Operations | Monitoring | ITSM | DevOps | Cloud

Run cost-effective, always-on agents to monitor your environment: the engineering behind Watchers

Alert rules are great for the failures you can predict, but they fall short on the ones you can't. With the advent of modern AI, you might think the solution is to swarm your stack with agents that monitor every last detail, but that can quickly lead to astronomical bills. And those are the gaps Watchers fill: catching what alerts miss while keeping costs in control. Generally Available as of ObservabilityCON 2026, Watchers are always-on agents in Grafana Assistant.

Any agent anywhere: How to use Grafana Cloud with Claude, Cursor, and any other AI agent

AI agents are becoming part of everyday engineering workflows, helping teams write code, troubleshoot issues, and automate tasks. But to be truly useful in production, these agents need access to more than code. They also need observability data and context to understand what's happening across your systems, investigate problems, and help you take action.

What's new with Grafana variables: less clutter, easier reuse across dashboards, and more

Template variables are one of the most used features in Grafana, providing users with a dropdown to turn one dashboard into hundreds: pick a different cluster, region, or service, and every panel updates. For most of Grafana's history, variables had a single home at the top of the dashboard. Each dashboard had one flat list of variables, and that list was shared by every panel on it. But as dashboards grew in size and number, those controls became harder to organize and maintain.

Trace linkage: connect the dots between your app traces and database queries

When an application request slows down, a trace can show a database call. Finding the database query behind it can be tedious, requiring you to switch between traces and database telemetry, as well as match timestamps or query text by hand. In Grafana Cloud, the Database Observability app already provides a window into all of your database telemetry, including query samples, performance history, and explain plan.

Bridging Alloy and OpenTelemetry: the OTel engine is now in Public Preview

Many Grafana Cloud customers love what Alloy offers them, but we're also seeing a growing base of users who feel the same way about the OpenTelemetry Collector. We want to make it easy for customers to make the decision that makes the most sense, regardless of their preference.

Instrumentation Hub in Grafana Cloud: start easier, stay in control

It's no secret that getting started with observability can be much harder than it should be. That's why, at ObservabilityCon 2025, we introduced Instrumentation Hub: a guided, scalable way to roll out observability coverage while still keeping you in control. Today, we’re excited to announce that Instrumentation Hub is now Generally Available in Grafana Cloud.

Grafana 13.3 release: manage variables across dashboards, share findings with Notebooks, a UI refresh, and more

Grafana 13.3 is here, bringing more consistency and control to how you work across Grafana. Cross-dashboard variables help you manage shared dashboard controls from one place, while Notebooks let you capture and share findings from across Grafana in a single, editable document. You'll also get a first look at Grafana's biggest visual refresh since Grafana 7, along with new ways to guide and refine dashboards built with Grafana Assistant.
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We've Never Shipped Code This Fast. Understanding It Hasn't Kept Up.

Ask anyone where dev ends and ops begins and they'll struggle to draw the line. That's the point of the last decade of DevOps: the two disciplines merged so completely that the boundary stopped mattering. But ask where building ends and understanding begins, and everyone answers instantly. Right after deploy.

Evaluate AI models for observability: o11y-bench joins Fireworks' Specialized Intelligence Index and reaches v1.1

When evaluating AI models for observability, generating a plausible query or explanation isn't enough. Teams need to know whether an agent's conclusions are supported by telemetry, whether its changes to dashboards actually work, and whether it can deliver reliable results consistently. This is why we built o11y-bench, Grafana Labs' open benchmark for evaluating AI models on observability and SRE tasks. And today, we're excited to share two updates.

Agent Observability FAQ: Understand the value of monitoring, evaluating, and improving your AI agents

Agents have quickly become part of the tech landscape as organizations embrace AI across their businesses. But embracing agents also means embracing the monitoring best practices that have long been part of engineers' workflows: tracking performance, catching errors, and responding to incidents But it doesn't stop there. Agents also introduce new challenges.