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Cloud Computing & DevOps

Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS)

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  • 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. Online 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.

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