Ready for the real environment experience?
Istio is an open source, multi-cloud service mesh, capable of performing intelligent traffic management. Istio's traffic routing rules let you easily control the flow of traffic and API calls to and from deployed cluster resources.
In this Lab scenario, you'll learn how to use Istio to perform traffic routing to a pair of sample web applications, V1 and V2, deployed into a Kubernetes cluster. You'll first setup a traffic routing policy to balance traffic evenly (50/50) across both versions. You'll test and confirm that the traffic is indeed evenly split before later updating the traffic routing policy to use a 80/20 split.
Upon completion of this Lab, you will be able to:
- Use Istio to perform traffic routing across a pair of versioned sample web applications
- Configure and deploy the following Istio custom resources:
- DestinationRule - the baseline deployment version of the webapp
- Gateway - uses a Kustomize overlay to change the baseline deployment settings
- VirtualService - uses a Kustomize overlay to change the baseline deployment settings
- Test, report, and validate the Istio service mesh based traffic routing using the curl command and your workstations browser
- Be comfortable with basic Linux command line administration
- Be comfortable with 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 and running 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 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).