![]() It also maintains a record of cluster state in an etcd key-value store. The Control Plane, which we’ll cover in more detail below, provides centralized APIs and internal services for cluster management. Key Kubernetes objectsĪ Kubernetes cluster is made up of two primary node types: worker nodes, which run your containerized workloads, and one or more Control Plane nodes. This article references metric categories and terminology from our Monitoring 101 series, which provides a framework for metric collection and alerting. We’ll also touch on the value of collecting Kubernetes events. Work metrics from the Kubernetes Control Plane.Resource metrics from Kubernetes nodes and pods. ![]() The metrics we’ll cover in this post fall into three broad categories: In this part of the series, we’ll dig into the data you can collect from these APIs to monitor the Kubernetes platform itself. ![]() So even though individual containers and pods may come and go, you can use these abstractions to aggregate your data and monitor the performance of your workloads.Īdditionally, Kubernetes provides a wealth of APIs for automation and cluster management, including robust APIs for collecting performance data. The good news is that Kubernetes is built around objects such as Deployments and DaemonSets, which provide long-lived abstractions on top of dynamic container workloads. As explained in Part 1 of this series, monitoring a Kubernetes environment requires a different approach than monitoring VM-based workloads or even unorchestrated containers. ![]()
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