Monitoring a Kubernetes Cluster: Troubleshooting Workloads
NEW! This course will present hands-on scenarios in which you will use Datadog to identify, fix, and monitor common Kubernetes workload issues.
Developing workloads for deployment to Kubernetes comes with unique challenges. These include managing resource requirements and allocations, ensuring node capabilities match workload demands, and maintaining the stability and performance of microservices and applications.
This course will present hands-on scenarios in which you will use Datadog to identify, fix, and monitor common Kubernetes workload issues.
In order to complete the course, you will need:
At the bottom of each lesson, click MARK LESSON COMPLETE AND CONTINUE button so that you are marked complete for each lesson and can receive the certificate at the end of the course.
Please note that your enrollment in this course ends after 30 days. You can re-enroll at any time and pick up where you left off.
Introduction
Tools
Strategy
About the lab
Lab: Troubleshooting Workloads
Summary
Feedback Survey