In the previous blog post in this two-part series, we discussed the critical signals you need to monitor in your Kubernetes environment to ensure optimal resource provisioning. These signals include high CPU and memory utilization, frequent pod evictions, slow application performance, and other indicators that your resources are over- or under-provisioned. Monitoring these signals is essential for maintaining an efficient, cost-effective, and environmentally sustainable Kubernetes environment.

Organizations that run Kubernetes clusters in cloud native environments should do so in a way that’s both operationally efficient and cost effective. However, many organizations don’t prioritize cost optimization until it becomes a pressing need. This may be due to a directive from senior leadership, a significant scale-up or migration of Kubernetes clusters, or an unexpected surge in the cloud bill.

With the release of the Data Explorer, users can now dig into the data behind any tile and slice, dice and explore as needed. This is perfect for those ad-hoc ‘scratchpad’ style scenarios where you want to get some answers without creating yet another dashboard. A couple of weeks ago, we released an awesome new feature that we haven’t had a chance to showcase yet. It’s called The Data Explorer, and I think it’s pretty cool. Let’s dive in!

Whether they’re for synthetic monitoring, large-language models, or some other use case, Grafana application plugins are a fantastic way to enhance your overall Grafana experience. Data for these custom experiences can come from a variety of sources, including nested data sources. However, they can also come from third-party APIs, which usually require authentication to access.

In this blog, I’d like to announce a new feature that brings an extra touch of personalization to your SquaredUp experience: Workspace Icons.

Grafana Geomap panels visualize geographical data on a map, making it easier to see spatial relationships and patterns. They are useful for monitoring metrics across different locations, such as server performance or application usage in various regions. The panels help identify regional issues quickly, allowing for faster troubleshooting and response times.