Systems | Development | Analytics | API | Testing

May’s release brings significant strides in browser support, cross-platform test execution, and intelligent AI-powered enhancements. Whether you’re running large-scale cloud tests, fine-tuning user journey maps, or adapting to Chrome’s latest changes, Katalon continues to innovate with features that boost precision, observability, and test coverage. Here is what we delivered in May.

The Perforce 2025 State of Automotive Software Development Report revealed that automotive companies are most concerned with quality, safety, and security.

At NodeSource, we’ve always been committed to making the Node.js experience secure, stable, and production-ready for teams around the world. Today, we're announcing a key change to how we serve and support our Node.js binary distributions, and it comes with something new: Extended Support.

In modern software development, the pressure to move fast is matched only by the need to get it right. Teams working within the software development lifecycle (SDLC) must constantly balance velocity and quality, ensuring releases are stable, secure, and performant. Traditional software development models often relied on manual verification and human intuition to validate releases; however, as systems have grown in complexity, guesswork is no longer sufficient to meet these rising needs.

A detailed Software Requirements Specification (SRS) document is key to building software that meets both business needs and user expectations. Clear, concise, and executable requirements align project teams, offer clarity on functionality, and act as a single source of truth throughout development. Whether you're using agile, waterfall, or a hybrid approach, this guide will help you craft clear, complete, and testable requirements.

Enterprise automation didn’t start with AI agents, but they’ve had a much bigger impact than earlier automation methods, such as software scripts or bots. Modern AI agents can do a lot more than tackle repetitive tasks. They can reason through complicated workflows, choose the best course of action, and access tools to execute said action. But to do all this, AI agents require interoperability. They need to be able to connect to numerous tools, databases, services, and APIs.

Before we get started on WebSocket integration, it’s worth quickly explaining how building real-time mobile apps used to work – and why issues with lag and latency led engineers to turn to WebSockets instead. Engineers building real-time Android apps struggled to make sure updates were reflected immediately when a user sent them. To solve this, they tried polling, which meant firing off a GET request to the server, say every five seconds, to a /messages endpoint.

In today's competitive landscape, data warehouses and data lakes are the essential platforms for business intelligence, analytics, and AI. While immensely powerful, these systems were traditionally designed for batch data processing, often leading to insights based on data that is hours or even days old. The primary challenge has always been the complexity of bridging the gap between real-time data streams, typically flowing through Kafka, and these analytical systems.

I was reading about the gRPC recently and was wondering what all this about? Believe me, I was in the same boat not too long ago. I didn’t even know what exactly gRPC means before this. If you’re curious about how to inspect gRPC traffic, check out this guide on capturing gRPC traffic going out from a server. In this blog, I will walk you through everything I have learned about the game changing technology that is changing the world of distributed system.