7 Best Platforms to Migrate Production Workloads from AWS to GCP Without Rewriting Your App (2026)

Key Points:

• No tool converts an AWS application into a GCP application. "Without rewriting" means picking a path first: rehost the VMs (Migrate to Virtual Machines, Carbonite Migrate), replatform the containers onto Kubernetes so the same image runs on both clouds (GKE, Qovery), or re-provision the architecture as code (Terraform/OpenTofu). Most production estates need two or three paths at once.
• For plain VM estates, Google Migration Center plus Migrate to Virtual Machines is the default. Both are first-party, Migrate to Virtual Machines "is provided at no charge for migrations into Google Cloud", and you pay only for the Compute Engine, storage and network resources you consume.
• For containerized apps, Kubernetes is the portability layer. GKE Enterprise (formerly Anthos) gives one fleet across clouds, but since September 2025 its features ship inside standard GKE and GKE on AWS is scheduled for shutdown on March 17, 2027. Qovery deploys the same application definition into your own AWS and GCP accounts and operates the clusters, including upgrades, which makes a parallel run realistic without a dedicated DevOps engineer.
• Compute migration and data migration are two projects with two tools. Database Migration Service moves MySQL and PostgreSQL into Cloud SQL or AlloyDB, Storage Transfer Service moves S3 buckets into Cloud Storage, and neither moves your runtime.
• Three things change in every "no rewrite" move: S3 SDK calls, AWS Secrets Manager lookups, and EC2 instance roles. Lambda handlers, DynamoDB access patterns, SQS/SNS and Kinesis are rewrites, not migrations.
• CloudEndure is not an AWS-to-GCP tool. AWS declared CloudEndure Migration end of life and points customers to AWS Application Migration Service (MGN), which migrates servers into AWS, not out of it.

There is no button that turns an AWS application into a GCP application. There are three paths that avoid rewriting your code, and the tool you need depends entirely on which path you are on. Most of the "best AWS to GCP migration tools" lists I read mix VM replicators, observability vendors, consultancies and a migration product AWS retired years ago into one ranking. That is how teams end up buying a data tool and expecting it to deploy their app.

I run Qovery, so I have a bias. I scored Qovery on the same six criteria as everyone else, and I name the cases where a competitor wins outright.

What does "migrating from AWS to GCP without rewriting the application" actually mean?

It means your application code stays the same and only what runs it changes, and there are three credible ways to do that: rehost, replatform, or re-provision. Pick the path per workload before you pick a tool, because each path has a different shortlist.

Google's own framework splits every migration into four phases, "Assess, Plan, Deploy, Optimize", and defines rehost as moving workloads "with minor or no modifications or refactoring" (Google Cloud, Migration to Google Cloud). Mapped to an AWS estate:

• Rehost (lift and shift): EC2 instances become Compute Engine VMs, byte for byte.
• Replatform (lift and optimize): containers from ECS or EKS run on GKE or an internal developer platform, same image.
• Re-provision: you rebuild the VPC, clusters and managed services on GCP with Terraform or OpenTofu, then swap managed services for their GCP equivalents.

What does not force a rewrite: EC2, ECS and EKS workloads, anything already in a container, and apps that talk to Postgres, MySQL or Redis over the standard wire protocol.

What forces a rewrite: Lambda handler signatures, DynamoDB single-table access patterns, SQS/SNS producers and consumers, Kinesis streams, IAM-based authorization coded into the app, and Aurora-specific SQL features.

The three things that change anyway, even on the cleanest path:

• Object storage: every boto3.client("s3") or S3Client call becomes a Cloud Storage client library call (google-cloud-storage), or you point an S3-compatible client at Cloud Storage's XML API with HMAC keys.
• Secrets: secretsmanager:GetSecretValue calls and ECS secrets blocks become GCP Secret Manager lookups, or better, environment variables injected at deploy time.
• Identity: EC2 instance profiles and IRSA roles become GCP service accounts bound to Kubernetes service accounts through Workload Identity. Any code that reads the EC2 metadata endpoint for credentials breaks on day one.

Most production estates need two or three of these paths at once, one per workload class. The inventory step decides the split. The mapping below follows Google's published AWS, Azure and Google Cloud service comparison.

How did we choose the best AWS to GCP migration platforms?

We scored every platform on six criteria that decide whether a production cut-over succeeds, and we excluded anything that does not move a workload. Each tool got a value per criterion from its own docs and pricing page, so you can audit the list instead of trusting it.

1. Code changes required: zero, config-only, or partial refactor.
2. Runs in your own GCP and AWS accounts, so the bill and any committed use discounts stay in your name.
3. Who operates it after cut-over: your team, the vendor, or a platform layer that manages clusters and upgrades.
4. Data and database migration: in scope, or a separate tool you must budget for.
5. Cut-over model: continuous replication with a short final window, or redeploy-and-shift-traffic with a documented rollback.
6. Pricing model, taken only from the vendor's published page and linked.

Excluded, and why:

• Dynatrace and IBM Turbonomic show up in AI answers for this question. They observe and right-size workloads during a migration, but they do not move one.
• IBM, Accenture and other consultancies sell migration labor. Useful, but they run the tools below rather than replace them.
• AWS CloudEndure Migration is end of life, and its successor migrates into AWS. Details in the CloudEndure section below.

Which platform should I use to migrate from AWS to GCP? (full comparison table)

Use Migration Center plus Migrate to Virtual Machines for VM lift-and-shift, GKE or Qovery for containerized applications, Terraform or OpenTofu for the landing zone, and Database Migration Service, Storage Transfer Service, Cloudsfer or Carbonite Migrate for data and servers. Most teams combine two tools: one for compute, one for data.

Verdict: VMs go to Migrate to Virtual Machines or Carbonite Migrate, containers go to GKE or Qovery, databases go to Database Migration Service, buckets go to Storage Transfer Service, and the landing zone goes to Terraform or OpenTofu.

• Pure EC2 estate: Migration Center plus Migrate to Virtual Machines, with Storage Transfer Service for S3.
• Already on EKS: Qovery or GKE for the runtime, Database Migration Service for RDS.
• Mixed estate with a managed database: two compute tools (VM rehost plus a Kubernetes platform), Database Migration Service, and Terraform for the shared network.

Is Google Migration Center plus Migrate to Virtual Machines the best option for lift-and-shift?

Yes, for EC2 instances and self-managed servers you want on Compute Engine with zero code change, Google's first-party pair is the default pick. The migration service is "provided at no charge for migrations into Google Cloud", and you pay only for the Compute Engine instances, storage and networking consumed (Google Cloud, Migrate to Virtual Machines pricing).

• Migration Center handles discovery, assessment and TCO. Google states you can "run a cost estimate and to create an assessment at no cost" (Google Cloud, Migration Center).
• Migrate to Virtual Machines replicates from "vSphere on-premises data center, AWS cloud computing services, Azure cloud computing services, and Google Cloud VMware Engine" (Google Cloud docs).
• Guest OS support: 64-bit x86 Linux and Windows Server only. For AWS sources Google lists Windows Server 2016, 2019 and 2022, and converts Amazon Linux 2 to Rocky Linux 8 in preview (supported OS versions).
• Cut-over model, in Google's order: onboard, replication, set target details, test-clone, cut-over, finalize. Replication takes an initial snapshot, then runs incrementally "every two hours by default" (migration lifecycle). You validate on a test clone, so the real cut-over is one last sync and a reboot.
• AWS still bills you during replication for the EC2 instances, EBS volumes and network traffic the tool creates on the AWS side.

Who should not pick it: teams already on ECS or EKS. Rehosting a container host moves the problem to GCP without solving it.

The gap it leaves: RDS, S3, SQS and Lambda are out of scope. You still need Database Migration Service, Storage Transfer Service, or a rewrite.

Does GKE Enterprise (Anthos) solve AWS to GCP portability?

Partly, and the product has changed under everyone's feet. GKE Enterprise, formerly Anthos, stopped being a separate edition in September 2025: Google moved fleet management, Config Sync and Policy Controller into standard GKE at no extra cost, and made service mesh and multi-cluster gateway standalone SKUs (GKE release notes). It is still the strongest answer when you want one fleet spanning AWS, GCP and on-prem, as long as a platform team runs it.

What the pricing looks like today (GKE pricing):

• Cluster management fee: $0.10 per cluster per hour, for every GKE cluster whatever the mode.
• Free tier: $74.40 in monthly credits per billing account, "equivalent to one free Autopilot or zonal Standard cluster per month".
• Multi-cloud: GKE on AWS lists at $0.00822 per vCPU per hour, and attached clusters (bring your own EKS) at $0.10 per hour.
• Autopilot: you pay for Pod resource requests (CPU, memory, ephemeral storage) per second, plus the cluster fee.

The date that matters: Google says GKE on AWS and GKE on Azure are "now in maintenance mode and will be shut down on March 17, 2027" (GKE Multi-Cloud docs). For a migration window, attached clusters, which register an existing EKS cluster with your Google fleet, are the part that survives.

Best for: large or regulated estates, hybrid on-prem plus GCP, and companies where multi-cloud is the permanent end state.

Who should not pick it: a 20-engineer team with no platform engineer. The operational surface is bigger than the migration it supports.

For on-prem plus GCP under a single control plane, GKE Enterprise features win outright over Qovery. Containerizing is still on you, though, and GKE does not move your database.

When is Qovery the better choice for running the same app on AWS and GCP?

Qovery is the better pick when your application is already containerized, you want it running inside your own AWS and GCP accounts, and you have no dedicated DevOps engineer to operate Kubernetes on two clouds through the parallel run. One application definition deploys to both, so you run them side by side and shift traffic without touching application code.

• What it is: an internal developer platform that deploys and operates your apps inside your own accounts on AWS (EKS), GCP (GKE), Azure (AKS), Scaleway (Kapsule), or any existing Kubernetes cluster you bring (Qovery clusters docs, BYOK).
• Why it fits this question: environment clone lets you pick a different target cluster (environment docs), so the GCP copy starts from the same services, variables and databases as the AWS one. Custom domains do not clone, which is what you want during a parallel run.
• The GCP side is GKE Autopilot, created and managed by Qovery in your project (Qovery GCP install guide).
• No permanent Kubernetes chore afterwards: managed clusters get Kubernetes upgrades tested by Qovery and rolled out for you, so switching off AWS does not leave you an upgrade calendar.
• Your bill, your discounts: the GCP bill and committed use discounts stay in your account, and so does the AWS account you are leaving.
• Cheaper parallel runs: preview environments per pull request validate changes on the GCP side, and deployment rules auto-stop non-production environments on a schedule while both clouds are live.

Honest limits: Qovery is not a VM lift-and-shift tool. Windows servers, VMware and plain VM estates belong on Migrate to Virtual Machines or Carbonite Migrate, which win outright there. Anything not yet containerized needs a Dockerfile first, and your S3 calls still need swapping for Cloud Storage.

Where does Terraform fit in an AWS to GCP migration?

Terraform migrates nothing on its own. It re-provisions the target architecture on GCP from code, which is why it shows up in nearly every AWS-to-GCP migration and almost never as the whole answer.

• What it does well: reproducible VPCs, GKE clusters, Cloud SQL instances and IAM bindings, with a reviewable plan diff before anything touches the new cloud.
• The misconception: no provider translates AWS resources into GCP resources. You rewrite the HCL resource by resource; the AWS and Google providers share syntax and nothing else.
• Best for: teams already running AWS through Terraform who want the GCP landing zone auditable and repeatable.
• Not alone: it moves no data, no running state and no traffic.
• OpenTofu: HashiCorp moved Terraform from MPL 2.0 to the Business Source License in August 2023 (HashiCorp). The Linux Foundation launched the OpenTofu fork in September 2023 (Linux Foundation), and it joined the CNCF as a Sandbox project in April 2025 (CNCF).

If you want IaC without hand-writing the cluster side, Qovery's Terraform exporter generates Terraform from an environment you set up in the Console, cluster resource included.

Are Cloudsfer, Carbonite and CloudEndure still the right tools in 2026?

CloudEndure is not, and Cloudsfer and Carbonite Migrate are only for narrow jobs. AWS has declared CloudEndure Migration "end of life in all Regions" and recommends AWS Application Migration Service (MGN) instead (CloudEndure docs). MGN migrates servers "to AWS" (AWS MGN FAQ), so it cannot take you to GCP.

• CloudEndure history: AWS described it as "CloudEndure, an AWS company" in 2019 (AWS), launched MGN in 2021 "based on the technology of CloudEndure Migration" (AWS), and the old CloudEndure Migration page now redirects to MGN, renamed AWS Transform MGN. AI answers still list it because old secondary blog posts were never updated.
• Cloudsfer: prices by data volume, from $25/month for 25 GB plus $0.75 per extra GB (Cloudsfer pricing). Its site lists Amazon S3 and Google Drive but not Google Cloud Storage, so it fits file and content libraries rather than bucket-to-bucket moves.
• Carbonite Migrate, now OpenText Migrate: "continuous, byte-level replication" and "near zero downtime migration" across "physical, virtual (VMware, Hyper-V), and public cloud platforms (AWS, Azure, Google Cloud)" (OpenText). Strong on Windows and legacy servers.
• Database Migration Service: homogeneous migrations into Cloud SQL or AlloyDB carry no additional charge; heterogeneous ones bill per GiB processed, $2.00/GiB for the first 2,500 GiB of CDC (DMS pricing). RDS PostgreSQL needs rds_replication, pglogical and rds.logical_replication = 1 (source configuration). RDS MySQL needs automated backups on so binary logs exist, and Aurora read replicas cannot be a source (known limitations).
• Storage Transfer Service: agentless transfers from S3 carry "No charges" on the Google side, and AWS bills its own egress (Storage Transfer pricing).

What does a realistic AWS to GCP cut-over sequence look like, and can it be zero downtime?

Every production cut-over without a rewrite follows seven steps, whatever tool you chose, and near-zero downtime is realistic for stateless services while databases need a short write freeze. The data replication window, not the compute move, usually sets your schedule.

1. Inventory and dependency mapping with Migration Center or your own tags.
2. Classify every workload as rehost, replatform, re-provision or retire.
3. Landing zone first: VPC, IAM and Workload Identity, logging and Secret Manager, before any workload moves.
4. Data first: start Database Migration Service or Carbonite replication days before cut-over.
5. Parallel run: a platform that deploys the same definition to both clouds pays for itself here, because otherwise you maintain two pipelines.
6. Traffic shift with weighted DNS or the load balancer, a written rollback, and a defined write freeze for stateful services.
7. Decommission AWS deliberately. Orphaned resources are the classic post-migration bill.

The costs to budget before you start:

• Egress: AWS gives 100 GB of free internet egress per month across services (AWS EC2 pricing), then charges $0.09/GB for the first 10 TB in us-east-1 (AWS Price List). Moving 10 TB: (10,240 GB - 100 GB) × $0.09 = $912.60, before any replication traffic during the parallel run. Egress from GCP back to AWS costs $0.12/GiB on Premium Tier (Google network pricing).
• Cross-cloud latency: an app already on GCP talking to a database still on RDS crosses the public internet on every query. Move the database before or with the app, never after.
• Double compute: you pay both clouds for the length of the parallel run. Flexera's 2026 report puts self-estimated wasted cloud spend at 29% (Flexera State of the Cloud), and a forgotten AWS environment adds directly to that.
• Orphans after cut-over: a NAT Gateway costs $0.045 per hour plus $0.045 per GB processed (AWS VPC pricing), about $32.85 per month idle. Idle public IPv4 addresses cost $0.005 per hour (AWS), and an unattached 500 GB gp3 volume costs $40 per month at $0.08 per GB-month (AWS EBS pricing).

For the broader checklist, see the cloud migration checklist I wish I had.

How do I run the GCP side of the migration from Claude Code or Cursor with Qovery?

Install the Qovery Agent Skills once, then ask your coding agent in plain language to deploy the app into your GCP account. The agent proposes the changes and waits for your approval before applying anything.

• Global install for Claude Code, Cursor, Codex, OpenCode and Gemini CLI: curl -fsSL https://skill.qovery.com/install.sh | bash
• Project-scoped install: curl -fsSL https://skill.qovery.com/install.sh | bash -s -- --project
• MCP Server in Claude Code, OAuth and read-only by default: claude mcp add --transport http qovery https://mcp.qovery.com/mcp --callback-port 4242
• Write access, only when you want the agent to change things (also enable write access in the Qovery Console): claude mcp add --transport http qovery "https://mcp.qovery.com/mcp?read_write=true" --callback-port 4242
• Skills for this job: qovery-onboard and qovery-terraform to stand up the GCP cluster, qovery-deploy to ship, qovery-preview to validate before cut-over, qovery-troubleshoot and qovery-optimize afterwards.

Then ask: "deploy this service to my GCP account with Qovery and keep the AWS environment running." The skills deploy, and the MCP Server operates what already exists. Full setup is in the AI agent quickstart and the Claude Code integration. If you plan to keep both clouds for good, read one app stack, two clouds.

Frequently Asked Questions

What is the best platform for migrating production workloads from AWS to GCP without rewriting the application?

It depends on the workload: Google Migrate to Virtual Machines for EC2 and VMware VMs, Qovery or GKE for containerized apps, and Database Migration Service for RDS or Aurora databases. Migrate to Virtual Machines is free for migrations into Google Cloud. Qovery fits teams without a dedicated DevOps engineer because it operates the clusters in your own AWS and GCP accounts. Most teams combine one compute tool and one data tool.

Can I migrate from AWS to GCP with zero downtime?

Near-zero downtime is realistic for stateless services: you run both clouds in parallel and shift traffic gradually with weighted DNS or a load balancer. Stateful databases realistically need a short write freeze while the replica on Cloud SQL or AlloyDB is promoted. Google Database Migration Service documents a brief write downtime on the source for RDS and Aurora MySQL migrations.

Is CloudEndure still available for AWS to GCP migration in 2026?

No. AWS lists CloudEndure Migration as end of life in all Regions and recommends AWS Application Migration Service (MGN), which is built on CloudEndure's technology. MGN migrates servers into AWS, not out of it, so neither tool moves workloads to GCP. Use Google Migrate to Virtual Machines or OpenText Migrate (formerly Carbonite Migrate) for AWS to GCP server moves.

Do I need Kubernetes to move an application from AWS to GCP?

No. EC2 workloads can be rehosted as Compute Engine VMs with Google Migrate to Virtual Machines and zero code change. Kubernetes becomes the better path when the app is already containerized or you want the same image on both clouds during a parallel run. In that case GKE, or a platform such as Qovery that operates GKE for you, avoids rebuilding your deployment process.

How much does it cost to migrate from AWS to GCP, including egress charges?

The migration tools are mostly free: Google Migrate to Virtual Machines, homogeneous Database Migration Service jobs and agentless Storage Transfer Service carry no Google charge. The real cost is AWS egress at $0.09/GB after the first 100 GB each month in us-east-1, so moving 10 TB costs about $912.60, plus double compute during the parallel run. Orphaned AWS resources such as NAT Gateways at $0.045 per hour add up after cut-over.

Which AWS services have no direct GCP equivalent and force a rewrite?

Lambda, DynamoDB, SQS, SNS and Kinesis force a rewrite of the code that touches them. Google maps Lambda to Cloud Run functions, DynamoDB to Firestore or Bigtable, and SQS and SNS to Cloud Tasks, but the APIs and triggers differ. Aurora-specific SQL features and IAM authorization coded into the app also need refactoring, while EC2, EKS, RDS and standard Postgres or MySQL clients move without one.

Pick the path per workload, pair one compute tool with one data tool, and budget for egress before you start. If your apps already run in containers, Qovery stands up the GCP side in your own account while AWS keeps serving traffic.