Systems | Development | Analytics | API | Testing

Automation testing is now the default for modern QA teams. Instead of spending hours manually clicking buttons, filling out forms, and triple-checking for bugs (only to miss one in production), testers can write a script once, and the machine takes over. It can mimic the user’s actions, flags issues, and gives teams back hours that they can use for more strategic tasks. When done right, automation testing is a game-changer.

APIs are the backbone of modern applications. They connect services, share data, and power almost every feature you see in a web or mobile app. As software becomes more complex, QA teams rely on web service testing tools to make sure APIs work as intended. These tools help you validate functionality, performance, and security while speeding up test creation and execution. With so many API testing tools available today, choosing the right one can feel overwhelming.

Today, we're going to have a little history lesson for those of you who haven't been around since forever, but for those of you who have been around since forever, hopefully this will be a nostalgia fest. We can enjoy some good memories together. From FTP to Kamal, an oral history of deploying Rails apps. Watch the video for the full story!

Record sessions in the background: Multiplayer saves recordings the moment bugs or anomalies occur, making it effortless to capture elusive, hard-to-reproduce problems. Most session recording tools force you into a tradeoff.

Chatbots have quickly moved from novelty to necessity. With over 987 million users and platforms like ChatGPT receiving more than 4.6 billion monthly visits, chatbots are now core to how people interact with digital products.

Solo.io Gloo Gateway gives teams a reliable way to secure, route, and monitor API traffic in real time. With its high-performance Envoy core and Kubernetes-native design, it meets the demands of distributed applications and modern service architectures. However, performance metrics alone don’t reveal how developers engage with your APIs or why adoption stalls.

As your application grows, the volume of telemetry data expands with it. Every additional service, customer, and feature generates more log entries. It becomes harder to quickly isolate the events that actually matter. Without the right tools, finding a single root cause can feel like searching for a needle in an ever-growing haystack. You may have already been using log search tools to find and act on errors. However, those tools rarely connect that data back to your API traffic patterns or metrics.

How flexibility and interoperability can help you overcome vendor lock-in.

As AI models become commoditized, the conversation is shifting from building smarter models to building data infrastructure that turns models into real business value. Enterprises are accelerating their adoption of agentic AI—systems that don’t just predict but plan, decide, and act autonomously—across their software and operations.

Streaming at scale just got a lot more powerful and cost-effective. Our Q3 Confluent Cloud launch is packed with innovations to help you do more with less: reduce cloud networking costs while maintaining your security posture, scale effortlessly with boosted connection limits, and build production-ready agentic artificial intelligence (AI) applications with seamless tool integrations.