Hands-on AWS Auto Scaling Labs: Essential Lab Exercises

Hands-on AWS Auto Scaling Labs: Essential Lab Exercises

Instructors: Pearson

Access provided by Xavier School of Management, XLRI

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Create a Launch Template and set up Auto Scaling Groups to manage compute resources dynamically; practice core configuration steps.
Configure Target Tracking, Simple, Step, and Predictive Scaling policies for efficient and optimized resource management.
Integrate Spot Instances into Auto Scaling Groups to achieve and demonstrate cost-effective scaling strategies.
Create Target Groups and Load Balancers; set up Network Load Balancer integration to enhance availability and scalability.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

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Assessments

5 assignments

Taught in English

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There is 1 module in this course

This course enables learners to master AWS Auto Scaling through immersive hands-on labs, allowing them to dynamically adjust compute resources, optimize application performance, and excel in creating scalable, resilient cloud solutions. It is designed for cloud professionals seeking to develop their AWS Auto Scaling skills, and is essential for those aiming to optimize application performance, availability, and cost-effectiveness in cloud environments. AWS Auto Scaling facilitates the automatic adjustment of compute resources based on demand, ensuring applications efficiently handle varying workloads. A solid understanding of Auto Scaling is also crucial for designing resilient and dynamically scalable architectures.

This module provides a comprehensive introduction to AWS Auto Scaling. Learners will explore core concepts, configure scaling policies, integrate auto scaling groups with load balancers, and monitor and update groups using CloudWatch and CloudTrail. Hands-on labs guide students through creating launch templates, implementing various scaling strategies, ensuring high availability, and updating auto scaling configurations for robust cloud applications.