Operations | Monitoring | ITSM | DevOps | Cloud

The Uptrace team is thrilled to announce the release of v2.0—our biggest update yet! This release represents a complete reimagining of how observability data should be stored, queried, and managed. With multi-project support, revolutionary JSON-based storage, powerful data transformations, and a host of developer-friendly features, Uptrace v2.0 is designed to scale with your growing infrastructure needs.

Healthcare IT environments have become incredibly complex. Think about everything running simultaneously in your organization: physical medical devices, cloud platforms, clinical applications like Epic, and patient-facing applications. Each component needs to work together seamlessly, much like how ICU monitors track multiple vital signs at once. Many healthcare organizations still use monitoring solutions designed for simpler times, when systems were more isolated.

We’re thrilled to share that Grafana Labs has been recognized as a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms—for the second year in a row. This year’s report placed Grafana Labs furthest in “Completeness of Vision,” which we believe reflects our deep commitment to building a truly open, composable observability stack that gives users flexibility, control, and the tools to own their observability strategy.

Observability has an investigation problem, and dashboards and alerts aren’t enough for solving problems in today’s complex systems. AI-driven capabilities, powerful analytics, and the ability to scale are essential to drive real-time investigations while keeping costs low. We think this is why Elastic has been named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the second time.

We are thrilled to announce that, for the fifth consecutive year, Datadog has been named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms. We believe that this recognition reflects our continued focus on helping customers observe, secure, and act on everything that matters across their technology stack.

One of the most common challenges in modern software engineering today is understanding how requests flow through applications. As system architectures shift to favor widely distributed, cloud-native designs, keeping track of how an application processes user actions is more difficult than ever. A single user action may trigger events processed in dozens of backend services. Traces are helping software developers today with this challenge.

Let's be honest: most conversations about AI ethics sound like they're happening in a boardroom, not an ops room. But here's the thing, when you're using AI to make sense of your telemetry data, ethics isn't some abstract concept. It's the difference between insights you can trust and algorithmic noise that leads you down the wrong path. The uncomfortable reality? Your AI is only as ethical as the messiest, most biased piece of telemetry data you feed it. And if you think your data is clean, well...