Systems | Development | Analytics | API | Testing

Evolve25: Cloudera Product & Strategy Keynote

Learn how to eliminate the gap between public and private clouds with a unified data fabric that offers one-hour time-to-value.. Discover how the acquisition of Octopai and Taikun enables automated data lineage and seamless Kubernetes deployment across any environment. From private AI inferencing to Spark 4 upgrades, see the future of enterprise data management and hybrid cloud portability.

JavaScript Exception Handling: try, catch, throw, async & Best Practices

Exceptions are inevitable. It’s how we deal with them that matters. An effective exception handling regime is the difference between an app that only works in sandbox and one that can adapt and scale in the real world. JavaScript can throw up all kinds of weird and wonderful exceptions, because it runs in inherently unpredictable environments. So we’ve put together this guide to give you a clear, repeatable plan for handling them.

Spring Boot API Testing: A Practical Guide for Enterprise Teams

Enterprise Spring Boot APIs should be tested at three levels: unit tests for business logic, integration tests for external service behavior, and traffic replay for production edge cases. Most teams only do the first. This guide shows all three using a real Spring Boot application that calls external APIs (SpaceX, US Treasury) with JWT authentication. The kind of service that looks simple in development and breaks in production.

Debugging Encrypted Microservice Traffic with Speedscale's eBPF Collector

Production bugs that only reproduce in actual traffic can be some of the most frustrating bugs in software development. You can stare at your logs, add traces to your code, add instrumentation – and still not be able to see the actual requests that went over the wire. And that gets even harder when the requests are encrypted and the system is a black box. You can use tools like Wireshark or Kubeshark to capture the requests.

Jenkins vs Codemagic: Why Mobile Teams Are Making the Switch

If you’re a mobile developer running builds on Jenkins, you already know the drill: a flaky agent goes down on a Friday afternoon, your Xcode version is three months behind, and the DevOps engineer who set the whole thing up left six months ago. The builds ship eventually - but at what cost? Jenkins is a powerful, battle-tested automation server. For teams building web backends or managing complex polyglot pipelines, it earns its place.

Simplified Kafka Cluster Migration: Strimzi to AWS Express Brokers with Lenses

Migrating Kafka clusters doesn't have to be a complex or high-risk operation. In this technical walkthrough, we demonstrate how Lenses K2K managed through Lenses 6 simplifies the migration of mission-critical banking applications from Strimzi to AWS Express Brokers with minimal downtime and zero data loss.

What made the first TrueTest implementation successful, and what lessons or surprises came from it?

The first TrueTest implementation succeeded because the team aligned early on clear goals and maintained an open, realistic mindset about what AI could deliver. By being transparent, receptive to guidance, and working in a stable environment, they were able to move quickly and achieve measurable value much faster than expected, which was the biggest and most positive surprise from the implementation.

JRebel and XRebel: The Ultimate Power Duo for Java Development and Performance

Every minute spent waiting for your IDE to build, package, and redeploy code is a minute taken away from what matters most: writing better code. JRebel and XRebel give Java developers the power to eliminate redeploy wait times and catch performance bottlenecks in real-time — so your team can focus on shipping high-quality features faster.

Tricentis AI Workspace: The new control plane for autonomous quality engineering

AI is reshaping how software gets built, tested, and delivered. For quality engineering teams, AI agents promise extraordinary acceleration by automating analysis, executing tests, generating assets, and orchestrating tasks across the SDLC. But when enterprises begin experimenting at scale, new challenges appear. Where are these agents running? What exactly are they doing? Who approves their decisions? How do we govern them safely?