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Google Cloud Modernize is a portfolio announced on October 6, 2026, that groups Google’s infrastructure assessment, platform modernization, and application modernization tools, adding AI-assisted workflows for tasks such as estimating migration costs, analyzing legacy code, and moving Kubernetes workloads from AWS EKS to Google Kubernetes Engine (GKE). The EKS-to-GKE migration agent is in public preview—not generally available—while Migration Center’s Agentic Quick Estimator is generally available. The announcement’s performance and customer results are Google-reported claims, not independent benchmarks.
What is Google Cloud Modernize?
Google describes Google Cloud Modernize as an enterprise transformation portfolio, rather than one standalone migration product. It brings together existing services—including Migration Center, Google Cloud VMware Engine, and Google Cloud Mainframe Modernization—with the new EKS-to-GKE Migration Agent and a new in-console Modernization Hub. The tools address infrastructure assessment, platform modernization, and application modernization. Google’s October 6, 2026 announcement is the source for the scope and product claims below.
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The practical idea is to connect assessment and migration tasks with modernization workflows that use Gemini. That does not mean every step is autonomous: Google describes approval gates for the EKS migration agent, and the announcement does not establish that the portfolio can modernize every application without engineering or operational review.
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Agentic Quick Estimator for infrastructure planning
Migration Center’s Agentic Quick Estimator is labeled generally available. Google says it can use VMware inventory exports, including RVTools, alongside infrastructure inputs to produce total-cost-of-ownership projections for Compute Engine. Teams can use its interactive chat to model assumptions such as multi-region deployments and bring-your-own-license (BYOL) versus pay-as-you-go licensing.
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Google says the estimator can reduce weeks of spreadsheet modeling to minutes; that is the company’s time-saving claim, not an independently measured result. Google also says its Rapid Migration & Modernization Program (RaMP) provides a no-cost comprehensive modernization assessment. The announcement does not detail eligibility, terms, or the estimator’s pricing beyond those statements.
EKS-to-GKE Agentic Migration
Google labels the EKS-to-GKE Agentic Migration tool a public preview. It is intended to help move workloads from Amazon Elastic Kubernetes Service (EKS) to Google Kubernetes Engine (GKE). Google says it automates discovery, Kubernetes manifest translation, and storage and network mapping across clouds. Human-in-the-loop approval gates and in-memory credential security are described as safeguards.
So, can Google migrate workloads from AWS EKS to GKE? The announced agent is designed to assist with that path, but public preview is not the same as general availability or a guarantee that a particular cluster will migrate without changes. The announcement does not give a compatibility matrix, supported workload limits, migration pricing, or a detailed cutover procedure.
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Modernization Hub and CodMod
Modernization Hub is a newly launched in-console experience for developers and architects. Google says it supports analysis of Java, .NET, and mainframe applications, including source-code analysis and dependency mapping. The announcement does not assign it a separate GA or preview label.
The Hub integrates Google’s App Modernization CLI (CodMod), which Google says uses Gemini to analyze large code repositories, map dependencies, identify modernization challenges, and generate recommendations. One example is moving legacy .NET Framework applications to modern .NET Core on Linux containers. Google presents this as a route to reduce operating-system licensing overhead and make applications and data more accessible to AI-agent workflows; actual savings and suitability depend on the application and its operating requirements.
What platform modernization options are included?
Google’s announcement also describes compute products for enterprise workloads, with availability and specifications that differ by product:
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| Offering | Availability in the October 6, 2026 announcement | Google’s stated details |
|---|---|---|
| X5 Series for SAP S/4HANA | Generally available | Single-node configurations with 43 TiB of memory, compared with a previous 29 TiB ceiling, according to Google. |
| M4N Series | Generally available | 26.57 GiB RAM per vCPU with Hyperdisk Extreme. Google says this may reduce software licensing costs by more than 20% for Oracle and other core-licensed databases. |
| Z4D | Generally available | Up to 84,000 GiB of high-speed local NVMe SSD and 400 Gbps networking, according to Google. |
| Z4M | Preview | Up to 168,000 GiB of high-speed local NVMe SSD and 400 Gbps networking; Google also lists RDMA support. |
These capacities, networking figures, and potential licensing savings are Google-published product claims, not independent performance tests or guaranteed customer outcomes. The announcement does not provide comparable third-party benchmarks.
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For organizations that want to keep VMware rather than immediately re-architect workloads, Google describes a self-managed VMware option on Bare Metal Z3 shapes with VMware Cloud Foundation 9.1. Google says native global VPC links connect VMware estates with Compute Engine, GKE, BigQuery, and Gemini Enterprise. The announcement does not provide pricing or a detailed comparison with other VMware hosting options.
How does Google approach mainframe modernization?
Google describes three components for mainframe projects, each covering a different stage of the work:
- Mainframe Assessment Tool: Parses code, extracts business rules, maps dependencies, and produces target specifications.
- Dual Run: Replays production transaction streams across old and new applications to check functional equivalence before cutover.
- Mainframe Connector: Moves mainframe data into Google Cloud services such as BigQuery, AlloyDB, and Cloud Storage.
Dual Run is meant to provide evidence that a replacement behaves as expected before a full transition; it is not, by itself, proof that every operational or regulatory requirement has been met. In the announcement, Intesa Sanpaolo’s Head of IT Architecture, Claudio Balbo, said the bank needs confidence for leadership, internal control units, and regulators, and described Dual Run as gradually providing evidence for those groups. That is the customer’s perspective, not a general regulatory endorsement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What customer results did Google report?
Google’s October 2026 announcement cites customer examples, but it does not supply independent validation or enough methodology to treat the figures as predictions for other organizations.
- NetEase Games: Google says infrastructure scaling during peak launches fell from hours to five minutes and server costs were cut by 40% in its GKE containerization example. NetEase Games SRE director Deng Ding said integrating diverse compute instances and orchestration had turned infrastructure into a competitive advantage.
- Deutsche Börse Group: Google says the group’s move of mission-critical SAP S/4HANA and DAX index calculations to Google Cloud reduced disaster recovery time from hours to minutes, cut aggregation latency by over 50%, and shortened development cycles from months to days.
These figures are outcomes reported by Google for named customer examples in 2026; they are not guarantees, independent benchmarks, or evidence that every workload will see similar changes. Google also quotes Cognizant’s Global Practice Head for Digital Engineering, Nishant Upadhyaya, describing AI-led, governed delivery as a way to accelerate modernization. Cognizant is identified as an ecosystem collaborator integrating the portfolio with enterprise delivery frameworks.
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Which parts are available now?
Availability labels below reflect Google’s October 6, 2026 announcement and can change. Check the current product documentation and availability in your region before planning a deployment.
| Product or capability | Announcement status |
|---|---|
| Migration Center Agentic Quick Estimator | Generally available |
| EKS-to-GKE Agentic Migration | Public preview |
| X5 Series | Generally available |
| M4N Series | Generally available |
| Z4D | Generally available |
| Z4M | Preview |
| Modernization Hub | Newly launched; no separate GA or preview label stated |
What should an enterprise evaluate before choosing a migration path?
The portfolio is not a single all-purpose migration route. The right tool depends on the source environment, workload, target architecture, and the amount of change the organization can safely absorb. A practical evaluation should cover:
- Workload and source coverage: Establish whether the project concerns VMware, EKS/Kubernetes, databases, Java or .NET applications, or a mainframe. Confirm that the specific versions and dependencies are supported.
- Availability and operational readiness: Distinguish generally available products from preview tools, and decide whether a preview-stage workflow is acceptable for production-critical migration planning.
- Compatibility and cutover: Validate manifest translation, storage and network mapping, application dependencies, rollback plans, and how functional equivalence will be assessed.
- Security and control: Review credential handling, approval requirements, access boundaries, auditability, and the organization’s own regulatory obligations.
- Cost and licensing: Model infrastructure, software licenses, network transfer, operations, and ongoing support using workload-specific assumptions. Do not treat Google’s potential savings claims as a forecast.
- Delivery capability: Assess internal skills and any implementation partner’s experience with the relevant workload and governance model. Google names Cognizant as a collaborator, but the announcement does not establish a referral or affiliate program.
Google’s announcement presents a portfolio and selected product claims, not a head-to-head comparison with AWS, Microsoft Azure, or other providers. It therefore does not establish that Google is the best destination for a given enterprise workload.
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