The hands-on lab is part of these learning paths
Ready for the real environment experience?
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.
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
This lab is intended for:
- Kubernetes practitioners
- DevOps Engineers
You should be familiar with:
- Basic Linux command line administration
- Basic Kubernetes and Container-based concepts
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)
Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.
Jeremy holds professional certifications for both the AWS and GCP cloud platforms.