Azure Virtual Machines: Everything You Need to Know and How to Choose the Right VM Size
Cloud computing has transformed the way organizations deploy applications, but not every workload can immediately move to Platform as a Service (PaaS) or containers. Many business applications still require full operating system control, legacy software support, custom security configurations, or specialized hardware. This is where Azure Virtual Machines (Azure VMs) become one of Microsoft's most powerful Infrastructure as a Service (IaaS) offering.
Azure Virtual Machines provide scalable, secure, and highly available computing resources that eliminate the need to purchase, maintain, or refresh physical servers. Whether you're migrating an existing datacenter, deploying enterprise applications, building development environments, or running high-performance workloads, Azure VMs provide the flexibility to meet virtually any business requirement.
In this article, we'll explore Azure Virtual Machines from the ground up, understand how they work, examine the different VM families, and learn how to choose the right VM size for your workloads while optimizing cost and performance.
What is an Azure Virtual Machine?
An Azure Virtual Machine is a software-based computer running inside Microsoft's global cloud infrastructure.
Just like a physical server, an Azure VM includes:
CPU
Memory (RAM)
Storage
Network interfaces
Operating System
Applications
The difference is that Microsoft manages the physical hardware, while you manage everything inside the virtual machine.
This follows the Shared Responsibility Model, where Microsoft is responsible for:
Physical datacenters
Hardware maintenance
Networking infrastructure
Hypervisor
Physical security
Customers are responsible for:
Operating System
Applications
Updates
Security
Antivirus
Data
User access
Backup configuration
Think of Azure Virtual Machines as renting powerful enterprise servers only when you need them instead of buying expensive hardware.
Azure VM Architecture
A typical Azure VM consists of multiple Azure resources working together.

Every component can be managed independently.
Components of an Azure VM
Virtual Machine
The compute resource that runs your operating system.
Examples:
Windows Server
Ubuntu
Red Hat Enterprise Linux
SUSE Linux
Debian
Managed Disks
Azure stores VM disks separately from compute resources.
Types include:
OS Disk
Contains:
Operating System
Boot partition
System files
Data Disk
Stores:
Databases
Application files
User data
Logs
Temporary Disk
Provides:
High-speed temporary storage
Page files
Cache
Scratch data
Important:
Temporary disks are not persistent.
Data will be lost if the VM is moved or redeployed.
Network Interface (NIC)
Every VM requires at least one NIC.
The NIC connects the VM to:
Virtual Network
NSGs
Load Balancer
Public IP
Multiple NICs are supported for certain VM sizes.
Public IP Address
Optional.
Required only if the VM needs direct internet connectivity.
Examples:
Bastion replacement (not recommended)
Testing
Public web servers
Best practice:
Avoid assigning Public IPs whenever possible.
Use:
Azure Bastion
VPN Gateway
ExpressRoute
Jump Servers
Virtual Network (VNet)
Every Azure VM belongs to a subnet inside a Virtual Network.
VNets provide:
Private communication
DNS
Routing
Isolation
Azure VM Deployment Models
Azure supports several deployment options.
Azure Portal
Best for beginners.
GUI-based deployment.
Azure CLI
Example:
az vm create
Azure PowerShell
Example:
New-AzVM
ARM Templates
Infrastructure as Code.
Repeatable deployments.
Bicep
Microsoft's modern Infrastructure as Code language.
Cleaner than ARM JSON.
Terraform
Popular multi-cloud Infrastructure as Code tool.
VM Images
Azure Marketplace provides thousands of ready-to-use images.
Examples include:
Windows
Windows Server 2025
Windows Server 2022
SQL Server
Visual Studio
Linux
Ubuntu
Debian
Red Hat
Oracle Linux
SUSE
Applications
WordPress
Jenkins
Docker
Kubernetes Nodes
You can also upload your own custom images.
Azure VM Availability Options
Keeping applications online is critical.
Azure offers multiple options.
Availability Sets
Protect against:
Planned maintenance
Hardware failures
Uses:
Fault Domains
Update Domains
Typically provides 99.95% SLA.
Availability Zones
Separate physical datacenters within the same Azure region.
Benefits:
Higher resiliency
Fault isolation
Supports 99.99% SLA.
Virtual Machine Scale Sets (VMSS)
Automatically creates and manages multiple VM instances.
Perfect for:
Web servers
APIs
Application farms
Supports:
Auto Scaling
Load Balancing
Rolling updates
VM Storage Performance
Azure offers several managed disk options.
Disk Type | Best For |
|---|---|
Standard HDD | Archive, Backup |
Standard SSD | General workloads |
Premium SSD | Production applications |
Premium SSD v2 | High-performance databases |
Ultra Disk | Mission-critical databases |
Azure VM Pricing
Azure VM pricing depends on:
VM Size
Operating System
Region
Storage
Network
Reserved Instances
Spot VM usage
Remember:
Stopping a VM inside Windows does not stop billing.
You must:
Stop (Deallocate)
from Azure Portal or Azure CLI.
Choosing the Right Azure VM Size
One of the most common mistakes organizations make is selecting the wrong VM size.
Choosing a VM that is too small causes:
Slow performance
High CPU
Application crashes
Choosing a VM that is too large results in:
Higher monthly costs
Wasted resources
Microsoft provides dozens of VM families, each optimized for different workloads.
Understanding VM Naming
Example:
Standard_D4s_v5
Meaning:
Component | Meaning |
|---|---|
D | General Purpose |
4 | vCPUs |
s | Premium SSD Support |
v5 | Generation |
Azure VM Families
B-Series (Burstable)
Best for:
Small websites
Test environments
Development
Domain Controllers
Low CPU applications
Characteristics:
Low cost
CPU credits
Burstable performance
Not suitable for constant high CPU workloads.
D-Series (General Purpose)
The most commonly used VM family.
Ideal for:
Active Directory
File Servers
IIS
Business applications
Medium SQL Servers
Balanced CPU and memory.
E-Series (Memory Optimized)
Designed for:
SQL Server
SAP
Oracle
Redis
Large in-memory databases
Provides significantly more RAM.
F-Series (Compute Optimized)
Designed for:
Application servers
Gaming servers
Batch processing
Analytics
Higher CPU-to-memory ratio.
M-Series
Enterprise-scale workloads.
Examples:
SAP HANA
Large databases
Mission-critical systems
Supports several terabytes of RAM.
L-Series
Storage optimized.
Best for:
Big Data
Cassandra
Hadoop
NoSQL databases
Provides extremely high disk throughput.
N-Series
GPU-enabled VMs.
Used for:
AI
Machine Learning
Deep Learning
CAD
Rendering
Video Editing

Selecting the Correct VM
Start with workload requirements.
Ask yourself:
How many users?
20 users
200 users
2000 users
CPU Usage
High?
Low?
Constant?
Bursting?
Memory Requirements
Applications like SQL Server require significant RAM.
Storage Performance
Does the workload require:
HDD
SSD
Premium SSD
Ultra Disk
Network Throughput
Some applications require:
High bandwidth
Low latency
Future Growth
Always leave room for scaling.
Azure allows resizing VMs later.
Common VM Recommendations
Workload | Recommended VM Family |
|---|---|
Active Directory | B-Series or D-Series |
DNS | B-Series |
File Server | D-Series |
IIS Web Server | D-Series |
SQL Server | E-Series |
SAP | M-Series |
AI Training | N-Series |
Jenkins | D-Series |
Dev/Test | B-Series |
Azure DevOps Agent | B-Series |
Rightsizing Best Practices
Never select VM sizes based only on guesswork.
Instead:
Monitor CPU utilization
Monitor Memory usage
Analyze Disk IOPS
Review Network throughput
Enable Azure Monitor
Review Azure Advisor recommendations
Azure Advisor can identify:
Oversized VMs
Underutilized VMs
Cost-saving opportunities
Performance recommendations
Vertical vs Horizontal Scaling
Vertical Scaling
Increase VM size.

Simple but may require a restart.
Horizontal Scaling
Add more VMs behind a Load Balancer.

Provides:
Better scalability
Higher availability
Fault tolerance
Often implemented using Virtual Machine Scale Sets.
Cost Optimization Tips
Reduce Azure VM costs by following these practices:
Stop and deallocate unused VMs.
Use Azure Advisor recommendations.
Select the correct VM family.
Choose Reserved Instances for long-running workloads.
Use Azure Hybrid Benefit if you have eligible Windows Server licenses.
Use Spot VMs for interruptible workloads such as testing, CI/CD, or batch processing.
Regularly review performance metrics and resize underutilized VMs.
Use Autoscale with VM Scale Sets for dynamic workloads.
Security Best Practices
Protect Azure Virtual Machines by implementing:
Microsoft Defender for Cloud
Just-in-Time (JIT) VM Access
Azure Bastion instead of Public IPs
Network Security Groups (NSGs)
Azure Disk Encryption
Managed Identities
Azure Backup
Automatic OS patching
Microsoft Entra ID authentication where applicable
Least privilege using Azure RBAC
Monitoring Azure Virtual Machines
Continuous monitoring helps maintain performance and availability.
Use Azure Monitor to track:
CPU utilization
Memory usage (via Azure Monitor Agent)
Disk latency and IOPS
Network throughput
Boot diagnostics
Guest OS metrics
Event logs
Performance trends
Integrate with Log Analytics and Azure Alerts to proactively detect issues before they impact users.
Final Thoughts
Azure Virtual Machines remain one of the most versatile and widely used services in Microsoft Azure. They provide organizations with the flexibility to migrate existing applications, host enterprise workloads, and build scalable cloud infrastructure without investing in physical hardware.
However, deploying a VM is only the beginning. Selecting the appropriate VM family and size is equally important for achieving the right balance between performance, availability, and cost. By understanding workload characteristics, leveraging Azure Advisor recommendations, monitoring resource utilization, and applying Azure best practices, organizations can maximize the value of their Azure investments.
As your cloud environment evolves, regularly revisit your VM sizing strategy. Azure makes it easy to scale resources up or down, allowing you to adapt to changing business requirements while maintaining operational efficiency and controlling costs.

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