Dashboards

We consistently roll out helpful updates and fun features in Grafana Cloud, our fully managed observability platform powered by the open source Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). In case you missed them, here’s our monthly round-up (the first of 2025!) of the latest and greatest Grafana Cloud updates. You can also read about all the features we add to Grafana Cloud in our What’s New in Grafana Cloud documentation.

The promise of observing your application without writing code (i.e., auto-instrumentation) is not new, and it’s extremely compelling: run a single command in your cluster and suddenly application telemetry starts arriving at your observability backend. What else could you ask for? The OpenTelemetry Operator aims to fulfill such a dream for Kubernetes environments by using a set of well known patterns such as operators and custom resources.

Grafana Tempo 2.7 is here, and while the latest release is primarily focused on performance and operational improvements, we managed to sneak in some new TraceQL features, too!

They might seem very similar at first sight, but when you zoom in on them, the differences are more apparent. Status Pages and Service Health Dashboards serve distinct purposes and cater to different audiences. As organizations adopt more complex systems, the tools used to communicate about service health and performance have become equally important. Let’s dive into the key differences, use cases, and how these tools complement each other.

It’s hard to believe Grafana Play has been around for almost a decade. The platform continues to be a great way to demo Grafana, play around with new features, learn what’s possible, and simply have fun with data. Grafana Play provides a publicly available version of Grafana Cloud, and requires no login for access. It’s preloaded with a wide range of sample dashboards that teach users how to work with data sources, create visualizations, and explore advanced Grafana features.

As your applications scale, so too does the flood of logs, metrics, profiles, and traces—along with the costs to store and manage them. Collecting everything might feel like the safest bet, but it often leaves you buried in noise and struggling to find the signals that matter, all while costs spiral out of control.

Service-level objectives (SLOs) can be a great way to ensure you’re hitting your goals, but many software teams struggle to set realistic targets when they first set up the service-level indicators (SLIs) that underpin those efforts. Sometimes management has a decree that all services will operate with “three 9s” of availability; other times engineers pick a number out of thin air.

Instead of sifting through mountains of metrics across different network types, what if you had an AI-powered tool that could display all the necessary insights in an easy-to-understand format?