Kubernetes Monitoring Learning Path
Follow this curated path to build a foundation in monitoring Kubernetes with Datadog.
Through hands-on courses, you’ll learn to install and configure the Datadog Agent using Helm or the Datadog Operator, gather comprehensive visibility into your clusters, and troubleshoot real-world containerized workloads with confidence.
This path is designed for Engineers managing and monitoring Kubernetes environments in production.
You’ll learn how to do the following:
Introduction to Monitoring Kubernetes
In this course, you learn the basics about monitoring the Kubernetes platform with Datadog, including the importance of tagging your various workloads. You also look at the different metrics, logs, and APM traces that are specific to Kubernetes.
Monitoring a Kubernetes Cluster: Install the Agent
To monitor your Kubernetes cluster with Datadog, you must install the Datadog Agent. This course will walk you through the most common ways of installing Cluster and Node Agents on Kubernetes: the Helm chart and The Datadog Operator.
Monitoring a Kubernetes Cluster: The Control Plane
This course will walk you through monitoring each of a Kubernetes cluster's control plane components: API Server, Controller Manager, Scheduler, and etcd.
Monitoring a Kubernetes Cluster: Troubleshooting Workloads
This course will present hands-on scenarios in which you will use Datadog to identify, fix, and monitor common Kubernetes workload issues.
Progressive Delivery in Kubernetes
A good observability strategy is key to success with progressive delivery. In this course, you learn various observability strategies for implementing progressive delivery in Kubernetes and how these strategies can fit different organizations.
