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Auto Scaling and Load Balancing in AWS Cloud

Auto Scaling and Load Balancing in AWS Cloud

Siddhant Bhattarai's photo
Siddhant Bhattarai
·

6 min read

Introduction:

Welcome to the latest version of our comprehensive guide on scaling and load balancing your architecture using Amazon Web Services (AWS). In this lab, we'll delve into the powerful combination of Elastic Load Balancing (ELB) and Auto Scaling services, equipping you with the knowledge to seamlessly distribute traffic and dynamically scale your infrastructure based on your application's needs.

Understanding Elastic Load Balancing (ELB):

Elastic Load Balancing, a key component of AWS, automates the distribution of incoming application traffic across multiple Amazon EC2 instances. By doing so, it ensures fault tolerance, providing the necessary load balancing capacity to efficiently route application traffic. This feature contributes significantly to enhancing the reliability and availability of your applications.

Exploring Auto Scaling:

Auto Scaling is your ally in maintaining application availability while offering the flexibility to automatically scale your Amazon EC2 capacity based on predefined conditions. Whether you need to scale out or in, Auto Scaling empowers you to manage your desired number of Amazon EC2 instances effortlessly. It can dynamically adjust the number of instances to meet demand spikes, optimizing performance, and reduce capacity during lulls to control costs effectively. Auto Scaling proves particularly valuable for applications with stable demand patterns or those experiencing hourly, daily, or weekly usage variations.

Lab Objectives:

Upon completing this lab, you will gain proficiency in the following key objectives:

  • Create an Amazon Machine Image (AMI) from a running instance.

  • Create a load balancer.

  • Create a launch configuration and an Auto Scaling group.

  • Automatically scale new instances within a private subnet

  • Create Amazon CloudWatch alarms and monitor performance of your infrastructure.

Scenario

You start with the following infrastructure:

The final state of the infrastructure is:

Task 1: Create an AMI for Auto Scaling

Objective: Prepare an Amazon Machine Image (AMI) to replicate Web Server 1's configuration for use in future Auto Scaling.

  1. Access EC2 in AWS Console: Go to the AWS Management Console, search for EC2 in the Services search box, and navigate to it.

  2. Select Instances: From the left navigation pane, click on "Instances" to see all running instances.

  3. Check Web Server 1 Status: Ensure "Web Server 1" passes all checks (2/2 checks passed). Use "Refresh" if necessary.

  4. Initiate AMI Creation: Click on "Web Server 1," go to the "Actions" menu, navigate to "Image and templates," and select "Create image."

  5. Configure AMI: Fill in the details:

    • Name: WebServerAMI

    • Description: Lab AMI for Web Server

    • Hit "Create image."

  6. Note AMI ID: After creation, a confirmation will show your AMI ID, which you'll use for Auto Scaling.

Task 2: Setting Up a Load Balancer

Objective: Distribute incoming traffic across multiple EC2 instances using a load balancer.

  1. Navigate to Target Groups: From the left pane, select "Target Groups" and click "Create target group."

  2. Create Target Group: Set up with the following:

    • Type: Instances

    • Name: LabGroup

    • VPC: Choose Lab VPC from the dropdown.

    • Proceed without adding instances by clicking "Next."

  3. Configure Load Balancer: Go to "Load Balancers" in the left pane, click "Create," select "Application Load Balancer," and fill in:

    • Name: LabELB

    • VPC: Lab VPC

    • Availability Zones: Choose both Public Subnets.

    • Security Groups: Select "Web Security Group," removing the default.

    • Listener HTTP:80: Set to forward to "LabGroup."

    • Finalize by clicking "Create load balancer."

Task 3: Auto Scaling Setup

Objective: Establish a launch template for Auto Scaling, followed by creating the Auto Scaling group.

  1. Launch Template Creation: In the left pane, select "Launch Templates," click "Create," and input:

    • Name: LabConfig

    • AMI: Select "Web Server AMI"

    • Instance type: t2.micro (or t3.micro based on the region)

    • Key pair: vockey

    • Security groups: "Web Security Group"

    • Enable "Detailed CloudWatch monitoring"

    • Click "Create launch template."

  2. Auto Scaling Group: With "LabConfig" selected, navigate to "Create Auto Scaling group":

    • Name: Lab Auto Scaling Group

    • VPC: Lab VPC

    • Subnets: Choose both Private Subnets.

    • Attach to existing load balancer: Select "LabGroup"

    • Set group size: Desired=2, Min=2, Max=6

    • Scaling policy: Target tracking, Metric=Average CPU Utilization, Target=60%

    • Skip optional steps, review, and create the group.

Task 4: Verify Load Balancing

Objective: Confirm the load balancer efficiently directs traffic.

  1. Check Instances: In "Instances" within the EC2 dashboard, look for two "Lab Instance" entries, indicating Auto Scaling launch.

  2. Health Checks: Go to "Target Groups," select "LabGroup," and verify both instances are healthy under the "Targets" tab.

  3. Load Balancer Test: Find your load balancer in "Load Balancers," note its DNS name, and visit that address in a browser to confirm operation.

Task 5: Testing Auto Scaling

Objective: Ensure the Auto Scaling group correctly manages instance counts under load.

  1. Monitor Alarms: In CloudWatch (via Services search), check "All alarms" for two related to your Auto Scaling group's CPU load.

  2. Adjust Scaling Policy: If alarms aren't visible, edit "LabScalingPolicy" in the "Auto Scaling Groups" section to a Target Value of 60.

  3. Observe Scaling: Return to CloudWatch to monitor alarm changes and confirm that additional instances launch as needed based on load.

Task 6: Terminate Web Server 1

In this task, you will terminate Web Server 1. This instance was used to create the AMI used by your Auto Scaling group, but it is no longer needed.

  1. Select Web Server 1 (and ensure it is the only instance selected).

  2. In the Instance state menu, choose Instance State > Terminate Instance.

  3. Choose Terminate

Summary

The provided guide outlines a comprehensive approach to scaling and balancing a web architecture within AWS, aimed at beginners. The process is divided into five distinct tasks, each designed to progressively establish a robust and scalable web environment. Here's a summary of the tasks involved:

  1. Create an AMI for Auto Scaling: This initial step involves creating an Amazon Machine Image (AMI) from an existing web server instance. The AMI serves as a template to replicate the server's configuration across new instances, ensuring consistency in the auto-scaling process.

  2. Set Up a Load Balancer: Following the creation of the AMI, the next task is to set up a load balancer. The load balancer's role is to distribute incoming web traffic evenly across multiple EC2 instances, enhancing the application's availability and reliability. This involves configuring target groups and setting up an Application Load Balancer with specific network and security settings.

  3. Auto Scaling Setup: With the load balancer in place, the guide transitions to setting up auto-scaling, which allows the application to adjust its computational resources automatically based on traffic demands. This is achieved by creating a launch template that specifies the configuration of instances to be launched, including the AMI, instance type, and security settings, followed by the creation of an Auto Scaling group that utilizes this template.

  4. Verify Load Balancing: Once the load balancer and Auto Scaling group are configured, the guide suggests verifying the load balancing functionality. This step ensures that the load balancer correctly distributes traffic to the instances launched by the Auto Scaling group, and that these instances are registered and healthy.

  5. Test Auto Scaling: The final task involves testing the Auto Scaling group's responsiveness to changes in load. This is done by monitoring CPU utilization and adjusting scaling policies as necessary to trigger the launch or termination of instances, ensuring the application maintains optimal performance under varying loads.

The guide meticulously details each step in the setup process, from the creation of an AMI to the testing of auto-scaling functionality, providing a clear path for beginners to follow in establishing a scalable and balanced AWS web architecture.

autoscalingLoad Balanceraws ec2