An introductory course to deploy workloads on multiple cloud providers leveraging Kubernetes as a common platform. The course walks participants through the concepts of containerization and commonly accepted Kubernetes practices. Participants will author a Dockerfile to package a sample application into a docker image, to compose a Kubernetes pod and to deploy to multiple Kubernetes-as-a-Service providers. Hands-on labs will focus on similarities and differences between leading public cloud Kubernetes providers, best practices, and common setbacks. The course will also introduce configuration, security, back-end, logging, and monitoring utilizing Kubernetes and/or cloud-native services.
- Software architects evaluating the strategies for Kubernetes workloads on multiple clouds
- Software developers writing code that needs to run in containers in a cloud-native manner
- DevOps engineers that will be implementing deployment and operation automation
- Kubernetes architecture, workloads and deployment
- Review the common design patterns of Kubernetes
- Compare Kubernetes-as-a-Service to self-managed Kubernetes
- Highlight the best design practices: 12 factor app & micro-services
- Deploy and configure pods, deployments, and services on multiple providers
- Review monitoring options available
- Analyze containerized application and Kubernetes logs
- Discuss stateful workloads constrains and deployment methods
- Review common security concerns
- Previous experience with GCP, Aws, and Azure
- Familiarity with Micro-services concepts
- Recent hands-on experience with terminal/command line
- Familiarity with data persistence
- Access to a personal AWS, Azure and GCP accounts for full control purposes