C++, when you create a new object (like a database connection or a game character), a special function called a constructor runs automatically to set up that object. Think of constructors as the "birth" process for objects—they allocate resources, set initial values, and make sure the object starts life in a valid state. But what happens when something goes wrong during this setup? Maybe a file can't be opened, a network connection fails, or invalid data is provided.

AI-powered code editors are speeding up API development by automating repetitive tasks, improving security, and optimizing performance. Developers now spend 55% less time on API creation, focusing more on design and business logic instead of boilerplate code. These tools reduce errors, generate real-time documentation, and enhance scalability, making API development faster and more efficient.

Enterprises working in Microsoft Azure need to mask data, and they need to mask it quickly.Yet, it can be difficult to find Azure data masking methods that are both swift and secure. The wrong approach can lead to bottlenecks, compromised analytics quality, and significant regulatory risks.

When your company deployed its first large language model last quarter, your CTO probably didn't mention you'd need entirely new tools to understand what's happening under the hood. But here we are. AI Observability isn't just another tech buzzword—it's the difference between confidently leveraging AI and crossing your fingers hoping nothing breaks.

Motorsports have always been synonymous with speed, precision, and innovation—both on the track and in the way they engage fans. In an era where digital experiences define audience expectations, realtime data has become the driving force behind deeper, more immersive fan engagement.