Duration
21 hours (usually 3 days including breaks)
Requirements
- An understanding of Docker and Kubernetes basics.
- Experience with the Linux command line.
- An Amazon AWS account with at least 10 USD on it.
Audience
- Developers
- System Administrators
- DevOps Engineers
Overview
There are a number of options for deploying Docker and Kubernetes on AWS, including Amazon Elastic Container Service, Amazon ECS for Kubernetes, AWS Fargate, and Amazon EC2.
This instructor-led, live training (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decision about which to deploy within their organization.
By the end of this training, participants will be able to:
- Set up a development environment that includes all needed tools to start developing.
- Set up, configure and deploy a series of demo containers using a number of different approaches.
- Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
- Automate the deployment of Docker containers.
- Set up a continuous integration and deployment pipeline.
- Integrate Docker and Kubernetes into an existing continuous integration system.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
Overview of Docker and Kubernetes on AWS
Preparing the Development Environment
Using Amazon Elastic Container Service
- Creating a Containerized Application
- Deploying the Application
Using Amazon ECS for Kubernetes
- Creating a Containerized Application
- Deploying the Application
AWS Fargate
- Creating a Containerized Application
- Deploying the Application
Amazon EC2
- Creating a Containerized Application
- Deploying the Application
Setting up a Continuous Integration Pipeline
Integrating Docker and Kubernetes with an existing Continuous Integration System
Troubleshooting
Summary and Conclusion