Grafana Labs has announced new enhancements to help address the challenges of Kubernetes monitoring and provided updates on its contributions to the open source ecosystem. These updates come in advance of KubeCon + CloudNativeCon Europe, the industry’s largest open source conference dedicated to Kubernetes, Prometheus, and other cloud-native technologies, taking place March 19-22 in Paris, France.

The company also released the findings from its second annual Observability Survey which provides insight into the evolving observability market. For example, despite open source technology continuing to be a critical piece of 98% of respondents’ observability stacks, it’s still not enough to offset concerns about cost, which is cited as their biggest concern when it comes to observability. The report underscores the critical role observability plays in modern IT landscapes, delving into the number and types of observability tools organizations are using; the challenges and benefits that come with centralized observability; and the impact of company size and industry on adoption and maturity.

“As Kubernetes becomes a de facto standard and organizations continue to mature in their observability strategy, integrating your infrastructure fleets with your observability platform becomes more powerful and necessary,“ said Tom Wilkie, Grafana Labs CTO and CNCF Governing Board member. “This is highlighted by the results of our 2024 Observability Survey, which shows the escalating importance of cost efficiency and the CNCF’s findings that Kubernetes adoption drove up costs for almost 50% of respondents. That’s why we’re focused on making it easy to get started with observability and Kubernetes monitoring with Grafana Cloud, including our generous forever free tier, to help customers understand the behavior of their infrastructure and improve resource utilization.”

Kubernetes Monitoring in Grafana Cloud makes it easier to monitor Kubernetes clusters by allowing users to visualize and analyze key metrics related to Kubernetes environments, track resource usage, and gain insights into the behavior of their applications within Kubernetes. New updates offer seamless setup and deployment, quick and easy issue management, fine-grained cost monitoring, and more:

• Deploy and scale easier: Users no longer have to use Grafana Agent or Grafana Agent Operator to manually configure infrastructure data. With the new Grafana Kubernetes Monitoring Helm chart, it’s easier to send metrics, logs, events, traces, and cost metrics to Grafana Cloud. Plus, you can customize the chart for your specific needs. In addition, IBM Cloud is now a configurable option as part of the out-of-the-box Helm chart.
• Respond to alerts quicker: You can now respond to and troubleshoot Kubernetes alerts without leaving the context of Grafana Kubernetes Monitoring. You can start your troubleshooting either through the “Pods in trouble” section on the home page or the Alerts page. The updated Alerts page provides a centralized location to view all alerts related to your Kubernetes infrastructure and the applications running within it. From here, you can see graphs showing alerts by cluster and namespace, as well as by alert severity, making it easier to filter and drill down into issues to resolve them more quickly.
• Get a 360° view of your infrastructure data: The Kubernetes monitoring interface now provides a comprehensive overview and detailed analysis of your cluster’s health and performance. The main page offers a snapshot of critical issues, displaying graphs for Clusters, Nodes, Pods, and containers, regardless of your cloud provider or Kubernetes distribution. In addition, the new time picker facilitates historical data analysis, allowing for the examination of resource usage over selected time frames, which is crucial for addressing inefficiencies and managing costs.
• Monitor, predict, and optimize resource usage: The New Summary views for Clusters, Nodes, Workloads and Namespaces now correlate CPU, memory, and storage usage, aiding in performance troubleshooting and identifying underutilized resources. Predictive features, enabled by the Machine Learning plugin, provide forecasts for CPU and memory usage to optimize resource allocation in every component insights view. Together, these features enable a robust approach to managing Kubernetes clusters, ensuring efficient resource use and cost-effectiveness.
• Keep on top of Kubernetes costs: Kubernetes Monitoring provides cost monitoring tools that allow you to correlate resource management to cost attribution. With the new Pod and Container detail pages, users can now see a breakdown of costs on a per-container or per-pod basis.
• Bring your own tools: Kubernetes Monitoring is now listed in the AWS marketplace as an EKS add-on. In addition, ClickHouse, InfluxDB and Presto integrations are now available to use with Kubernetes Monitoring and provide out-of-the-box dashboards, alerts and recording rules for an easy services observability start.