ObservabilityCON 2026: A guide to all the announcements from Grafana Labs | Grafana Labs

Today at ObservabilityCON 2026 in San Francisco, we unveiled a range of new Grafana Cloud capabilities designed to reshape cloud economics, bring richer context and deeper visibility across your systems and end-user experiences, and help teams move toward autonomous operations.
Check out the keynote to learn more about the latest updates to the open agentic observability cloud, and read on for a quick recap of all the news from ObservabilityCON 2026.
With Grafana Assistant in Grafana Cloud, you can bring more of your operational tasks together in one place so you can resolve incidents faster and get back to building. And you're doing it with AI features that automate much of the undifferentiated heavy lifting while still keeping you in control.
Assistant Investigations, generally available since late July, lets you run longer, deeper investigations that can start automatically from an alert or incident, and teams can run them from the platform, Slack, the Grafana Cloud MCP server, or gcx.
And today we're adding new AI features to help you take your automation even further:
With Grafana Cloud, you decide which parts of your operations you want to handle manually and which parts you want to hand off to Assistant.
To learn more about how you can get the most out of Grafana Cloud's AI capabilities, check out our blog posts on autonomous operations and Pages.
In the AI era, where teams are managing more telemetry than ever, they need to be able to find the right log line in seconds. They also need to know they're only storing the telemetry that's worth paying for. That's why we're making major query performance enhancements to Grafana Cloud Logs, built on technology from our Logline acquisition, and giving you more precision with Adaptive Telemetry, so your costs scale with the value you get from your data.
Grafana Labs’ Adaptive Telemetry suite optimizes cost across metrics, logs, traces, and profiles by recommending what to aggregate or sample, so teams keep the telemetry that matters. Customers have cut telemetry spend by 30% to 50% on average.
“Moving to Grafana Cloud and using Adaptive Telemetry cut our metrics costs enough to fund logs and traces as well," says Carl Eastman, Principal Software Engineer, Rapid7. "Our visibility went up while our costs went down, and dashboards and queries are faster and less noisy.”
New updates cover logs, metrics, and traces:
To learn more, check out our Adaptive Telemetry blog post.
Built on technology from Logline, which Grafana Labs acquired in April 2026, Cloud Logs customers are gaining access to faster needle-in-a-haystack queries, at no additional cost.
This full-text search capability, now generally available, helps teams find specific log lines, such as those containing request IDs or customer IDs, without scanning massive volumes of data. Faster queries can also benefit AI-driven investigations, where agents execute a large number of queries to help find root causes.
“When I ran our first query on newly submitted logs after enabling Logline, the improvement was clear,” said Timo Kirzdörfer, OpenTelemetry & Grafana Cloud Admin, DATEV eG. “We went from processing nearly a terabyte of logs in three minutes to around 100 gigabytes in under three seconds. That represents an 80-90% reduction in the volume of logs searched for newly submitted logs, and we saw the results immediately.”
To learn more about full-text search, please visit our docs.
As your systems grow more complex, you and your AI agents need a clearer picture of system health, user experiences, and what needs attention. Our latest Grafana Cloud updates bring more of that context together, expand visibility into the end-user experience, and help streamline everyday workflows.
Most teams have telemetry from across their stack, but connecting those signals to understand what's happening and how it affects users isn't always easy. That’s why we're rolling out new capabilities to advance full-stack observability across Grafana Cloud.
With expanded Knowledge Graph coverage and richer operational context, people and AI agents can better understand how systems fit together to investigate issues and find root causes faster.
A more connected view of your stack
The Knowledge Graph is the runtime context layer in Grafana Cloud that brings together your system's components, their relationships, and health insights in one connected view.
We're evolving the Knowledge Graph to be a platform capability, available in every stack, where you can curate context across Grafana Cloud. We’re also extending the full-stack picture, bringing more of your environment into the Knowledge Graph:
Together, these updates help teams investigate issues across more of their stack, from the user experience for their frontend apps to the services, databases, and infrastructure supporting it.
More operational context for people and AI agents
Knowing how your system fits together is important, but to investigate issues effectively, you also need context that’s unique to your organization, including which teams are responsible for which services and what you've learned from past incidents.
We're bringing more of that context into the Knowledge Graph, and making it available to both engineering teams and the AI agents they work with every day:
The Knowledge Graph is also available as runtime context for AI agents (generally available). Whether you're using Grafana Assistant or bringing your own agent through gcx, this lets you and your agents work from the same shared context.
For a deeper dive on these new features, check out our full-stack observability blog post.
Healthy systems don't always mean happy users. To understand how your applications are really performing, you need visibility into the end-user experience.
In Grafana Cloud, we've been building that foundation for Digital Experience Monitoring by bringing together Synthetic Monitoring and Frontend Observability, connecting proactive testing with real user signals.