Oreilly – Hands-on AWS Auto Scaling Labs: Essential Lab Exercises 2024-6

Oreilly – Hands-on AWS Auto Scaling Labs: Essential Lab Exercises 2024-6 Downloadly IRSpace

Oreilly – Hands-on AWS Auto Scaling Labs: Essential Lab Exercises 2024-6
Oreilly – Hands-on AWS Auto Scaling Labs: Essential Lab Exercises 2024-6

This hands-on AWS Auto Scaling Labs: Essential Lab Exercises video course will help you improve your AWS Auto Scaling skills by going through in-depth hands-on exercises. Auto Scaling is a feature in the AWS cloud service that automatically adjusts computing resources based on demand. With this capability, your applications can effectively adapt to changing workloads. In this course, by learning Auto Scaling, you will gain the ability to design scalable and flexible infrastructure.

Hands-on Labs are an integral part of this course and provide hands-on experience in configuring, testing, and fine-tuning Auto Scaling policies. Detailed guides and training videos along with these exercises will accompany you on the path of learning and optimal implementation of Auto Scaling solutions in AWS. The course starts with basic concepts and guides you in creating a Launch Template and setting up an Auto Scaling Group. In the first exercise, you will learn the basic configuration steps for dynamic resource management. The second lesson expands your knowledge by examining different scaling policies such as Target Tracking, Simple Scaling, Step Scaling, and Predictive Scaling. The second and third exercises provide appropriate practical exercises based on different work needs. In the fourth exercise, you will learn cost optimization strategies by integrating Spot Instances into Auto Scaling groups.

What you’ll learn in the Hands-on AWS Auto Scaling Labs: Essential Lab Exercises course

  • Creating a Launch Template to configure Auto Scaling groups
  • Set up an Auto Scaling group for dynamic management of computing resources
  • Creating a simple Auto Scaling group to understand the basic configuration steps
  • Configure Target Tracking and Simple Scaling policies for efficient resource management
  • Implementing Simple Scaling policies to dynamically adjust resource capacity
  • Configure Step Scaling policies to manage incremental workloads
  • Configure Predictive Scaling to predict resource needs based on past data
  • Applying Step and Predictive Scaling policies to optimize resource allocation
  • Integrate Spot Instances into Auto Scaling groups for cost-effective scaling strategies
  • Create Target Groups and Load Balancers to improve application availability and scalability
  • Setting up Network Load Balancer integration with Auto Scaling groups

This course is suitable for people who:

  • Beginners and intermediates in the field of AWS
  • AWS Solutions Architects
  • AWS SysOps Administrators
  • Cloud professionals seeking AWS certifications such as AWS Certified Solutions Architect and AWS Certified SysOps Administrator.

Description of the Hands-on AWS Auto Scaling Labs: Essential Lab Exercises course

  • Publisher: Oreilly
  • Lecturer: Richard Crisci
  • Training level: beginner to advanced
  • Training duration: 2 hours and 14 minutes

Course headings

  • Introduction
  • Hands-on AWS Auto Scaling Labs: Introduction
  • Lesson 1: Create an Auto Scaling GroupLearning objectives
  • Learning objectives
  • 1.1 Create a Launch Template
  • 1.2 Create an Auto Scaling Group
  • 1.3 Hands-on Lab 1: Create a Simple Auto Scaling Group
  • Lesson 2: Configuring Scaling Policies
  • Learning objectives
  • 2.1 Configure Target Tracking and Simple Scaling
  • 2.2 Hands-on Lab 2: Configure Simple Scaling
  • 2.3 Configure Step Scaling
  • 2.4 Configure Predictive Scaling
  • 2.5 Hands-on Lab 3: Configure Step and Predictive Scaling
  • 2.6 Create an Auto Scaling Group with Spot Instances
  • 2.7 Hands-On Lab 4: Auto Scaling Group with Spot Instances
  • Lesson 3: Load Balancers and Auto Scaling
  • Learning objectives
  • 3.1 Create Target Group and Load Balancer
  • 3.2 Create Launch Template
  • 3.3 Create Auto Scaling Group
  • 3.4 Verify Load Balancer
  • 3.5 Hands-on Lab 5: Network Load Balancer and Auto Scaling
  • 3.6 Simulate an Instance Failure
  • Lesson 4: Monitoring and Updating Auto Scaling Groups
  • Learning objectives
  • 4.1 Monitor Auto Scaling Groups
  • 4.2 Hands-on Lab 6: Monitoring Auto Scaling Groups
  • 4.3 Update the Launch Template
  • 4.4 Perform an Instance Refresh
  • 4.5 Hands-on Lab 7: Updating Auto Scaling Groups
  • 4.6 Clean Up Your AWS Account to Avoid Charges
  • Summary
  • Hands-on AWS Auto Scaling Labs: Summary

Images of the course Hands-on AWS Auto Scaling Labs: Essential Lab Exercises

Creating a Launch Template to configure Auto Scaling groups Setting up an Auto Scaling group to dynamically manage computing resources Creating a simple Auto Scaling group to understand the main configuration steps Configuring Target Tracking and Simple Scaling policies to efficiently manage resources Implementing Simple Scaling policies to set Dynamic resource capacity, configuration of Step Scaling policies to manage incremental workload, configuration of Predictive Scaling to predict resource needs based on past data, application of Step and Predictive Scaling policies to optimize resource allocation, integration of Spot Instances into Auto Scaling groups Create Target Groups and Load Balancers for cost-effective scaling strategies to improve availability and scalability Launch Network Load Balancer integration with Auto Scaling groups

Sample video of the course

Installation guide

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