Systems | Development | Analytics | API | Testing

At GTC 2026, ClearML announced the general availability of its Platform Management Center, an administrative dashboard purpose-built for IT administrators and AI platform leaders managing multi-tenant ClearML deployments at enterprise scale. Available under the ClearML Enterprise plan, it gives cluster admins a single place to monitor every tenant’s activity, resource usage, and costs while protecting the privacy of tenant workloads and data.

Most teams think they are testing their LLM features. They run a few prompts during development, check that the responses look reasonable, and then ship the feature. Three weeks later, a user enters a strange edge case into the input field. The model confidently gives an answer that is factually wrong, slightly offensive, or completely unrelated. The team spends two days trying to understand what went wrong. In the end, they realize there was no real test coverage, only quick visual checks.

Over the past few years, we’ve watched coding velocity accelerate at an extraordinary pace. AI has completely disrupted how developers build software. Agentic tools can now generate clean code faster than ever before. While AI has turbocharged code generation, code review, and code-level testing, it’s created a massive strain on the rest of the software development lifecycle.

The JavaScript debugger statement is a built-in keyword that tells the JavaScript engine to pause execution at a specific line of code. When execution stops, you can inspect variables, function scope, and the call stack using developer tools. It is commonly used during development to analyze how values change and where logic breaks, without relying on repeated logging or assumptions. No more guesswork. No more partial truths.

Jonas Best & Patrick Polster Kafka migrations are one of the riskiest infrastructure projects a platform team can take on. Miss a dependency and a downstream app starts reprocessing events it already handled leading to breaking SLAs and eroding trust with application teams. Migrate without visibility and you risk a major production issue. The instinct is to reach for a replication tool and call it done. But replication is only one piece of the puzzle.

At Lenses, our goal has always been to help organizations get the most out of their streaming data. We started with visibility into the Apache Kafka, moving up to the part that drives value, the application layer and now the Agentic layer. Lenses 6 moved us into a multi-Kafka world, as increasing, our clients aren’t just running on one type of Kafka anymore, and as sovereign cloud becomes increasingly topical (no pun intended) this is only increasing.

Enterprises in 2026 are under increasing pressure to modernize applications, adopt hybrid cloud architectures, and streamline operations—but their expanding and aging VMware footprints have become a major obstacle. As VMware licensing models evolve and operational costs climb, reducing or restructuring this footprint has become just as critical as adopting new platforms.