AWS EC2 Automation

7 min readOct 2, 2023

TABLE OF CONTENTS

EC2
Launch Templates in EC2
Instance Types
General Purpose
Compute Optimised
Memory Optimised
Storage Optimised
GPU Instances
FPGA Instances
Instance Sizes
AMI
Tasks: Create a launch template with Ubuntu AMI and t2.micro instance type with Jenkins and Docker setup (You can use the Day 39 User data script for installing the required tools).

In the previous blog, we learned about User Data and IAM. Let’s learn how to automate EC2 using Launch Templates and Auto Scaling Groups.

EC2

EC2 stands for Elastic Compute Cloud. It is a web service provided by Amazon Web Services (AWS).

EC2 provides scalable computing capacity, allowing users to quickly provision and configure virtual machines called instances.

With EC2, users can choose the type of instance they need, such as the amount of CPU, memory, storage, and networking capacity. Instances can be launched from pre-configured Amazon Machine Images (AMIs) that contain various operating systems and software configurations, or users can create their own custom AMIs.

EC2 provides a flexible and scalable infrastructure for running applications in the cloud, allowing users to pay only for the resources they consume and easily scale their computing capacity up or down as needed.

The below image depicts the lifecycle of an Instance:

Instances can be launched using the launch instance wizard or using a launch template.

Launch Templates in EC2

A launch template is a feature provided by Amazon EC2 that allows you to create reusable configurations for launching instances.

You can create a launch template that contains the configuration information to launch an instance. You can use launch templates to store launch parameters so that you do not have to specify them every time you launch an instance.

Launch templates support versioning, which means you can create multiple versions of a template to track changes over time. If you do not specify a version, the default version is used. You can set any version of the launch template as the default version — by default, it’s the first version of the launch template.

Instance Types

When you launch an instance, the instance type that you specify determines the hardware of the host computer used for your instance.

Instance types are named based on their family, generation, additional capabilities, and size.

The first position of the instance type name indicates the instance family, for example c.
The second position indicates the instance generation, for example 5.
The remaining letters before the period indicate additional capabilities, such as instance store volumes.
After the period (.) is the instance size, which is either a number followed by size, such as 9xlarge, or metal for bare metal instances.

The different types of Instances provided by AWS are:

General Purpose

These instances provide a balance of CPU, memory, and network resources. They are suitable for a wide range of workloads, including web servers, small databases, development environments, and other applications that require a balance of compute power and memory.

Examples: t3, m5

Compute Optimised

These instances are designed for compute-intensive workloads that require high CPU performance. They offer a high ratio of vCPUs to memory and are ideal for applications like scientific modeling, batch processing, gaming servers, and highly scalable front-end fleets.

Examples: c5

Memory Optimised

Memory-optimized instances are designed for memory-intensive workloads such as in-memory databases, real-time analytics, and high-performance computing. They offer a large amount of RAM relative to CPU resources, allowing efficient processing of data-intensive applications.

Examples: r5

Storage Optimised

Storage-optimized instances are designed for workloads that require high storage capacity and high sequential read/write performance. They are suitable for big data processing, data warehousing, and other applications that require fast and large-scale data access.

Examples: i3, d2.

GPU Instances

GPU instances are equipped with powerful graphics processing units (GPUs) that accelerate applications requiring parallel processing and high-performance computing. They are used for machine learning, deep learning, video rendering, and other GPU-intensive workloads.

Examples: p3, g4.

FPGA Instances

FPGA (Field Programmable Gate Array) instances are specialized instances that provide programmable hardware acceleration. They are suitable for applications that require custom hardware acceleration and can be programmed to perform specific tasks efficiently.

Examples: f1

Instance Sizes

AMI

AMI stands for Amazon Machine Image. It is a pre-configured template that contains the necessary information to launch an instance in Amazon EC2. An AMI serves as the building block for creating virtual servers in the cloud.

AMIs are available as Amazon-provided AMIs, AWS Marketplace AMIs, and Custom AMIs.

An AMI includes Root Volume, Instance Configuration, Permissions, Block Device Mappings, and Launch Permissions.

Tasks: Create a launch template with Ubuntu AMI and t2.micro instance type with Jenkins and Docker setup (You can use the Day 39 User data script for installing the required tools).

Select Launch Templates on the left side of your screen under Instances.

Click on Create Launch Template.

Application and OS Images (Amazon Machine Image): Ubuntu

Instance Type: t2.micro

Advanced Details: Use the following script-

#!/bin/bash
sudo apt-get update -y
sudo apt install openjdk-11-jre -y
curl -fsSL https://pkg.jenkins.io/debian-stable/jenkins.io-2023.key | sudo tee \
  /usr/share/keyrings/jenkins-keyring.asc > /dev/null
echo deb [signed-by=/usr/share/keyrings/jenkins-keyring.asc] \
  https://pkg.jenkins.io/debian-stable binary/ | sudo tee \
  /etc/apt/sources.list.d/jenkins.list > /dev/null
sudo apt-get update
sudo apt-get install jenkins -y
sudo systemctl enable jenkins
sudo systemctl start jenkins
sudo apt-get update
sudo apt-get install docker.io -y
sudo systemctl start docker

Click on Create Launch Template.

In the Launch Templates Dashboard, select the template you created and click on Actions. Select Launch Instance from the template.

Since we need 3 instances from the template we created, In Summary > Number of Instances > Type 3.

Select the KeyPair and click on Launch Instances.

We can see that 3 instances are running.

Let’s create ASG(Auto Scaling Group) and make the process more automated depending on the usage.

On the left side of your screen, you can find Auto Scaling Groups.

Click on Create Auto Scaling Group.

Step 1: Choose the launch template or configuration

Auto Scaling group name: JenDockScaling
Launch template: DockerJenkinsTemplate
Version: 2

Click Next.

Step 2: Choose instance launch options

Select the availability zones and click on Next.

Step 3: Configure advanced options

Load balancing: Attach to a new load balancer

Attach to a new load balancer:

Load balancer type: Application Load Balancer

Load balancer name: JenDockScaling-1

Load balancer scheme: Internal

Let the other options be the default, and click on Next.

Step 4: Configure group size and scaling policies

Desired capacity: 3

Minimum capacity: 1

Maximum capacity: 5

Click on Next.

Step 5: Add notifications

Step 6: Add Tags

Click on Next.

Once you reach the Review section, click on Create AutoScaling Groups.

click on Create AutoScaling Group.

When the utilization increases or decreases, the instances are scaled up or down automatically, based on the criteria you have given.

In this blog, I have discussed how to automate EC2 instance creation using Launch Templates and Auto Scaling Groups. If you have any questions or would like to share your experiences, please leave a comment below. Don’t forget to read my blogs and connect with me on LinkedIn and let’s have a conversation.

To help me improve my blog and correct my mistakes, I am available on LinkedIn as Mudit Mathur. Do reach me and I am open to suggestions and corrections.

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