Monitoring K8s with the Kubernetes Dashboard, Prometheus, and Grafana
Description
When it comes to running production-grade Kubernetes clusters, monitoring and alerting are considered essential components of an enterprise Kubernetes observability stack.
In this hands-on lab, you'll learn how to set up and use the following essential monitoring applications:
You'll learn how to integrate these monitoring applications together into an effective and cohesive monitoring solution.
Learning Objectives
Upon completion of this Lab, you will be able to:
- Deploy and instrument a sample Python Flask web-based API into Kubernetes, instrumented to provide metrics which will be collected by Prometheus and displayed within Grafana
- Install and configure the Kubernetes Dashboard using Helm
- Install and configure Prometheus into Kubernetes using Helm
- Setup Prometheus for service discovery
- Install and configure Grafana into Kubernetes using Helm
- Import a pre-built dashboard for real-time visualisations
Intended Audience
This lab is intended for:
- Kubernetes practitioners
- DevOps Engineers
- SREs
Lab Prerequisites
You should be familiar with:
- Basic Linux command line administration
- Basic Kubernetes and Container-based concepts
Lab Environment
This Lab will start with the following AWS resources provisioned automatically for you:
- 2 x EC2 instances - each assigned a public IP address:
- ide.cloudacademy.platform.instance - provides a web-based IDE with integrated terminal
- k8s.cloudacademy.platform.instance - provides a fully functional Kubernetes cluster
To achieve the Lab end state, you will be walked through the process of:
- Using your local workstation browser to remotely connect to the ide.cloudacademy.platform.instance
- Using the web-based IDE and integrated terminal, you'll complete the remainder of the stated Lab Objectives (above)
Updates
October 28th, 2024 - Resolved an issue preventing the lab from provisioning successfully
June 14th, 2024 - Resolved deployment issue