Operations | Monitoring | ITSM | DevOps | Cloud

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 of the latest and greatest Grafana Cloud updates.

Imagine setting up your AWS configuration in Grafana Cloud by hand and clicking through menus. When you only have a few services, it’s not a big deal. But as you add more and more, keeping track of every little change becomes a headache. It’s easy to make mistakes, and before you know it, things can get out of sync and your monitoring becomes unreliable.

Frederik Van Leeckwyck is the co-founder and CRO at Factry. He oversees go-to-market activities and ensures their software solutions align with real factory demands. Passionate about open technologies, he believes in making data-driven insights accessible to everyone in the factory. Factories today are often rich in process data, but poor in insights.

Here at Grafana Labs, our commitment to our “big tent” philosophy runs deep. We prioritize interoperability and flexibility within our observability solutions, and believe you should be able to connect to and visualize data from a wide range of sources, including both open source and commercial technologies. Our rich ecosystem of Grafana data sources directly reflects these values — and today, we’re excited to share a recent milestone related to that ecosystem.

What if you were to tell Kubernetes Monitoring what you wanted, and the system configured collectors based on your choices? We wondered that as well—wondered enough to create Alloy Operator and its Helm chart for version 3.0 of the Kubernetes Monitoring Helm chart. We’re excited to share that the new Kubernetes Monitoring Helm chart is now available, and it introduces a dynamic way of setting up your telemetry data collection with Alloy Operator.

In Grafana Cloud, we offer a range of AI capabilities to support your observability needs, including a feature for forecasting on any of your metrics and coupling it with Grafana Alerting. This is critical functionality if you want to make the switch from reactive to proactive alerting, as troubleshooting a problem before it arises is an important part of modern observability.

Japanese organizations are focused on controlling costs and limiting complexity—and they might be getting ready to broaden their adoption at just the right time, according to analysis of a micro survey on observability recently conducted by Grafana Labs. Observability is an evolving space in Japan, and this is the first time Grafana Labs has run a Japanese version of our annual Observability Survey.

Grafana Tempo 2.8 is officially here, delivering new TraceQL features, performance improvements, and bug fixes, as well as some breaking changes. Watch the video below to learn more about the TraceQL features, or continue reading to get a quick overview of these and other updates. If you’re looking for something more in-depth for all of the changes that happened in this release, head over to the Grafana Tempo 2.8 release notes or the changelog.

If you’re working with metrics in Grafana Cloud, chances are you’ve come across DPM (data points per minute). It shows up in usage dashboards, invoice breakdowns, and occasionally pops up in Slack when your ingestion numbers start looking suspicious. DPM can also be seen in the Grafana Cloud billing and usage dashboard, which is available by default in every Grafana Cloud account. It helps you understand how much data you’re sending—and whether it’s more than you need.

Grafana Play is a free and publicly accessible sandbox environment that allows users to explore and learn Grafana without setting up their own instance. Grafana Play comes preloaded with ready-made sample dashboards, and showcases how to work with different data sources, create visualizations, and use advanced Grafana features.