Using AWS load balancer with Auto Scaling

Create an Auto Scaling group: First, you need to create an Auto Scaling group that will automatically launch and terminate EC2 instances based on demand. You can define the minimum and maximum number of instances in the group, as well as the desired capacity.

1. Create a launch configuration: Next, you need to create a launch configuration that defines the settings for an EC2 instance, such as the AMI, instance type, and security groups. When Auto Scaling launches new instances, it uses the launch configuration to create the instances.

2. Configure load balancer: You need to configure the load balancer to distribute traffic across the instances in your Auto Scaling group. AWS provides several types of load balancers, including the Application Load Balancer and Network Load Balancer.

3. Associate Auto Scaling group with load balancer: To ensure that traffic is distributed evenly across your instances, you need to associate your Auto Scaling group with the load balancer. This can be done using the AWS Management Console or the AWS CLI.

4. Configure Auto Scaling policies: You can configure Auto Scaling policies to automatically adjust the number of instances in your Auto Scaling group based on demand. There are several types of scaling policies available, including target tracking, simple scaling, and step scaling.

5. Test your configuration: Before deploying your configuration to production, it's a good idea to test your configuration in a staging environment. This will help you ensure that your load balancer is distributing traffic evenly across your instances and that your Auto Scaling policies are working as expected.

Overall, using AWS load balancer with Auto Scaling provides a flexible and scalable solution for managing your resources. By distributing traffic across your instances and automatically adjusting the number of instances based on demand, you can ensure that your application is highly available and responsive to user requests.

AWS Load Balancer Architecture

AWS Load Balancer is a highly available and scalable service that distributes incoming traffic to multiple targets (such as EC2 instances, containers, and IP addresses) across one or more Availability Zones (AZs) within a region.

This helps to improve the availability, scalability, and fault tolerance of your applications by ensuring that incoming traffic is evenly distributed and that healthy targets receive traffic.

Here's an example of AWS Load Balancer architecture using an Application Load Balancer (ALB):

Example

In this example, the web application consists of two microservices running on different EC2 instances within two Availability Zones.

The ALB is used to route incoming HTTP/HTTPS requests to the appropriate microservice based on the path of the request.

The architecture consists of the following components:

1. Clients: These are the users who access the web application via a web browser or a mobile app.
2. DNS: The domain name system (DNS) routes incoming requests to the appropriate load balancer based on the domain name.
3. Application Load Balancer: The ALB routes incoming requests to the appropriate microservice based on the path, host, query string, or headers of the request.
4. Target Group: A target group is a collection of targets (such as EC2 instances or containers) that receive traffic from the load balancer based on the configured routing rules.
5. EC2 Instances: The EC2 instances host the microservices that handle incoming requests from the ALB. These instances are registered with the target group and receive traffic based on the routing rules.
6. Availability Zone: An Availability Zone is an isolated location within a region that consists of one or more data centers. The targets are distributed across multiple Availability Zones to improve fault tolerance and scalability.
7. Auto Scaling Group: An Auto Scaling group is used to automatically scale the number of EC2 instances based on the demand to handle incoming traffic.

Overall, the AWS Load Balancer architecture helps to ensure that incoming traffic is evenly distributed across multiple targets, resulting in improved availability, scalability, and fault tolerance.