How Do I Migrate My GCP Instance to AWS?

You can use the AWS Application Migration Service, which provides a highly automated lift-and-shift approach to migrate virtual machines from GCP to AWS.

Why Move From GCP to AWS?

AWS offers broader service offerings, including AWS Outposts, and has enhanced scalability, a more robust global infrastructure and a more extensive partner network.

Can GCP Connect to AWS?

Yes. GCP can connect to AWS through direct peering, VPN connections or third-party cloud interconnectivity tools.

How to Migrate From GCP to AWS: GCP to AWS Migration Guide

A GCP to AWS migration is a complex process that requires keen care to ensure compatibility, data integrity and minimal disruption to ongoing operations.

Written by Kevin Kiruri (Writer)

Reviewed by Aleksander Hougen (Co-Chief Editor)

Last Updated: 05 Apr'25

All our content is written fully by humans; we do not publish AI writing. Learn more here.

A GCP to AWS migration is a multi-step process. To ensure a seamless transition, you must assess your current GCP environment and plan your AWS architecture, data migration, application migration, testing and validation, and cutover and optimization; decommission the GCP resources; and finally, perform continuous monitoring and support.

Step 1: Evaluate your GCP environment to determine your AWS cloud readiness and design your target AWS architecture.
Step 2: Choose a data migration strategy and tools.
Step 3: Refactor or replatform your applications for AWS compatibility.
Step 4: Test your migrated applications and data in the AWS environment for functionality and performance.
Step 5: Switch traffic to the AWS environment, monitor for issues and optimize for performance and cost.
Step 6: Decommission your GCP resources to avoid unnecessary costs.
Step 7. Continuously monitor the AWS environment for any issues.

Meet the experts

Kevin Kiruri (Writer)

Kevin Kiruri is an experienced AWS Cloud Solutions Architect and writer specializing in cloud computing. With a background in DevOps engineering, cloud consulting and AWS instruction, Kevin brings a deep understanding of cloud infrastructure to his articles. His expertise, coupled with a passion for sharing knowledge, makes his writing on cloud technologies insightful and accessible. Kevin’s interests outside of work include bowling, traveling, socializing and driving.

More about Kevin Kiruri

Aleksander Hougen (Co-Chief Editor)

Aleksander Hougen, the co-chief editor at Cloudwards, is a seasoned expert in cloud storage, digital security and VPNs, with an educational background in software engineering. Beyond his prolific writing commitment, Aleksander helps with managing the website, keeping it running smoothly at all times. He also leads the video production team and helps craft e-courses on online technology topics. Outside of the professional realm, he is a digital nomad with a passion for traveling, having lived in many countries across four continents.

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Learn more about our editorial team and our research process.

Overview of Steps to Migrate from GCP to AWS

We will go over each of these steps in more detail below, but here is an overview of the migration strategy, going from Google Cloud to AWS.

Assessment and planning: Evaluate your current GCP environment. Design your target AWS architecture to select the AWS services that align with the application needs to determine your cloud readiness. Create a detailed migration plan, including the migration timeline, resource utilization and potential risks.
Data migration: Choose a suitable data migration strategy and tools based on the volume, operating systems and sensitivity of your data.
Application migration: Refactor or replatform your applications to ensure compatibility with AWS services.
Testing and validation: Thoroughly test your migrated applications and data in the AWS environment to ensure functionality and optimal performance.
Cutover and optimization: Switch traffic to the new AWS environment. Monitor the AWS environment closely for any issues and optimize for performance and cost efficiency.
Decommissioning GCP resources: Once you have fully migrated to AWS, decommission your GCP resources to avoid unnecessary costs.
Continuous monitoring and support: The new AWS environment should be continuously monitored to address any issues that may arise.

Step 1: Assessment & Planning

Assessment and planning involve carrying out a detailed inventory analysis of your GCP infrastructure and designing the target AWS infrastructure. The goal is to identify all the resources and dependencies, understand application workloads and choose the appropriate AWS resources to align with your needs.

To help with assessing resource inventory, you will need services such as:

The AWS Application Discovery Service
The Google Cloud Asset Inventory.

The AWS Well-Architected Tool can help design the AWS infrastructure under the well-architected framework. A project management tool such as ClickUp would be helpful for planning and tracking migration tasks.

Consider keeping a thorough inventory of all resources to avoid missing any critical dependencies. Conducting a perfect assessment of the resources and dependencies — and designing the AWS infrastructure using the well-architected framework — ensures a structured and organized migration, optimizes resource allocation on AWS and minimizes disruptions.

Some of the associated risks include unforeseen costs, application downtime, security vulnerabilities, misaligned architecture, application incompatibility and performance bottlenecks.

Step 2: Data Migration

Data migration involves transferring databases and storage from GCP to AWS while ensuring data integrity and security. Select a suitable data movement strategy and tools based on the volume and sensitivity of the data.

Services and tools you could use include:

AWS Direct Connect
AWS DataSync
AWS Snow Family
Data backup and recovery tools

Use an appropriate migration tool based on your data volume and network bandwidth, ensure data encryption during the transfer of sensitive data and validate the data through data integrity checks after the transfer to avoid data corruption issues.

A properly executed data migration ensures business continuity, minimizes downtime and data loss, preserves data integrity and ensures seamless application functionality.

Some of the risks associated with data migration include data corruption, application errors and data inconsistency due to incomplete data transfer, and data breaches due to inadequate data security.

Step 3: Application Migration

Application migration entails refactoring or replatforming to ensure compatibility with AWS services, such as modifying code, configurations or infrastructure to leverage AWS-specific features.

Tools and services to use include:

AWS Application Migration Service
AWS Elastic Beanstalk
CI/CD tools like Jenkins to manage app changes
Code repositories like GitHub

Consider ensuring compatibility with AWS services and testing the changes in a staging environment before deploying to a production environment. Avoid hardcoding dependencies on the application code.

Correctly refactoring the application ensures that it functions correctly on AWS, minimizes downtime, helps reduce operational costs and improves maintainability.

Incorrect refactoring may lead to application failures, bugs and security vulnerabilities, application performance degradation and production errors.

Step 4: Testing & Validation

Testing and validation involve testing the migrated application’s functionality and performance to ensure everything works as expected in the new environment.

Prerequisites and required tools include:

AWS CloudWatch
AWS X-Ray
Third-party performance testing tools
Automated testing frameworks

Ensure thorough test coverage to identify potential issues, conduct performance and load testing, and make sure all validation steps are performed. Proper testing identifies and resolves issues before they impact end users, ensures performance and functionality requirements are met, and reduces post-migration disruptions.

Failure to run appropriate and complete testing and validation procedures could lead to application failures, poor user experience, user dissatisfaction and undetected security vulnerabilities that pose a risk to data and operations.

Step 5: Cutover & Optimization

Cutover and optimization involve redirecting live traffic to the new AWS environment and closely monitoring it for issues, as well as optimizing performance and cost efficiency.

Prerequisites include properly tested and validated applications and data in the AWS environment. Required tools include:

Load balancers
Routers
Traffic management tools
DNS management tools

This step involves gradually switching traffic to the new AWS environment to minimize downtime and ensure a smooth transition. The cutover should be completed during low-traffic periods as you closely monitor the new environment to detect and resolve any issues that may arise.

A successful cutover and optimization procedure ensures a smooth transition with minimal downtime, continuous monitoring for prompt issue resolution and reduced costs.

Poor cutover and optimization risks unplanned downtime, undetected issues and higher operational costs due to lack of optimization.

Step 6: Decommissioning GCP Resources

Decommissioning means pulling down infrastructure. Once the migration is complete and the AWS environment is stable, decommission the GCP resources to avoid extra costs.

This phase requires:

Access to your GCP account
An inventory of all GCP resources to ensure nothing is overlooked
A backup and data retention policy to ensure data is securely archived

You will need to confirm that all critical data and applications are successfully migrated before decommissioning, and ensure backups are completed to cater to any data that may be needed in the future. Do not rush the decommissioning process or you could end up with data loss.

Proper decommissioning eliminates redundant infrastructure, reduces costs and ensures all resources are accounted for, preventing security vulnerabilities.

The risks involved in decommissioning GCP resources include accidental deletion of data and overlooked resources that may lead to ongoing unnecessary costs.

Step 7: Continuous Monitoring & Support

Continuous monitoring and support is the ongoing process of keeping an eye on the health, performance and security of an IT environment.

This involves monitoring tools such as:

AWS CloudWatch
AWS X-Ray
Logging services like AWS CloudTrail
Security services and tools such as AWS GuardDuty
Security groups and incident management tools like ClickUp

Make sure you have comprehensive monitoring coverage for all critical resources and applications. Regularly review and update monitoring configurations to align with the application performance metrics and infrastructure needs, and avoid setting up too many alerts. You can set up automated monitoring with serverless services such as AWS Lambda.

Continuous monitoring provides real-time insights into the AWS environment’s health and performance for proactive issue resolution. Ongoing support ensures issues are quickly addressed, minimizing downtime and maintaining business continuity.

Insufficient monitoring can result in undetected issues, and delayed responses could lead to customer dissatisfaction.

What Are the Different Cloud Migration Strategies to Consider for GCP to AWS Migration?

There are five cloud migration strategies to consider for GCP to AWS migration, including rehosting, replatforming, refactoring, repurchasing and retiring. Each strategy has its own benefits and considerations depending on the specific needs, goals and constraints of your organization.

Strategy 1: Rehosting (Lift & Shift)

Rehosting involves moving applications from GCP to AWS without making any significant changes to the architecture or code.

The rehosting steps include:

Assessment
Replication
Testing and validation
Cutover

This strategy is beneficial because it is quick and straightforward, requiring minimal changes, lower upfront costs and less effort.

However, the rehosting strategy may not optimize for AWS features or cost efficiency, and it may not be suitable for complex applications. Use cases include organizations with tight timelines, applications with minimal dependencies and interconnections, and non-critical applications that don’t require optimization.

Strategy 2: Replatforming (Lift, Tinker & Shift)

Replatforming involves making minor modifications to applications to leverage AWS-specific services while maintaining the core architecture.

Replatforming steps include:

Assessment
Modifying code and applications
Testing
Deployment

This strategy offers improved performance, scalability and cost optimization, and leverages AWS-native features.

Replatforming may require more effort than rehosting, as it involves code changes and testing. Moreover, the process takes longer than rehosting and may not fully optimize the application for AWS. Use cases include organizations seeking a balance between speed and optimization, semi-complex workloads and applications that can benefit from specific AWS services.

Strategy 3: Refactoring (Rearchitecting)

Refactoring involves redesigning your application to fully leverage cloud-native AWS features.

The refactoring steps include:

Architecture redesign
Code development
Testing
Deployment

This strategy helps achieve maximum agility, scalability and resilience from the infrastructure; leads to significant long-term cost savings; and takes full advantage of AWS capabilities.

However, refactoring entails high upfront costs and requires significant time, effort and resources. This strategy is suitable for mission-critical workloads requiring high scalability and performance, organizations committed to a long-term AWS cloud strategy, organizations aiming to maximize AWS cloud benefits and applications that need major improvements.

Strategy 4: Repurchasing (Drop & Shop)

Repurchasing involves moving to a different product that provides the same functionality. If a service on AWS serves the purpose of the application, you may choose to drop the current solution and start using the AWS solution.

The repurchasing steps include:

Assessment and planning
Configure AWS accounts and services
Data migration
Testing
Deployment

This strategy helps you leverage AWS-enhanced capabilities and reduces the operational burden, especially if it makes use of managed services.

Drawbacks of repurchasing are the learning curve involved with new AWS services and tools, complex data and application migration, potential downtime and vendor lock-in. Repurchasing is best for applications with readily available SaaS alternatives, organizations aiming to reduce infrastructure management and businesses seeking new features and capabilities.

Strategy 5: Retiring

Retiring involves identifying and decommissioning applications or systems that are no longer essential for business operations.

The retiring steps include:

Assessment and planning
Data archival
Decommissioning
Validation
Documentation and reporting

This strategy aims to eliminate obsolete resources, simplify the IT environment and maintain only essential systems. It helps organizations reduce costs and environment complexity, focus on their core applications and reduce the security attack surface.

Retiring may cause data loss and user disruption if the proper evaluation and decommissioning procedures are not followed. Good use cases for retiring include legacy systems that have been replaced by newer systems, redundant applications, low-usage systems with no strategic importance and high-cost applications with a low return on investment.

What Are the Best Cloud Migration Services for GCP to AWS Migration?

AWS cloud migrations can be complex and require careful planning, execution and monitoring. Fortunately, cloud migration services can help streamline the process. Cloud migration services for GCP to AWS include AWS migration services, CloudZero, Corent MaaS, Striim, Carbonite Migrate and Cloudsfer.

AWS migration services: These include native AWS tools and services used for planning and migration. Examples of AWS migration services are AWS Application Migration Service, AWS Database Migration Service and the AWS Migration Hub.

AWS Application Migration Service: This service provides automated server replication, testing and cutover capabilities. The pricing is based on the number of server instances deployed and the replication duration.

AWS Database Migration Service: This service helps migrate databases from GCP to AWS with minimal downtime. It supports a range of database engines, including MySQL, PostgreSQL, Oracle and SQL Server. It uses a pay-as-you-go model, charging based on the source database size and instance hours used.
Image Name: aws_dms

AWS Migration Hub: This service helps monitor the migration status across your portfolio and provides a unified view to efficiently manage the process. It is a free service, but the underlying migration services may incur costs.

CloudZero: This service provides cloud cost management and optimization for AWS environments. It helps organizations manage and optimize their cloud spending during and after migration. It uses custom pricing based on usage and organization size.

Corent MaaS: This service enables the migration of SaaS applications to AWS virtual private clouds and facilitates application management while optimizing them for cloud performance and cost. It implements custom pricing based on the complexity and requirements.

Striim: This service enables real-time data integration and migration with continuous replication and can efficiently transfer data from GCP to AWS virtual private clouds. Striim offers a subscription-based model, with the cost depending on the volume of data processed, the number of connectors used and the specific deployment requirements.

Carbonite Migrate: This service enables the transfer of workloads with minimal disruption, supports various source and target environments, and can migrate data from GCP to AWS. It is subscription-based, with the price varying by deployment size and complexity.

Cloudsfer: This service specializes in cloud-to-cloud migration for files and documents. It facilitates the migration of data from various cloud storage services to AWS. Cloudsfer uses a subscription model, with an additional pay-as-you-go model based on the amount of data transferred beyond the subscription provision.

What Are the Different Challenges of the GCP to AWS Migration Process?

The challenges of GCP to AWS migration include architectural disparities, service compatibility, operational differences, security and compliance, and cost management. Migrating from Google Cloud Platform (GCP) to Amazon Web Services (AWS) can be complex. Both offer robust cloud computing solutions, but they have distinct architectures, services and operational models.

Architectural disparities: GCP and AWS have different underlying architectures. Applications designed for GCP’s architecture might require significant refactoring or redesign to run optimally on AWS. This could lead to increased development time and potential disruptions to application functionality.
Service compatibility: Both AWS and GCP offer a wide array of services, but they are often not directly compatible. Applications relying heavily on GCP-specific services might need code modifications or alternative solutions to work seamlessly on AWS. This could introduce compatibility issues and requires thorough testing.
Operational differences: Both platforms have different management consoles, monitoring tools and operational practices. Teams used to GCP’s workflows may need to adjust to AWS. The learning curve for new operational tools and processes could slow down migrations and lead to errors if not addressed through training and documentation.
Security and compliance: Security configurations, access controls and compliance requirements may differ. Data security and adherence to regulations during and after migration are paramount. Overlooking security considerations could expose data to vulnerabilities. Compliance issues could lead to legal repercussions if not addressed.
Cost management: Each cloud provider has varying pricing models and resource optimization strategies. It’s essential to understand how costs will change when migrating from GCP to AWS. Without proper cost estimation and optimization, migrating to AWS could lead to unexpected expenses.

What Are the Benefits of Migrating to AWS From GCP?

The benefits of migrating to Amazon Web Services from GCP include enhanced scalability, cost-effectiveness, comprehensive service offerings, better global reach and an extensive partner network. Migrating to AWS from GCP offers numerous benefits and can significantly impact an organization’s efficiency, scalability and overall cost-effectiveness.

Enhanced scalability: AWS offers a highly scalable infrastructure that can easily adapt to varying workloads and business needs. It has a wider range of scaling options, including auto-scaling and load balancing, enabling seamless adaptation to fluctuating workloads. This enhances organizational compliance with service-level agreements.
Cost-effectiveness: AWS offers a variety of pricing options, including on-demand reserved instances and spot instances, allowing businesses to optimize costs based on their usage patterns.
Comprehensive service offerings: AWS has a wider range of cloud services and features to meet diverse business needs. Its comprehensive portfolio of services — including compute, storage, databases, analytics, machine learning and more — provide greater flexibility and more options.
Better global reach: AWS has a more extensive global infrastructure, with data centers in more regions than GCP. This ensures better performance and availability for a wider audience.
Extensive partner network: AWS has a broad ecosystem of partners and a large community offering support, resources and expertise. The AWS Partner Network (APN) includes consulting and technology partners who offer solutions, integrations and expertise to help businesses optimize their AWS environment.

What Are the Differences Between AWS and GCP?

A key difference between GCP and AWS is the cost structure. AWS has a complex pricing structure, with pricing models such as on-demand, reserved and spot instances. AWS provides tools such as AWS Cost Explorer and AWS Budgets to help users manage spending. GCP has more straightforward and customer-friendly pricing, making it attractive for startups.

Integration with other services and the developer experience differ for GCP and AWS. AWS has a wider range of integrations and partnerships, making it versatile and adaptable to business needs. GCP is not as extensive as AWS but offers seamless integration with other Google services, enhancing productivity and collaboration for businesses in the Google ecosystem.

Launched in 2006, AWS is the oldest and most popular cloud computing platform. It offers a broader range of services and tools in compute, storage, databases and more. It has a wider global reach, with data centers spanning more regions than GCP. GCP was launched in 2008 and is known for its strength in data analytics and machine learning.

Which Is Better, GCP or AWS?

Both GCP and AWS are top-tier cloud providers. However, AWS generally stands out as the better option due to its maturity, extensive service offerings and widespread adoption. AWS has been on the market longer, so it has a more robust and comprehensive set of services, along with a larger global infrastructure.

GCP may be a better option in certain instances. For companies that are heavily reliant on big data and machine learning, GCP offers unique advantages, with its cutting-edge AI and data analytics tools such as BigQuery and TensorFlow. Additionally, GCP’s pricing model can sometimes be more budget-friendly than AWS’.

Ultimately, deciding which platform is best for you entails conducting a careful evaluation of your individual requirements and making a comparison of the specific services each platform offers. They both offer solid cloud infrastructure solutions for business needs.

How to Migrate from AWS to GCP

The steps to migrate from AWS to GCP include:

Infrastructure assessment
Migration planning
Data migration
Application migration
Testing and validation
Post-migration optimization

Migrating from AWS to GCP involves following a structured process to ensure a smooth transition. You first must thoroughly assess your existing AWS infrastructure, including applications, databases, storage and network configurations. This allows you to develop a comprehensive migration plan and a clear roadmap for the transition.

The next step is data migration. Select the appropriate tools and services to securely transfer data from AWS storage services to the equivalent GCP services. The data migration must ensure data integrity and consistency. You can leverage techniques such as custom data transfer scripts, Google cloud migration tools like GCP’s Storage Transfer service and physical data transfer appliances.

Finally, migrate your applications, which may involve rehosting, refactoring or rearchitecting. Throughout the process, you must continuously carry out testing and validation procedures to identify and resolve issues before fully committing to the new GCP environment. Post-migration optimization will help refine the setup and maximize the benefits of GCP’s features and services.

Final Thoughts

Migrating from GCP to AWS is a technical process that should be done with the utmost care and precision to ensure the organization’s migration is successful. AWS offers a wider range of cloud services and tools, which makes it a more diverse cloud solution compared to GCP. By following the steps above, you will minimize disruption and have a smooth transition.

Thank you for taking the time to read our article. We’d love to hear about your own migration experience. Was this article helpful for your GCP to AWS cloud migration journey? What else would you like to see from us? Please share your experiences, questions or suggestions in the comments below.

FAQ: Google Cloud Platform to AWS Migration Process

You can use the AWS Application Migration Service, which provides a highly automated lift-and-shift approach to migrate virtual machines from GCP to AWS.
AWS offers broader service offerings, including AWS Outposts, and has enhanced scalability, a more robust global infrastructure and a more extensive partner network.
Yes. GCP can connect to AWS through direct peering, VPN connections or third-party cloud interconnectivity tools.