Azure VM pricing: Understanding the costs of virtual machines

Note: Pricing and product information are correct as of May 3, 2024, and subject to change.

The virtual machine market is witnessing an uptrend, driven by the rapid growth of cloud computing technologies and the increasing demand for scalable computing resources. With a market size value of USD 11,277.6 million in 2023, the virtual machine market is projected to experience a compound annual growth rate (CAGR) of 15.1% from 2023 to 2030, reaching a revenue forecast of USD 30,122.3 million by 2030.

Within this thriving market, among many hyperscalers, Microsoft Azure offers a suite of cloud services, including Azure virtual machines (Azure VMs). As businesses increasingly adopt cloud resources and migrate their applications and data to the cloud, understanding virtual machine pricing is essential for effective cloud cost optimization and budgeting. Cloud costs can quickly escalate if not monitored and optimized correctly, leading to unexpected expenses and potential financial strain. This article digs into the details of Azure VM pricing, exploring pricing models, pricing factors, cost estimation tools, optimization strategies, and best practices.


  1. Azure VM pricing offers flexibility through multiple models, such as pay-as-you-go and reserved instances, but estimating costs may be complex due to various factors.

  2. The Azure pricing calculator helps estimate costs for different VM configurations and additional Azure services for more accurate budgeting.

  3. DigitalOcean’s Droplets provide a more straightforward, predictable, and cost-effective pricing model, appealing to both smaller workloads with limited budgets and big enterprises.

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What is Azure virtual machine pricing?

Azure Virtual Machine pricing refers to the cost structure of deploying and running virtual machines (VMs) on Microsoft’s Azure cloud platform. The pricing model for Azure VMs allows customers to choose from various VM types, VM series, sizes, and configurations to meet their specific compute capacity needs.

Azure virtual machine pricing models

Microsoft Azure offers several pricing models for virtual machines, allowing organizations to optimize their cloud costs based on their specific workload requirements and budget considerations. Each pricing model caters to different use cases and budget requirements, allowing organizations to optimize their Azure virtual machine costs based on their specific needs. The primary pricing models include:

Pay-as-you-go pricing for Azure VMs

Part of the pay-as-you cloud computing model, Azure’s pay-as-you-go flexible pricing model lets customers pay for Azure virtual machine instances based on usage without any upfront commitments or long-term contracts. Pay-as-you-go pricing is ideal for production workloads with variable or unpredictable compute demands, providing the ability to scale resources up or down as needed.

Reserved instances

Azure offers reserved instances involving upfront payments for a one-year or three-year commitment. By reserving compute capacity in advance, customers can benefit from cost savings compared to pay-as-you-go pricing. Reserved instances are a cost-effective option for applications with consistent resource needs. This pricing model best suits customers with predictable workloads or steady-state computing requirements.

Azure savings plan for compute

The Azure savings plan is a pricing model for compute resource usage. Suppose the actual usage of Azure components (like virtual machines, Azure Databricks, and Azure Container Instances) is less than or equal to the hourly amount committed in the savings plan. In that case, organizations benefit from the lower, discounted savings plan prices for those compute resources.

However, if the usage exceeds the hourly amount committed in the savings plan, the pricing model adjusts accordingly. The usage portion up to the hourly amount is billed at the lower savings plan prices, which are included in the overall plan cost. Any additional usage beyond the hourly amount is then billed separately at the standard pay-as-you-go prices. This plan is particularly useful for businesses with dynamic or unpredictable workloads that require the flexibility to scale compute resources up or down without being tied to specific VM configurations.

Spot virtual machines

Azure spot virtual machines offer an opportunity to capitalize on unutilized Azure capacity as spot instances are offered at significantly reduced costs compared to pay-as-you-go pricing. These instances are ideal for batch processing, high-performance computing, and other workloads that can tolerate interruptions, as Azure can reclaim the resources at any time based on capacity availability.

Factors affecting Azure VM pricing

Azure virtual machine pricing is influenced by several key factors, which determine the overall cost of deploying and running virtual machines on the Microsoft Azure cloud platform.

Virtual machine size

The virtual machine size is a crucial factor directly impacting Azure VM pricing. The size encompasses the compute resources allocated to the virtual machine, including CPU, RAM, storage capacity, and high throughput networking capabilities. Generally, larger virtual machine instances with more powerful CPUs, higher RAM configurations, and enhanced networking performance command higher prices. Choosing the right VM size helps to ensure optimal performance while managing costs effectively.

Operating system

The choice of operating system plays a role in determining Azure VM pricing. Microsoft Azure supports both Windows server and Linux virtual machines, with pricing varying based on the selected operating system. Organizations may benefit from the Azure Hybrid Benefit for Windows server workloads, which allows them to use their existing Microsoft licenses.

Azure region

Microsoft’s global data center infrastructure is divided into multiple Azure regions, and the cost of Azure services, including virtual machines, can vary across these regions. The pricing for Azure VMs is influenced by local infrastructure costs, regional demand, and data residency requirements. Organizations should carefully consider the Azure region to determine which best aligns with their operational needs, performance requirements, and cost optimization goals.

Azure VM type

Azure offers a diverse range of virtual machine types optimized for different workload scenarios. The pricing for these specialized VM types varies based on their configurations and capabilities, ensuring that customers pay for the resources aligned with their specific application and workload requirements. The following table gives a short description of different types of Azure VMs.

VM Type Description
General-purpose VMs Designed for balanced compute and memory requirements. Suitable for web servers, small to medium databases, and development/test environments.
Compute-optimized VMs Ideal for CPU-intensive workloads such as high-performance computing, batch processing, and other compute-heavy applications.
Memory-optimized VMs Optimized for memory-intensive applications, such as relational database servers, caching services, and in-memory analytics.
Storage-optimized Suitable for disk throughput and large transactional databases. Most sought for Big Data, SQL, NoSQL databases, and data warehousing.
GPU-Accelerated VMs Equipped with powerful GPUs, well-suited for graphics-intensive tasks like machine learning, deep learning, video rendering, and other parallel workloads.
High performance compute Designed for high-throughput network interfaces.

Estimating Azure VM costs

Accurate cost estimation helps businesses plan and manage their cloud spending effectively. Organizations can gain visibility into the potential costs associated with their Azure VM deployments and other required Azure services by using tools like the Azure pricing calculator.

Estimating costs for different VM configurations using the Azure pricing calculator

Microsoft Azure provides an online tool called the Azure pricing calculator to help customers estimate the costs associated with their cloud resource requirements, including Azure virtual machines. Users can explore and compare pricing for different Azure virtual machine configurations. By selecting the appropriate VM type and operating system (Windows Server or Linux VMs) and specifying the desired virtual machine size (CPU, RAM, storage, high throughput networking), customers can obtain cost estimates tailored to their specific compute capacity needs.

Considering additional Azure services

While estimating costs for Azure virtual machines, consider the potential usage of other Azure services that may be required for your cloud workloads. The Azure pricing calculator allows you to factor in additional services like Azure relational database management, Azure data storage needs, and Azure Kubernetes service for container orchestration and management. By including these costs, organizations can devise a strategy for Azure cost optimization and prevent unexpected expenses from overlooked service dependencies.

Understanding the potential challenges of Azure VM adoption

While Azure Virtual Machines offer numerous benefits and flexible pricing options, there are some potential drawbacks. Carefully evaluate the following potential drawbacks and weigh them against the benefits of using Azure virtual machines to ensure a well-informed decision that aligns with your organization’s needs and budgetary requirements.


Azure VM pricing can be complex, with various factors influencing the costs, such as VM size, operating system, region, and pricing model. Understanding and accurately estimating the costs can be challenging, especially for organizations with dynamic or unpredictable workloads.

Vendor lock-in

By committing to Azure VMs, businesses may experience vendor lock-in, making it difficult to migrate to other cloud providers or on-premises solutions without incurring significant costs and engineering efforts. Egress costs, which are charges incurred for transferring data out of the cloud provider’s network, also contribute to vendor lock-in by making it financially prohibitive to move data elsewhere.

Unexpected costs

Despite cost estimation tools, businesses may encounter unexpected costs due to data transfer charges, usage spikes, overlooked service dependencies, and Azure hidden costs, leading to higher-than-anticipated cloud bills. While Azure provides cost management tools, some organizations may find it challenging to gain granular visibility into their cloud costs, making it difficult to optimize spending effectively.

Licensing complexities

Managing software licenses, especially for Windows Server or SQL Server, can be complex. The licensing fees for specific Microsoft software can constitute a significant portion of the overall cost. Organizations must thoroughly understand licensing models, usage rights, and regulations to avoid penalties and disruptions.

Embrace simplicity and savings for your cloud needs using DigitalOcean’s Droplets

DigitalOcean offers an alternative pricing model for its virtual machine instances called Droplets. Here are some factors to help you choose between DigitalOcean vs Azure:

Transparent pricing

DigitalOcean’s pricing is transparent, with clear upfront pricing information, making it easier to compare costs and make informed decisions. Regarding entry-level cloud computing resources, DigitalOcean’s Droplet pricing offers an affordable starting point compared to Azure Virtual Machines. DigitalOcean’s smallest Droplet size, aptly named the Basic Droplet, starts at just $4 monthly. In contrast, Azure’s smallest general-purpose VM starts at $6.1 per month.

This pricing difference can add up quickly, especially for small businesses, startups, and developers who require multiple low-cost virtual machines for their projects or testing environments. DigitalOcean’s affordable pricing, transparent billing model, user-friendly documentation, and highly engaging community make it the most cost-effective choice for those with modest computing requirements or limited budgets.

Simplicity with predictable costs

DigitalOcean’s Droplet pricing is straightforward and easy to understand. It is a fixed monthly price based on the Droplet size, eliminating the complexity of various factors influencing the costs. With Droplets, you know exactly how much you’ll be paying each month, making it easier to budget and avoid unexpected costs, pricing fluctuations, or bill shock. Unlike Microsoft Azure vm pricing, DigitalOcean’s budget-friendly Droplet pricing is preferred by most cloud businesses.

No vendor lock-in

DigitalOcean’s platform is engineered to be open and portable, mitigating the risk of vendor lock-in common with Azure. While long-term commitments with cloud vendors may offer cost savings, they also bind users to a predetermined level of spending, regardless of potential usage fluctuations. Compared to Azure, DigitalOcean offers a generous free bandwidth allowance (500 GiB to 11,000 GiB per month, depending on the Droplet plan) and does not implement region-based pricing for data egress, simplifying budgeting for bandwidth costs. DigitalOcean’s approach promotes flexibility, allowing organizations to adapt their cloud consumption based on evolving needs without being tied to rigid contracts.

Simplified licensing

DigitalOcean’s Droplets come pre-installed with popular open-source operating systems and software, eliminating the need to manage complex software licensing and compliance requirements.

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DigitalOcean Droplets offer simplicity, predictable costs, and competitive pricing, which makes them an attractive alternative to Azure virtual machines, especially for developers, startups, and SMBs looking for a cost-effective and straightforward cloud computing solution.

Try DigitalOcean’s value-driven Droplet pricing model today!


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