Google Compute Engine vs Amazon EC2
Compare Google Compute Engine vs Amazon EC2 for virtual machines, deployment and operating costs. Review the deployment model, migration work and proposed acceptance checks.
Which option fits the workload?
Consider Google Compute Engine when the workload belongs in Google Cloud and needs configurable virtual-machine instances. Consider Amazon EC2 when the workload belongs in AWS and needs EC2 instance and networking options. Validate the required configuration and operating responsibilities before comparing costs.
Seven differences that change the shortlist
| Buying question | Google Compute Engine | Amazon EC2 |
|---|---|---|
| Infrastructure provider | Google Cloud | AWS |
| Core resource | Compute Engine VM instance | EC2 instance |
| Reusable deployment | Instance templates and managed instance groups | Amazon Machine Images and launch templates |
| Block storage | Persistent Disk or Hyperdisk, subject to configuration | Amazon EBS, subject to configuration |
| Access model | Google Cloud IAM and service accounts | AWS IAM roles and policies |
| Network boundary | Google Cloud VPC | Amazon VPC |
| Cost exercise | Selected machine, disks, runtime and data transfer | Selected instance, EBS, runtime and data transfer |
Four worked buying briefs
These are hypothetical scenarios with explicit assumptions. They do not establish equal capabilities, measured usability or a negotiated price.
| Requirement | Proposed exercise | Accept when |
|---|---|---|
| Image boot | Boot the approved operating-system image and application. | The application starts without manual configuration changes. |
| Private access | Connect the application to its database over the intended private network. | Only approved network paths and identities can connect. |
| Recovery | Recreate an instance from the retained image and configuration. | The documented recovery procedure restores the service. |
| Cost model | Price the same runtime, disk and outbound-traffic assumptions. | Both estimates show the complete billable resource scope. |
Image boot
Can the team boot the approved operating-system image and application?
Google Compute Engine: Using Google Compute Engine, boot the approved operating-system image and application.
Amazon EC2: Using Amazon EC2, boot the approved operating-system image and application.
The application starts without manual configuration changes.
Private access
Can the team connect the application to its database over the intended private network?
Google Compute Engine: Using Google Compute Engine, connect the application to its database over the intended private network.
Amazon EC2: Using Amazon EC2, connect the application to its database over the intended private network.
Only approved network paths and identities can connect.
Recovery
Can the team recreate an instance from the retained image and configuration?
Google Compute Engine: Using Google Compute Engine, recreate an instance from the retained image and configuration.
Amazon EC2: Using Amazon EC2, recreate an instance from the retained image and configuration.
The documented recovery procedure restores the service.
Cost model
Can the team price the same runtime, disk and outbound-traffic assumptions?
Google Compute Engine: Using Google Compute Engine, price the same runtime, disk and outbound-traffic assumptions.
Amazon EC2: Using Amazon EC2, price the same runtime, disk and outbound-traffic assumptions.
Both estimates show the complete billable resource scope.
Architecture and application fit
Both services provide virtual machines. The useful comparison starts with the operating system, CPU architecture, memory, accelerator requirements and network access your application actually needs. Compare available machine configurations in the intended region rather than matching marketing family names.
Compute Engine uses Google's project and VPC model; EC2 runs inside the AWS account and VPC model. Existing permissions, image pipelines, monitoring and operations skills can matter more than a small difference in the hourly compute line.
Google Compute Engine product documentation ↗ · Amazon EC2 product information ↗
Cost and migration planning
Build a cost model with the same runtime, storage capacity, resilience arrangement and outbound traffic. A VM quote without its disks, snapshots, load balancing and network traffic is incomplete.
A machine image is not automatically portable between clouds. Test image conversion, startup configuration, credentials, application dependencies and rollback before treating a migration as a simple instance replacement.
Questions before you choose
When should I choose Google Compute Engine over Amazon EC2?
Consider Google Compute Engine when the workload belongs in Google Cloud and needs configurable virtual-machine instances. Consider Amazon EC2 when the workload belongs in AWS and needs EC2 instance and networking options. Validate the required configuration and operating responsibilities before comparing costs.
What should we include in the cost comparison?
Build a cost model with the same runtime, storage capacity, resilience arrangement and outbound traffic. A VM quote without its disks, snapshots, load balancing and network traffic is incomplete.
What should we test before a production migration?
A machine image is not automatically portable between clouds. Test image conversion, startup configuration, credentials, application dependencies and rollback before treating a migration as a simple instance replacement.
Turn the comparison into your own evaluation
Use the same criteria and priorities for both products, keep unknowns unassessed and record the plan and evidence behind your ratings.
Build a Google Compute Engine vs Amazon EC2 scorecard →Keep the assumptions with the figures
Use the date, billing cycle, units and limits with each example. Check current account terms before purchasing. Unverified prices and model costs stay unpriced.
Download the buying examples as JSON ↓Share the comparison
Use these examples when discussing the shortlist with your team.