Courses
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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.
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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.
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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.
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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.
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Monitoring Workloads on Kubernetes
This course explores the distinctive aspects of monitoring workloads on Kubernetes, focusing in particular on the impact of workload scheduling.
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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.
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Managing Datadog monitors through Kubernetes configuration
In this lab, you use DatadogMonitor to define Datadog monitors as Kubernetes objects, allowing you to store them in Git with the rest of your application configuration.
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Tracking Canary Deployments with Datadog
In this lab, you use Datadog’s deployment tracking together with Docker to deploy, track, and remediate issues within staged releases.
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Introduction to Cluster Checks and Endpoint Checks
In this lab, you learn how to set up cluster checks and endpoint checks for Kubernetes services.
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