Introducing o11y-bench: an open benchmark for AI agents running observability workflows

Evaluating agents is hard. Verifying observability tasks is harder. Yes, AI agents have gotten dramatically and quantifiably better at coding and tool use, but observability presents a different kind of challenge. In a real incident, the hard part is rarely just writing a query. It's deciding which signal matters, figuring out whether a spike is noise or symptom, correlating metrics with logs and traces, and sometimes making a change in Grafana without breaking the dashboard another engineer depends on.

Grafana 13 release: get value from your data faster, manage operations at scale, and more!

Who says 13 is unlucky? With the release of Grafana 13, we're giving the community the most streamlined, flexible, and intuitive Grafana experience yet. Unveiled during the opening keynote of GrafanaCON 2026, the latest major release is all about helping you get value from your data faster, whether you’re spinning up dashboards, operating Grafana at scale, or extending the platform as your requirements change. Download Grafana 13.

Git Sync: Observability as code built for scale | Demo | Grafana Labs

In this video, Fabrizia Rossano and Roberto Jiménez demonstrate Git Sync, a feature that provides you with the power of Git version control right in your Grafana instance. Git Sync enables you to submit changes in your dashboards as pull requests and get them reviewed by your team directly from Grafana or from Git.

Grafana 13 TL;DR - What's New (and Worth Your Time)

Grafana 13 is here! In this video, we walk through the biggest updates and improvements, from faster ways to build dashboards to new features that make Grafana easier to manage at scale. We cover things like: If you’ve ever struggled with broken dashboards, messy layouts, or just getting started from scratch, this release focuses on making those workflows a lot smoother. This is a TL;DR, so we’re just scratching the surface—but it should give you a solid sense of what’s new and what’s worth checking out.

Grafana Assistant everywhere: Customize and connect to the AI agent to fit your specific needs

The ways you and your teams build and observe your systems are changing. It’s no longer just engineers looking at dashboards, or writing queries or config files. More often, it’s an agent interacting with the data, too, helping write code, run applications, investigate incidents, rightsize deployments, and more.

Introducing Pyroscope 2.0: faster, more cost-effective continuous profiling at scale

Continuous profiling is becoming a standard part of the observability stack, and for good reason. It's the only signal that tells you why your code is slow or expensive, not just that it is. Metrics tell you CPU usage is high. Logs tell you a request was slow. Traces tell you which service is the bottleneck. But only a profile tells you which function, on which line, is burning the cycles. As systems grow more complex, that level of visibility becomes essential.

Power BI Dashboard Best Practices for Data Engineers and BI Developers

A strong Power BI dashboard is not built solely on visuals. For data engineers and BI developers, the dashboard is the final expression of a much larger analytics system. Its quality depends on the data model's structure, the discipline of the transformation layer, the clarity of the DAX logic, the dataset's performance, and the security model governing access.

Monitor Databricks with Grafana Cloud for instant visibility into your workloads

If you're running Databricks workloads, you've probably asked yourself these types of questions: How much is this costing me? Why did that job fail last night? Why are my dashboard queries suddenly slow? We've been there, too. Databricks is fantastic for data engineering, ML, and analytics. But once you start running jobs, pipelines, and SQL queries at scale, you need a way to keep tabs on what's happening. That's why we built the Databricks integration for Grafana Cloud.