📌 Amazon EC2 (Elastic Compute Cloud) – Virtual servers in the cloud
📌 EC2 Pricing Models (On-Demand, Reserved, Spot)
📌 Elastic Load Balancer (ELB) & Auto Scaling
📌 AWS Lambda (Serverless Compute) – Event-driven execution
📌 Amazon ECS & EKS – Container services
🔗 Hands-on:
✅ Launch an EC2 instance and connect via SSH
✅ Create an Auto Scaling Group with Load Balancer
✅ Deploy a simple Lambda function
EC2 Instance
On Demand Instance
Spot Instance
Reserved Instance
EC2 Compared to a Hotel (Simple Analogy)
- EC2 Instance = Hotel Room (Temporary rental)
- AMI (Amazon Machine Image) = Room Type (Standard, Suite, Deluxe)
- CPU & RAM = Room Size & Facilities (Basic, Premium, Luxury)
- EBS Storage = Hotel Closet (Store your belongings)
- Security Groups = Room Key & Door Locks (Access control)
- Auto Scaling = Booking More Rooms When Guests Increase
AMI
An Amazon Machine Image (AMI) is a pre-configured template that contains the necessary information to launch an EC2 instance.
✅ EC2 Instance – It's like buying a new computer online, where you get the hardware (CPU, RAM, storage, network, etc.) and can set it up as needed.
✅ AMI (Amazon Machine Image) – It's like buying a pre-installed computer with an operating system and necessary software already set up, so you don’t have to install the OS manually.
💡 With AMI, launching an instance is faster since everything is already installed and configured.
Example:
💻 Buying a new laptop:
1️⃣ If you buy a bare laptop, you need to install Windows/Linux, drivers, and software manually.
2️⃣ If you buy a pre-installed laptop, it comes with Windows, MS Office, Chrome, and Antivirus already set up.
Similarly,
- EC2 Instance (Without AMI) = A blank server where you manually install OS and software.
- EC2 Instance (With AMI) = A ready-to-use server with pre-installed OS and necessary software.
So, AMI saves time by letting you launch an EC2 instance without manual setup! 🚀
What Does an AMI Contain?
✅ Operating System (OS) – Linux, Windows, macOS
✅ Software & Applications – Web server (Apache, Nginx), Database, etc.
✅ Configuration Settings – Security settings, network settings
✅ Storage Information – Root volume (EBS snapshot)
Create a Custom AMI & Use Auto Scaling
🔹 Step 1: Install & Configure Everything on One EC2 Instance
- Boot an EC2 instance
- Install your application, required software, and dependencies
- Configure settings (security, environment variables, etc.)
🔹 Step 2: Create a Custom AMI
- Go to the EC2 console → Select your configured instance
- Click Actions → Create Image (AMI)
- This AMI will have everything pre-installed
🔹 Step 3: Launch New EC2 Instances from the Custom AMI
- When traffic increases, use this AMI to launch new instances
- No need to manually install the application every time
🔹 Step 4: Use Auto Scaling for Automatic Scaling
- Set up an Auto Scaling Group
- Define a rule: Example → "If CPU usage > 70%, launch a new EC2 instance"
- AWS will automatically create new instances from your Custom AMI
Real-Life Example (Scaling a Website)
1️⃣ You set up a web application on an EC2 instance and install Apache, Node.js, or Python
2️⃣ You create a Custom AMI with everything installed
3️⃣ When traffic increases, Auto Scaling launches more EC2 instances using this AMI
4️⃣ Load Balancer distributes traffic across multiple instances
5️⃣ When traffic decreases, Auto Scaling terminates unused instances to save costs
Advantages of Custom AMI & Auto Scaling
✅ Saves Time – No need to install software again on each instance
✅ Handles High Traffic – New instances launch automatically
✅ Cost-Effective – Instances scale up/down based on traffic
✅ Consistency – All instances have the same pre-configured setup
EC2 Instance Lifecycle
An EC2 instance goes through multiple states in its lifecycle, similar to how a computer is powered on, used, and shut down.
🔹 Example: Lifecycle in Action
Imagine you are launching a web server on AWS using an EC2 instance:
Step 1: Launching an Instance (Pending → Running)
- You start a new EC2 instance
- It moves to the Pending state
- Once booted, it moves to Running
✔ Example: You power on your laptop and start using it
Step 2: Stopping the Instance (Running → Stopping → Stopped)
- If you no longer need the instance, you stop it
- Moves to Stopping, then to Stopped
✔ Example: You shut down your laptop but do not delete any files
Step 3: Restarting the Instance (Stopped → Running)
- You decide to use the instance again, so you start it
✔ Example: You press the power button to turn on your laptop again
Step 4: Terminating the Instance (Running → Terminating → Terminated)
- If you terminate the instance, AWS permanently deletes it
✔ Example: You factory reset your laptop and sell it
Storage Services (S3, EBS, EFS, Glacier)
📌 Amazon S3 (Simple Storage Service) – Object storage
📌 S3 Bucket Policies & Permissions
📌 EBS (Elastic Block Store) – Persistent storage for EC2
📌 EFS (Elastic File System) – Shared storage across instances
📌 Glacier – Archival storage
🔗 Hands-on:
✅ Create an S3 bucket and upload files
✅ Configure S3 bucket permissions (Public vs. Private)
✅ Attach and mount an EBS volume to an EC2 instance
Networking & Security (VPC, IAM, Security Groups)
📌 AWS VPC (Virtual Private Cloud) – Isolated network environment
📌 Subnets, Route Tables, Internet Gateway, NAT Gateway
📌 IAM (Identity and Access Management) – Users, Groups, Roles, Policies
📌 Security Groups & NACLs (Firewall Rules)
📌 AWS Shield & WAF (DDoS Protection)
🔗 Hands-on:
✅ Create a VPC with public and private subnets
✅ Set up IAM users with custom permissions
✅ Configure Security Groups for EC2
Monitoring & Logging (CloudWatch, CloudTrail)
📌 AWS CloudWatch – Monitoring metrics & alarms
📌 AWS CloudTrail – Logs API calls for security auditing
📌 AWS Config – Resource compliance tracking
🔗 Hands-on:
✅ Set up CloudWatch Alarms for EC2
✅ Enable CloudTrail and track account activity
Database Services (RDS, DynamoDB, Redshift)
📌 Amazon RDS (Relational Database Service) – MySQL, PostgreSQL, etc.
📌 Amazon DynamoDB (NoSQL Database)
📌 Amazon Redshift (Data Warehousing)
📌 AWS Aurora (High-performance relational DB)
🔗 Hands-on:
✅ Launch an RDS MySQL database and connect using MySQL Workbench
✅ Create a DynamoDB table and add data