Lets have a look at the Step by Step process on how to Automate EC2 Autoscaling with Terraform for High Availability on AWS
Lets get started
Requirements:
AWS-CLI
Terraform
GitHub Account
IAM User with Access Key and Secret Key
A Key Pair In EC2 Console
Folder Structure:
Project Overview :
Using Terraform we are going to create AWS resources with High availability
If the EC2 instances CPU reaches 75% load, Cloud watch will trigger the EC2 Autoscaling.
Once AWS Autoscaling is triggered it will add one new instance in EC2.
If the 5-minute average load CPU is reduced to 50%, Auto scale deletes the one instance.
AWS Autoscaling Min instances = 2, Max=4, Desired=2
At a Specific time in the day, AWS Autoscaling refreshes the instance
Make sure you Have installed AWS CLI
Now Lets connect with AWS Console using aws configure
For this you need to generate Access key and Secrete key from IAM Console
Make sure you have installed terraform
You can use my repository for Terraform module files
GitHub - VenkatVk4622/AWS-Automate-EC2-Autoscaling-with-Terraform-for-High-Availability-on-AWS…
Automate EC2 Autoscaling with Terraform for High Availability on AWS …
github.com
So Once the above Terraform Modules is added in your Directory
Now lets get started with the Deployment:
Follow the below steps:
terraform init
terraform plan
terraform Apply
Now Terraform apply is successfull lets check our AWS Console
Here we can see we have successfully Deployed the autoscaling group
And we can also see the instance have been deployed
and this is our Launch Template used in Autoscaling group
Final Summary:
Automating EC2 Auto Scaling with Terraform for high availability on AWS offers a powerful, efficient, and reliable way to manage infrastructure.
Instead of manually creating and configuring instances, Terraform enables you to define your entire setup as code, making deployments consistent, repeatable, and version-controlled.
By using Auto Scaling Groups across multiple Availability Zones, your application becomes highly resilient to failures, automatically scaling up or down based on demand without manual intervention.
This approach not only reduces human error and operational overhead but also ensures that your architecture is always optimized for performance, cost, and reliability — the key pillars of a truly cloud-native environment.
Venkat C S
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