Kubernetes Health Monitoring

Monitor key Kubernetes health metrics

Track relevant Kubernetes data in one place.

Evaluate cluster metrics to understand count, health, and the availability of Kubernetes objects inside your cluster
Detect and troubleshoot application issues using resource usage metrics like memory, CPU, as well as disk usage inside your Kubernetes nodes and pods
Monitor Kubernetes resources and services such as the API server, controller managers, and schedulers with control plane metrics

Enable scalable Kubernetes monitoring

Evaluate Kubernetes health in context.

Streamline the collection of application and performance data from Kubernetes nodes with the Datadog Cluster Agent
Scale your Kubernetes deployment using cluster metrics or leverage metrics from cloud services to autoscale databases, caches, or load balancers
Ensure deployments are functioning correctly by correlating and monitoring Kubernetes metrics, traces, and logs side by side and in real time

Overcome Kubernetes health monitoring challenges

Make sense of Kubernetes health monitoring complexity.

Manage and filter thousands of Kubernetes metrics across varied platforms and services by importing labels and tags into Datadog
Identify and monitor dynamic pods and nodes as they are being created, modified, moved, or deleted with autodiscovery
Monitor Metrics Server app metrics and kube-state metrics to assess platform health when kubernetes components are modified alongside applications