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  5. Managing Your Instances using the AWS Systems Manager Run Command, Documents, & Parameter Store

Summary

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Overview
Difficulty
Beginner
Duration
16m
Students
17
Ratings
5/5
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Description

AWS Systems Manager helps you automatically implement complex workflows related to your machine deployment, configuration, and life cycle. In this course, you will learn about AWS Systems Manager and how it allows you to manage your machine fleet at scale in AWS, your own data center, or even other cloud platforms.

Learning Objectives

  • Understand the fundamentals of AWS Systems Manager operations
  • Learn how to the use the run command and parameter store in Systems Manager
  • Learn how to schedule tasks through maintenance windows

Intended Audience

This course is intended for architects, developers, and system operators looking for a unified, scalable and secure way to automate their machine maintenance workflows for multiple operating systems and for Amazon EC2 instances.

Prerequisites

To get the most out of this course, you should meet the requirements for the AWS Cloud Practitioner certification and preferably one of the AWS associate-level certifications.

Transcript

In this course, we discussed what Systems Manager can do in terms of features and capabilities including basic instance setup. We discussed The idea of system manager documents as a resource to define multiple steps of action. We also discussed the Systems Manager Run command and the importance of maintenance windows. 

For Cloud Academy, this is Jorge Negrón, Thanks for watching!

About the Author
Avatar
Jorge Negrón
AWS Content Architect
Students
414
Courses
4

Experienced in architecture and delivery of cloud-based solutions, the development, and delivery of technical training, defining requirements, use cases, and validating architectures for results. Excellent leadership, communication, and presentation skills with attention to details. Hands-on administration/development experience with the ability to mentor and train current & emerging technologies, (Cloud, ML, IoT, Microservices, Big Data & Analytics).