AWS Virtual Machine: What It Is, How It Works & How to Choose

If you’re looking for a flexible and scalable virtual machine (VM), AWS virtual machines are an excellent solution. An Amazon Web Services virtual machine offers cloud-provided service, allowing you to access a virtual service in minutes. You only pay for what you use, and don’t buy hardware or install an operating system. AWS handles the data centers, and you control the virtual machine.

Cloud VMs are just one method of using a virtual machine. Alternatively, local VMs (like Parallels Desktop) run directly on your Mac using your own CPU, memory, and disk. Cloud VMs are built for scale, shared access, and always-on availability. Local VMs are designed for speed, offline use, and tight integration with your personal workflow.

This guide covers what AWS virtual machines are, how they function, and how to choose the right configuration.

What is an AWS virtual machine?

Amazon Elastic Compute Cloud (Amazon EC2) is AWS’s on-demand cloud compute service. You launch AWS virtual machines through the AWS Console, and choose your specs: operating system, CPU, memory, storage, and networking. One study of cloud-based virtual machines found that AWS C2 virtual machines exceeded the performance of other popular competitors. 

Because AWS virtual machines are part of a global cloud platform, they’re commonly used for:

• Web applications: Users can create and deploy apps without needing to purchase new hardware.
• Distributed development and testing: Spinning up temporary environments that teams can share, scale, or tear down quickly.
• Databases and backend services: Running databases, caches, and internal services behind applications.
• AI and machine learning workloads: Training or running AI/ML models. Research shows that AI and ML are the top reason that organizations use public cloud services.
• Always-on infrastructure: Servers that must run 24/7 with high availability, backups, and centralized management.

How AWS virtual machines work

AWS virtual machines work by allowing you to access compute resources from a massive pool of shared cloud infrastructure. When you launch a virtual machine using Amazon Web Services, AWS allocates CPU, memory, storage, and networking from its data centers and assembles them into a usable server.

AWS groups virtual machines into broad EC2 instance types, each optimized for a different kind of workload:

• General purpose: Balanced CPU, memory, and networking for everyday workloads like web apps and internal services
• Compute-optimized: Higher CPU capacity for compute-heavy tasks such as batch processing and build systems
• Memory-optimized: More RAM for delivering fast performance for workloads involving large datasets.
• Storage-optimized: High disk throughput and low latency for data-intensive workloads.
• GPU-accelerated: Specialized hardware for graphics, video processing, and AI or machine learning workloads.

Under the hood, AWS uses the Nitro hypervisor, a lightweight foundation layer that offloads much of the traditional hypervisor work to dedicated hardware and software. 

Key features of AWS VMs

AWS virtual machines are designed to scale, adapt, and stay reliable as workloads change. Notable capabilities include:

• Auto Scaling for elastic capacity: Automatically adds or removes virtual machines based on demand. If traffic increases, AWS launches more instances; when demand drops, it scales them down.
• Load balancing for distributed workloads: Spreads incoming traffic across multiple VMs, keeping applications responsive and reducing the risk that a single instance becomes a bottleneck.
• Amazon Machine Images: AMIs act as blueprints for AWS virtual machines, creating standardized and repeatable environments.
• Pricing models: The cost of AWS depends on your plan - there are different AWS VM pricing options to match your workload and needs. Choose from On-Demand, Reserved Instances, Savings Plans, and Spot Instances.
• Monitoring & visibility: AWS provides built-in AWS monitoring tools that track metrics such as CPU usage, memory pressure, disk activity, and network throughput.
• Global regions and availability zones: AWS virtual machines run in multiple global regions, each made up of separate availability zones. This design allows you to deploy VMs closer to users for lower latency or spread them across zones to improve fault tolerance. 

How to choose the right AWS VM

Choosing the right AWS virtual machine is important for usage – you want to match your VM to how your workload behaves. A few core factors will narrow the field quickly.

1. Match workload type to instance category

Start by mapping which of the AWS instance families best meets your needs. 

• For web apps and APIs, general purpose instances provide a balanced mix of CPU, memory, and networking.
• Handling databases? Memory-optimized instances help keep performance stable under load.
• For AI & ML, GPU-accelerated instances support model training and inference.
• File processing or data-heavy backends do well in storage-optimized instances.

2. Balance cost & performance

There are different AWS EC2 pricing plans, and they relate to performance. For example, On-Demand Instances offer pay-as-you-go compute capacity, while Spot Instances allow you to use spare ECO capacity in the AWS Cloud at a discount. For business-critical events and high-availability requirements, you can also make On-Demand Capacity Reservations to reserve compute capacity in a specific Availability Zone. 

3. Plan for scaling and reliability

Even if you start small, assume your needs will change, and design your VM setup so it can scale. Use AWS Auto Scaling Groups to automatically adjust capacity as demand rises or falls. Also, deploy across multiple availability zones (AZs) to reduce the impact of hardware or data center failures.

4. Consider OS & licensing needs

Finally, factor in what the VM needs to run, whether that’s Linux, Windows Server, or specialized distros. 

AWS VMs vs. Local VMs 

AWS virtual machines are only one type of VM. The second option is local virtual machines. Understanding where each fits helps you avoid forcing the wrong tool into the wrong role.

When cloud VMs fit best

Cloud-based virtual machines are a strong fit when workloads need to live in shared, always-available infrastructure:

 

• Infrastructure hosting: Running production websites, APIs, and backend systems.
• Team collaboration: Shared environments accessed by multiple users or services.
• Distributed workloads: Batch jobs, analytics, or processing spread across many instances
• Server-side services: Systems that must be online 24/7 with centralized management and backups

When local VMs fit best

Local virtual machines run directly on a user’s computer and are optimized for responsiveness and offline use. For Mac users, tools like Parallels Desktop are best suited when the workload is tightly tied to the desktop:

• Mac users who need Windows apps locally and offline: No reliance on internet connectivity.
• Fast, interactive workloads: Design tools, finance models, development tasks, or testing that benefit from local CPU, memory, and graphics.
• Dev/test environments tied to desktop workflows: Quick snapshots, instant restarts, and direct access to local files and tools

Choosing the right AWS virtual machine with confidence

AWS virtual machines stand out for three core reasons: scalability, flexibility, and global availability. With Amazon Web Services, you can start with a single VM, scale to hundreds when demand grows, adjust resources as workloads change, and deploy close to users around the world – all without owning or managing physical hardware.

The most reliable way to choose the right AWS VM is experimentation. Testing multiple instance categories, sizes, and architectures lets you see real cost and performance differences in your own environment.

FAQs

What’s the difference between an AWS virtual machine and a local VM on a Mac?

An AWS virtual machine runs in the cloud on infrastructure managed by Amazon Web Services. It’s accessed over the internet and designed for shared, always-on workloads that benefit from scalability, centralized management, and global availability.

A local VM on a Mac runs directly on your own hardware using software like Parallels Desktop. It’s optimized for fast, interactive, offline-friendly workflows where low latency and tight integration matter.

Do AWS VMs support both Windows and Linux?

Yes. AWS virtual machines support a wide range of Linux distributions and Windows Server editions.

How do I choose the right AWS instance type?

Start by matching your workload type to an instance category – general purpose, compute-optimized, memory-optimized, storage-optimized, or GPU-accelerated. Then balance cost versus performance. Finally, plan for scaling and reliability by using Auto Scaling Groups and multi–availability zone deployments.