0Pricing
AWS for Backend Developers (EC2, S3, RDS, Lambda) · Lesson

EC2 Instance Types and AMIs

Select optimal EC2 instance types for specific workloads and create custom Amazon Machine Images (AMIs) for consistent deployments.

EC2 Instance Types and AMIs is a free AWS for Backend Developers (EC2, S3, RDS, Lambda) lesson on CoddyKit — lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the AWS for Backend Developers (EC2, S3, RDS, Lambda) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

Choosing the Right EC2 Instance

When you launch an EC2 instance, you need to pick an instance type. This choice is crucial for both performance and cost optimization.

An instance type defines the virtual hardware resources of your EC2 instance, like CPU, memory, storage, and networking capacity.

EC2 Instance Families Overview

AWS categorizes instance types into families, each optimized for different use cases. Understanding these helps you make the best choice for your applications.

  • General Purpose: Balanced compute, memory, and networking.
  • Compute Optimized: High-performance processors.
  • Memory Optimized: Large amounts of RAM.
  • Storage Optimized: High-performance local storage.
  • Accelerated Computing: Hardware accelerators (GPUs).

General Purpose: Balanced Workloads

General Purpose instances offer a good balance of compute, memory, and networking resources. They're ideal for a wide range of common applications.

  • M-series (e.g., m5.large): Great for web servers, small databases, and application servers.
  • T-series (e.g., t3.micro): Burst-capable instances, excellent for development, test environments, and low-traffic websites. They can burst CPU performance when needed.

Compute Optimized: High CPU Demand

Compute Optimized instances are specifically designed for applications that benefit significantly from high-performance processors and high CPU utilization.

C-series (e.g., c5.xlarge) are perfect for compute-intensive workloads such as:

  • High-performance web servers
  • Batch processing
  • Scientific modeling
  • Gaming servers

Memory Optimized: Large Datasets

Memory Optimized instances are built for workloads that process large datasets in memory. They feature a high memory-to-CPU ratio.

R-series (e.g., r5.2xlarge) and X-series (e.g., x1.large) instances are well-suited for:

  • High-performance relational databases
  • In-memory caches (like Redis)
  • Big data analytics
  • Enterprise applications requiring large memory.

Introducing Amazon Machine Images (AMIs)

An Amazon Machine Image (AMI) is a special type of virtual appliance that serves as a template for launching EC2 instances.

It defines the initial state of an instance, including the operating system, pre-installed software, configuration settings, and data for the root volume.

AMI Components and Sources

An AMI typically includes:

  • A template for the root volume (e.g., OS, application server, applications).
  • Launch permissions that control which AWS accounts can use the AMI.
  • A block device mapping that specifies the volumes to attach to the instance.

You can use AWS-provided AMIs, AMIs from the AWS Marketplace, or create your own custom AMIs.

Building Your Own Custom AMI

Creating a custom AMI allows you to pre-configure an instance with your specific software, settings, and data, saving time during launch.

The process involves: launching an instance from an existing AMI, customizing it (installing software, configuring settings), and then creating a new AMI from that running instance. This captures its current state as a reusable template.

Why Use Custom AMIs?

Custom AMIs offer several significant advantages for managing your EC2 instances:

  • Consistency: Ensures all instances launched from it have identical, known configurations.
  • Faster Launches: Instances are ready to use immediately, as software is pre-installed.
  • Security Baselines: You can bake in security patches and hardening measures.
  • Disaster Recovery: Quickly launch instances with known good configurations after an event.

Best Practices for AMIs

To maximize the benefits of AMIs, consider these best practices:

  • Regular Updates: Keep your custom AMIs updated with the latest OS patches and software versions.
  • Minimalism: Include only necessary software to reduce the attack surface and launch time.
  • Automation: Use tools like AWS Image Builder to automate AMI creation and updates.
  • Documentation: Clearly document what's included in each custom AMI for easy management.

Quick Check: Instance Types

You're building a new backend service that will handle a high volume of concurrent requests and perform complex calculations. Which EC2 instance family would generally be the most suitable starting point?

Recap: Instance Types & AMIs

We explored EC2 instance types, understanding how different families (General Purpose, Compute, Memory, Storage) cater to specific workload needs.

We also learned about Amazon Machine Images (AMIs), their components, and the significant benefits of creating custom AMIs for consistent, fast, and secure deployments. Choosing the right instance type and leveraging custom AMIs are key for efficient cloud infrastructure.

Frequently asked questions

Is the “EC2 Instance Types and AMIs” lesson free?

Yes — the full text of “EC2 Instance Types and AMIs” is free to read here on the web, and the AWS for Backend Developers (EC2, S3, RDS, Lambda) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the AWS for Backend Developers (EC2, S3, RDS, Lambda) course, upgrade to CoddyKit PRO.

What will I learn in “EC2 Instance Types and AMIs”?

Select optimal EC2 instance types for specific workloads and create custom Amazon Machine Images (AMIs) for consistent deployments. You practise AWS for Backend Developers (EC2, S3, RDS, Lambda) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start AWS for Backend Developers (EC2, S3, RDS, Lambda)?

No prior experience is required. AWS for Backend Developers (EC2, S3, RDS, Lambda) on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “EC2 Instance Types and AMIs” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this AWS for Backend Developers (EC2, S3, RDS, Lambda) lesson?

Yes. Every AWS for Backend Developers (EC2, S3, RDS, Lambda) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. EC2 Instance Types and AMIs
  2. Implementing Auto Scaling Groups
  3. Load Balancing with ELB
  4. Spot Instances and Cost-Efficient Compute
← Back to AWS for Backend Developers (EC2, S3, RDS, Lambda)