Amazon AWS vs Microsoft Azure

Compare GPU pricing, features, and specifications between Amazon AWS and Microsoft Azure cloud providers. Find the best deals for AI training, inference, and ML workloads.

Amazon AWS logo

Amazon AWS

Provider 1

6
GPUs Available
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Microsoft Azure logo

Microsoft Azure

Provider 2

0
GPUs Available
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Comparison Overview

6
Total GPU Models
Amazon AWS logo
6
Amazon AWS GPUs
Microsoft Azure logo
0
Microsoft Azure GPUs
0
Direct Comparisons
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Amazon AWS
Microsoft Azure

GPU Pricing Comparison

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Features Comparison

Amazon AWS

  • Global Infrastructure

    Extensive network of data centers across multiple regions worldwide

  • Pay-as-you-go Pricing

    Flexible pricing model with no upfront commitments required

  • Advanced Security

    Comprehensive security tools and compliance certifications

  • Auto Scaling

    Automatically adjust resources based on demand

  • Integrated Services

    Extensive ecosystem of services that work seamlessly together

  • Developer Tools

    Comprehensive suite of tools for development, deployment, and management

Microsoft Azure

  • Azure AI

    Comprehensive suite of AI services and tools for building intelligent applications

  • Enterprise Integration

    Seamless integration with Microsoft ecosystem and enterprise tools

  • Hybrid Capabilities

    Strong hybrid and multi-cloud support with Azure Arc

  • Advanced Security

    Industry-leading security features and compliance certifications

  • Global Scale

    Extensive worldwide network of data centers and edge locations

Pros & Cons

Amazon AWS

Advantages
  • Broad range of compute options including GPUs
  • Highly scalable and reliable infrastructure
  • Pay-as-you-go pricing with cost optimization tools
  • Extensive global network of data centers
Considerations
  • Complex pricing structure
  • Steep learning curve for new users
  • Potential for unexpected costs without proper management

Microsoft Azure

Advantages
  • Strong enterprise integration and support
  • Comprehensive AI and machine learning services
  • Advanced security and compliance features
  • Extensive hybrid cloud capabilities
Considerations
  • Complex pricing and billing structure
  • Can be expensive for certain workloads
  • Steeper learning curve for new users

Compute Services

Amazon AWS

Amazon EC2

Virtual servers in the cloud with a wide range of instance types.

Amazon ECS

Fully managed container orchestration service.

  • Support for Docker containers
  • Integration with other AWS services
Amazon EKS

Managed Kubernetes service for container orchestration.

  • Certified Kubernetes conformant
  • Integrates with AWS networking and security services

Microsoft Azure

Azure Virtual Machines

GPU-enabled VMs for various workloads

Azure Kubernetes Service (AKS)

Managed Kubernetes service with GPU support

  • Integrated GPU node pools
  • Automated scaling and updates
Azure Machine Learning

End-to-end ML platform with GPU acceleration

  • Automated ML capabilities
  • Integrated MLOps

Pricing Options

Amazon AWS

On-Demand Instances

Pay for compute capacity by the second with no long-term commitments.

Spot Instances

Use spare EC2 capacity at up to 90% off the On-Demand price.

Reserved Instances

Save up to 72% compared to On-Demand pricing with a 1 or 3-year commitment.

Savings Plans

Save up to 72% on compute usage with a 1 or 3-year commitment to a consistent amount of usage.

Microsoft Azure

Pay-as-you-go

Flexible pricing with no upfront commitment

Reserved VM Instances

Save up to 72% with 1 or 3-year commitments

Spot VMs

Up to 90% savings for interruptible workloads

Azure Hybrid Benefit

Cost savings for existing Windows Server and SQL Server licenses

Getting Started

Amazon AWS

Get Started
  1. 1
    Sign up for AWS

    Create an AWS account to access the cloud platform.

  2. 2
    Choose a compute service

    Select from EC2, Lambda, or container services based on your workload needs.

  3. 3
    Launch an instance

    Configure and launch your first compute instance or container.

  4. 4
    Set up security

    Configure security groups and access controls for your resources.

  5. 5
    Monitor and optimize

    Use AWS CloudWatch and Compute Optimizer to monitor performance and reduce costs.

Microsoft Azure

Get Started
  1. 1
    Create an Azure account

    Sign up for Azure and get started with free credits

  2. 2
    Set up your environment

    Configure your subscription, resource groups, and access controls

  3. 3
    Choose compute services

    Select from VMs, containers, or serverless based on your needs

  4. 4
    Deploy resources

    Launch your first GPU-enabled instance or AI service

Support & Global Availability

Amazon AWS

Global Regions

25+ regions and 80+ availability zones worldwide.

Support

Basic (free), Developer, Business, Enterprise support plans with varying response times and features. Extensive documentation, forums, and training resources.

Microsoft Azure

Global Regions

60+ regions worldwide with multiple availability zones

Support

Basic, Developer, Standard, and Professional Direct support plans with 24/7 options. Extensive documentation and community resources.