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Udoh Deborah
Udoh Deborah

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Day 40: AWS EC2 Automation

#ec2 #aws #devops #linux

Key Concepts

  1. Launch Template
    • A launch template stores the settings required to launch an EC2 instance (AMI, instance type, key pair, security groups, networking, storage, user data, etc.).
    • Benefit → saves time because you don’t need to re-enter these parameters each time you create an instance.

  2. Instance Types
    • EC2 instances come in families (General Purpose, Compute Optimized, Memory Optimized, etc.) with various sizes.
    • Example: t2.micro = free tier eligible (1 vCPU, 1 GiB RAM), suitable for small workloads like Jenkins & Docker labs.

  3. Amazon Machine Image (AMI)
    • A pre-configured OS + software package used to launch EC2 instances.
    • Example: Amazon Linux 2 AMI → lightweight, secure, and maintained by AWS.

🛠️ Task 1 – Hands-On Steps

Step 1: Create a Launch Template
1. Go to AWS Console → EC2 → Launch Templates → Create launch template.
2. Provide:
• Name: jenkins-docker-template
• AMI: Amazon Linux 2
• Instance Type: t2.micro
• Key Pair: Select your existing key (or create one).
• Security Group: Allow SSH (22), HTTP (80), and Jenkins (8080).
• User Data (script): paste the script from Day 39 that installs Jenkins + Docker automatically.

User Data runs at launch, so your instance is ready with Jenkins & Docker pre-installed.

Step 2: Launch Instances from Template
1. Select your launch template → Actions → Launch instance from template.
2. Choose number of instances.
• You’ll see an option: Number of instances (set this to 3).
3. Review & Launch.
• AWS will create 3 identical instances (AMI + t2.micro + Jenkins + Docker setup).

Step 3: (Optional) Create an Auto Scaling Group (ASG)
1. Go to EC2 → Auto Scaling Groups → Create Auto Scaling group.
2. Select the launch template you just created.
3. Configure:
• VPC & subnets (choose default if unsure).
• Desired capacity: 3 (to start with 3 instances).
• Scaling policies: Add scale out (if CPU > 70%) and scale in (if CPU < 20%).
4. Attach a load balancer (optional, but recommended for production).

Now, AWS automatically manages the number of instances based on load

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