Amazon AWS vs Google Cloud
Compare GPU pricing, features, and specifications between Amazon AWS and Google Cloud cloud providers. Find the best deals for AI training, inference, and ML workloads.
Amazon AWS
Provider 1
Google Cloud
Provider 2
Comparison Overview
GPU Pricing Comparison
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
Google Cloud
- Compute Engine
Scalable virtual machines with a wide range of machine types, including GPUs.
- Google Kubernetes Engine (GKE)
Managed Kubernetes service for deploying and managing containerized applications.
- Cloud Functions
Event-driven serverless compute platform.
- Cloud Run
Fully managed serverless platform for containerized applications.
- Vertex AI
Unified ML platform for building, deploying, and managing ML models.
- Preemptible VMs
Short-lived compute instances at a significant discount, suitable for fault-tolerant workloads.
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
Google Cloud
Advantages
- Flexible pricing options, including sustained use discounts
- Strong AI and machine learning tools (Vertex AI)
- Good integration with other Google services
- Cutting-edge Kubernetes implementation (GKE)
Considerations
- Limited availability in some regions compared to AWS
- Complexity in managing resources
- Support can be costly
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
Google Cloud
Compute Engine
Offers customizable virtual machines running in Google's data centers.
Google Kubernetes Engine (GKE)
Managed Kubernetes service for running containerized applications.
- Automated Kubernetes operations
- Integration with Google Cloud services
Cloud Functions
Serverless compute platform for running code in response to events.
- Automatic scaling and high availability
- Pay only for the compute time consumed
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.
Google Cloud
On-Demand
Pay for compute capacity per hour or per second, with no long-term commitments.
Sustained Use Discounts
Automatic discounts for running instances for a significant portion of the month.
Committed Use Discounts
Save up to 57% with a 1-year or 3-year commitment to a minimum level of resource usage.
Preemptible VMs
Save up to 80% for fault-tolerant workloads that can be interrupted.
Getting Started
Amazon AWS
- 1
Sign up for AWS
Create an AWS account to access the cloud platform.
- 2
Choose a compute service
Select from EC2, Lambda, or container services based on your workload needs.
- 3
Launch an instance
Configure and launch your first compute instance or container.
- 4
Set up security
Configure security groups and access controls for your resources.
- 5
Monitor and optimize
Use AWS CloudWatch and Compute Optimizer to monitor performance and reduce costs.
Google Cloud
- 1
Create a Google Cloud project
Set up a project in the Google Cloud Console.
- 2
Enable billing
Set up a billing account to pay for resource usage.
- 3
Choose a compute service
Select Compute Engine, GKE, Cloud Functions, or Cloud Run based on your needs.
- 4
Create and configure an instance
Launch a VM instance, configure a Kubernetes cluster, or deploy a function/application.
- 5
Manage resources
Use the Cloud Console, command-line tools, or APIs to manage your resources.
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.
Google Cloud
Global Regions
35+ regions and 100+ zones worldwide.
Support
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.
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