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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The pipeline history feature in Fleet Management now offers you the chance to restore versions of existing configuration pipelines. From the History details page, choose a version and click Restore.
Pipelines in Grafana Fleet Management can now leverage the Alloy export block to share their components with other pipelines. With pipeline export injection, you can export components from one configuration pipeline and inject them into another using the syntax argument.pipeline_exports.value["PIPELINE_NAME"]["EXPORT_NAME"]. This powerful feature enables you to create dynamic configurations that adapt to each pipeline’s exported values, allowing for flexible and reusable pipeline configurations.
Sort and filter logs with ease in the Logs and Events tables. You can use multiple filters, including:
- Time period
- Component
- Cloud region
- Error level

Find any non-standard workloads using filters on the Workloads main page. Filtering includes:
The memory tab and panels are accessible on any detail page beyond the container level. Now you can view memory usage in correlation with relevant data points, as shown in the screen capture of a namespace.

We recently added support for importing data source-managed rules through the alerting UI. However, users couldn’t import their existing Prometheus rules when no ruler was available.
We’ve updated the main navigation in Grafana Cloud to bring all observability tools together under a single menu called Observability. You’ll now find App Observability, Frontend Observability, Kubernetes Monitoring, Infrastructure Monitoring, Cloud Provider Observability, and more grouped in one place.
We’re excited to introduce SLO Reports—a powerful new feature in Grafana SLO that enables users to report on multiple service level objectives (SLOs) on a weekly or monthly basis.
Kubernetes Monitoring offers CPU tabs with insightful panels on every detail page beyond the container page to provide you with quicker troubleshooting and better resource planning. You can gain deeper visibility from cluster to pod with utilization efficiency graphs and CPU distribution analysis.

You can now restrict Private Load Zones (PLZs) in Grafana Cloud k6 to be used by a limited set of projects.
This feature lets you assign projects to a PLZ so that only tests inside of that project can be run on a specific PLZ.

You now have more flexibility to tailor Grafana IRM to your team’s specific incident response workflows with several new customization options:
- Custom incident statuses: Define additional phases, such as Investigating or Monitoring, to go beyond the default Active and Resolved statuses. Custom statuses help responders communicate progress more clearly and give stakeholders better visibility into the state of an incident.
- Custom metadata fields: Capture the information that matters most to your organization. Add custom fields, such as impacted services or involved teams, and even make them required to ensure consistent data collection across incidents.
- Private incidents: Limit visibility for sensitive incidents by declaring them privately. Private incidents automatically create a restricted Slack or Microsoft Teams channel and give you control over who has access throughout the incident.
To learn more, refer to the documentation on incident settings and private incidents.
Dynamic Alerting with our Forecasting and Outlier Detection features has been supporting role-based access control in Public Preview for the last months. We’re excited to announce that this feature is now generally available. This introduces the roles ML Editor, ML Viewer, Sift Editor and Sift Viewer to better manage access to our Dynamic Alerting features.




