Operations | Monitoring | ITSM | DevOps | Cloud

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Resolve issues faster without leaving Slack. This video shows how Grafana Assistant delivers real-time insights, automates troubleshooting, and helps you investigate and act on incidents directly where your team already works. Thanks for watching!

Get more accurate results with Grafana Assistant. Use specific prompts, set context with @, and enhance intelligence with MCP and memory to build dashboards and insights tailored to your environment.

Create full monitoring dashboards from a single prompt. Grafana Assistant analyzes your stack, builds key metrics instantly, and suggests next steps, so you skip complex queries and move straight to actionable insights.

Ask a question, get a system-wide answer. Grafana Assistant maps your architecture, builds service diagrams, and runs queries behind the scenes, so you can troubleshoot faster without writing complex code or hunting through dashboards.

Make Grafana AI Assistant work your way.

Overview & demo of how Cloud provides an end to end Observability Platform that empowers users who have adopted open standards like or to improve their systems reliability using & a shift left approach with performance testing while optimizing their observability costs.

In the March edition of the Kubernetes Monitoring Helm chart office hours, we discuss the version 4.0 major release, the upcoming 4.1 release and features, and we discuss the upcoming deprecation of the 1.x and 2.0 versions.

In this Campfire Community call, we'll be exploring Grafana's release pipelines - covering both our on-prem (public and private) artifact delivery and our Rolling Release Channels for building Grafana Cloud We'll walk through the fundamentals of how our pipelines work, including how ICs can patch branches and manage their own core Grafana releases, and where we're headed in the future. Plus much more!

The results show strong interest in AI for forecasting, root cause analysis, onboarding, and generating dashboards, alerts, and queries. But when it comes to autonomous action, practitioners are more cautious — and 95% say AI needs to show its work to earn trust.