Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS)

Overview

Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. In this three-day course, you’ll learn container management and orchestration for Kubernetes using Amazon EKS. You’ll build an Amazon EKS cluster, configure the environment, deploy the cluster, and add applications to your cluster. Also discover how to manage container images using Amazon Elastic Container Registry (ECR) and learn how to automate application deployment. In addition, you’ll deploy applications using CI/CD tools. You’ll review how to monitor and scale your environment by using metrics, logging, tracing, and horizontal/vertical scaling. Learn efficiency, cost, and resiliency by designing and managing a large container environment. Lastly, explore configuring AWS networking services to support the cluster and learn how to secure your Amazon EKS environment.

Who Should Take This Course

AUDIENCE

Anyone who will provide container orchestration management in the AWS Cloud, including DevOps engineers and systems administrators.

PREREQUISITES

Completed Amazon Elastic Kubernetes Service (EKS) Primer
Completed AWS Cloud Practitioner Essentials (or equivalent real-world experience)
Basic Linux administration experience
Basic network administration experience
Basic knowledge of containers and microservices

Why You Should Take This Course

This course will prepare you to:

Review and examine containers, Kubernetes, and Amazon EKS fundamentals—and the impact of containers on workflows
Build an Amazon EKS cluster by selecting the correct compute resources to support worker nodes
Secure your environment with AWS Identity and Access Management (IAM) authentication by creating an Amazon EKS service role for your cluster
Deploy an application on the cluster, then publish container images to ECR and secure access via IAM policy

Schedule

Course Outline

Day 1

Module 0: Introduction
Module 1: Introduction to Machine Learning and the ML Pipeline
Module 2: Introduction to Amazon SageMaker
Module 3: Problem Formulation

Day 2

Module 3: Problem Formulation (continued)
Module 4: Preprocessing

Day 3

Module 5: Model Training
Module 6: Model Evaluation

Day 4

Module 7: Feature Engineering and Model Tuning
Module 8: Deployment

FAQs

Is there a discount available for current students?

UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.

What is the cancellation and refund policy?

Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.