What's new from Grafana Labs
Grafana Labs products, projects, and features can go through multiple release stages before becoming generally available. These stages in the release life cycle can present varying degrees of stability and support. For more information, refer to release life cycle for Grafana Labs.
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Grafana Fleet Management now includes the Grafana Cloud Integrations catalog, combining the preconfigured functionality of Integrations and the scalability of remote configuration.
Choose from a list of platform-specific integration templates to automatically build configuration pipelines in Fleet Management and then assign attributes to match those pipelines to specific collectors.
You can now provision your Grafana Fleet Management collectors and configuration pipelines using the Grafana Terraform provider (v3.19.0 or later).
Use Terraform to preregister new collectors for the Fleet Management service, add remote attributes to collectors that are already registered, and build configuration pipelines to remotely configure your fleet. With Terraform and Fleet Management, you can create a stable, consistent, scalable observability setup.
Last year we introduced one-click data links and actions for canvas visualizations in public preview and experimentally respectively. With the One click switch toggled on, it takes just a single click to open a data link or trigger an action. Now, both of these features are generally available for the canvas visualization.
Out-of-the-box, built-in alerts help you spend less time troubleshooting and more time focusing on what matters.
- Prevent slowdowns: Get alerts for high CPU usage in AWS EC2, Azure VMs, and GCP Compute Engine.
- Keep databases running smoothly: Avoid failures with alerts for deadlocks, failed connections, and disk space limits.
- Optimize storage and messaging: Stay ahead of storage constraints and ensure messages are delivered on time.

Whether you’re running on AWS, Azure, or GCP, you can fix issues faster because of real-time notifications, including:
We’ve fully deprecated API keys in Grafana, and all existing API keys have been automatically migrated to Service Accounts. No action is needed on your part—your API integrations will continue to work seamlessly while benefiting from improved security and management features.
We’re excited to unveil our latest update to the Generative AI Observability Cloud integration.
AI Observability is a Grafana Cloud integration we released late last year, designed to provide insights into gen AI application performance.
By leveraging OpenLIT, the OpenTelemetry-native, open-source SDK, it simplifies the monitoring, diagnosis, and optimization of generative AI systems. This integration automatically instruments over 50 gen AI tools, including LLMs, vector databases (vector DBs), and frameworks like LangChain and LlamaIndex, streamlining your setup process.
Our integration not only guides you through the setup but also offers pre-built dashboards that can be customized to fit your needs. These dashboards, focused on LLM & VectorDB Observability, now include an exciting new feature: OpenTelemetry-based GPU monitoring! This new capability enables you to track GPU performance through key metrics such as utilization percentage, temperature, power consumption, and more, allowing you to optimize the efficiency of your AI workloads.
View how persistent volume (PV) changes over a specific time range in the storage tab on the Cluster, Namespace, Workload, Node, and Pod detail pages.

Grafana Service Center is now in public preview. The Service Center provides users a single pane of glass into key operational resources, including SLOs, Incidents, and Dashboards with more resources coming soon.
All Grafana SLO dashboards are now natively integrated with a Grafana SIFT panel. SIFT automatically checks burning SLOs for common issues and reports back using the SIFT panel in all auto-generated SLO dashboards. You can also manually run SIFT checks from the Grafana SLO dashboard.
One of the basic goals of performance testing is to ensure your applications perform well under various levels of traffic. However, most performance tests are conducted with minimal insight into why a system performs a certain way during testing.

Want to easily stop ingesting your low usage log lines? Adaptive Logs now makes this even easier, allowing you to filter recommendations by how often they are queried. Now, even fewer clicks to apply recommendations for logs which are never queried or rarely queried. This UI enhancement makes it easy to quickly get started with, and get value from, Adaptive Logs.

Adaptive Logs introduces support for exempting specified logs from drop recommendations to Grafana, giving you greater control of your data.
You can tell Adaptive Logs to not drop log lines from certain streams using the Stream selector. This ensures specified logs are ingested into Grafana Cloud, and not dropped by Adaptive Logs, no matter what our usage recommendations initially suggest. Our recommendation engine also updates to include the exemptions you specify.

Manage notification policies through Role-Based Access Control (RBAC). Choose who can create, edit, and read notification policies using fixed roles.
You can only grant different access levels to the entire notification policy tree; not to individual notification policies.


