Monitoring K8s with the Kubernetes Dashboard, Prometheus, and Grafana

Lab Steps

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Logging in to the Amazon Web Services Console
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Connecting to the CloudAcademy Web based IDE
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Deploy a Simple API Application
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Install and Configure K8s Dashboard
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Install and Configure Prometheus
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Install and Configure Grafana

The hands-on lab is part of these learning paths

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DifficultyIntermediate
Time Limit2h 30m
Students669
Ratings
4.7/5
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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)

About the Author
Students125482
Labs66
Courses113
Learning paths180

Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).