Azure Virtual Machine Instance Types

Understand the various virtual machine sizes and families available on Azure to choose the optimal instance for your workload.

Understanding Instance Families

Azure offers a diverse range of VM instance types, categorized into families optimized for different use cases. Each family has specific CPU, memory, storage, and networking capabilities.

Key families include:

  • General Purpose: Balanced CPU-to-memory ratio, suitable for testing, development, small to medium databases, and web servers. (e.g., D-series, B-series)
  • Compute Optimized: High CPU-to-memory ratio, ideal for applications requiring significant CPU power like batch processing, web servers, and application servers. (e.g., F-series)
  • Memory Optimized: High memory-to-CPU ratio, designed for large in-memory databases, big data analytics, and caching workloads. (e.g., E-series, M-series)
  • Storage Optimized: Optimized for high disk throughput and IOPS, suitable for big data, SQL and NoSQL databases, and data warehousing. (e.g., Lsv2-series)
  • GPU Optimized: Feature high-throughput GPUs, perfect for machine learning, AI, rendering, and video editing. (e.g., NC-series, NV-series)
  • High Performance Compute (HPC): Designed for extreme computational requirements, including large-scale simulations and modeling. (e.g., H-series)

Featured Instance Types

Here's a quick look at some commonly used instance types:

Family Name vCPUs Memory (GiB) Max Data Disk I/O Ideal For
General Purpose Dsv5-series 2 - 96 8 - 384 Up to 25600 IOPS Web servers, small-to-medium databases, development/test environments
Compute Optimized Fsv2-series 2 - 64 4 - 128 Up to 32000 IOPS High CPU workloads, web servers, batch processing
Memory Optimized Esv5-series 2 - 96 16 - 768 Up to 25600 IOPS In-memory databases, big data analytics, large caches
Storage Optimized Lsv2-series 4 - 80 32 - 640 Up to 192000 IOPS Big data, NoSQL databases, data warehousing
GPU Optimized NCv3-series 10 - 40 70 - 440 Up to 12800 IOPS AI, machine learning, deep learning, rendering

For a comprehensive list and detailed specifications, please refer to the official Azure VM documentation.

Choosing the Right Instance Type

Selecting the appropriate instance type is crucial for performance and cost optimization. Consider the following factors:

  • CPU Requirements: How much processing power does your application need?
  • Memory Needs: Will your application handle large datasets in memory?
  • Storage Performance: Do you need high IOPS or throughput for your data disks?
  • Networking Throughput: Are there significant network data transfer requirements?
  • GPU Acceleration: Does your workload benefit from graphical processing units?
  • Cost: Balance performance needs with your budget.

Azure provides tools like Azure Advisor and performance monitoring metrics to help you assess your current resource utilization and make informed decisions.

Important Note: Instance availability may vary by Azure region. Always check regional availability for specific VM families and sizes.

Instance Sizing Guidelines

Azure VMs are available in a wide range of sizes. Each size is identified by a name that indicates its family and capabilities. For example, in Dsv5, D indicates the family (general purpose), s indicates premium storage support, and 5 indicates the generation.

The general naming convention often follows:

<Family>[s][d][f][x][h][z][o][v]<Generation>

Where:

  • s: Premium storage optimized
  • d: Temporarily premium storage optimized (ephemeral OS disk)
  • f: Compute optimized
  • x: High memory
  • h: HPC
  • z: Storage optimized
  • o: Storage optimized
  • v: GPU enabled

For a detailed breakdown of these modifiers and all available VM sizes, please consult the full Azure VM documentation.