Today, we’re announcing Google Cloud Modernize, an end-to-end transformation portfolio to help enterprises collapse multi-year roadmaps with the power of AI.
Google Cloud Modernize brings together Google Cloud’s proven migration and modernization tools, including Migration Center, Google Cloud VMware Engine, Google Cloud Mainframe Modernization and our new EKS-to-GKE Migration Agent, into a single portfolio. With it, enterprise teams now have purpose-built agentic capabilities across infrastructure assessment, platform modernization, and application modernization.
Central to this portfolio is Modernization Hub, a newly launched in-console experience where developers and architects can analyze source code, map dependencies, and accelerate modernization for Java, .NET, and mainframe applications.
Every transformation begins with an accurate assessment. With new Gemini capabilities in Migration Center, the Agentic Quick Estimator (GA) converts VMware inventory exports (such as RVTools) and infrastructure inputs into total cost of ownership (TCO) projections for your Compute Engine environment.
Using an interactive chat interface, teams can test real-time modeling assumptions, such as evaluating multi-region footprints or comparing BYOL licensing against pay-as-you-go, to discover contextual cost optimizations. This condenses weeks of spreadsheet modeling into a defensible business case in minutes.
For specialized support, we also provide a comprehensive modernization assessment at no cost through our [Rapid Migration & Modernization Program (RaMP)](https://cloud.google.com/solutions/cloud-migration-program).
With the rise of real-time AI agents querying backend systems, workloads increasingly require high-throughput infrastructure that removes I/O bottlenecks. Once you’ve defined your target environment using our assessments, there are several new purpose-built compute options for mission-critical workloads:
SAP S/4HANA at scale (X5 Series, GA): Delivers single-node 43 TiB memory configurations that remove the previous 29 TiB ceiling, allowing enterprise ERP estates to run without distributed partitioning overhead.
Core-optimized database performance (M4N Series, GA): Delivers 26.57 GiB RAM per vCPU paired with Hyperdisk Extreme. This prevents organizations from overprovisioning compute cores to meet memory requirements, reducing software licensing costs by more than 20% for Oracle and other core-licensed databases.
**Ultra-low latency data engines (**Z4D, GA and Z4M, Preview): Deliver up to 84,000 GiB and 168,000 GiB of high-speed local NVMe SSD respectively, 400 Gbps networking for both Z4D and Z4M, and RDMA support for Z4M. This throughput reduces I/O wait times and prevents query timeouts when real-time AI agents query vector stores, operational databases, and large-scale data pipelines.
For organizations operating VMware estates that need the elasticity of the cloud but aren’t ready to re-architect their environment, the **Google Cloud self-managed VMware solution** provides administrative control on Bare Metal Z3 shapes with VMware Cloud Foundation (VCF) 9.1. Native global VPC links connect VMware estates directly to Compute Engine, [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine?utm_source=gemini) (GKE), BigQuery, and Gemini Enterprise, allowing teams to ground autonomous agents in operational data without code changes.
The new **EKS-to-GKE Agentic Migration** (Public Preview) automates transitions from AWS Elastic Kubernetes Service to [GKE](https://cloud.google.com/kubernetes-engine?utm_source=gemini) thanks to:
An automated pipeline: Manages discovery, Kubernetes manifest translations, storage and network mappings across clouds.
Enterprise-grade security: Built-in Human-in-the-Loop (HITL) approval gates and in-memory credential security maintain strict GitOps compliance. A fast-track to modern runtimes: Quickly moves workloads to GKE to take advantage of low-latency model serving, autoscaling, and multi-agent orchestration.
NetEase Games demonstrated the value of this platform approach by containerizing services on GKE, reducing infrastructure scaling times from hours to five minutes during peak launches while cutting server costs by 40%:
"By integrating diverse computing instances and powerful orchestration, we have transformed our infrastructure into a competitive advantage, ensuring NetEase remains a leader in the global gaming market." - Deng Ding, Director of Site Reliability Engineering, NetEase Games
Landing on modern infrastructure enables teams to unlock legacy business logic and modernize their core applications. Modernization Hub centralizes several modernization tools directly inside the Google Cloud console.
Modernization Hub integrates the Google Cloud App Modernization CLI (CodMod), which uses Gemini to analyze large source code repositories, understand legacy application architectures,maps hidden dependencies, identifies modernization challenges and generates modernization recommendations. This enables customers to migrate legacy .NET Framework applications to modern .NET Core running on Linux containers, reducing OS licensing overhead, while also making these applications and data accessible to modern AI agent workflows.
For customers running mainframes, we provide specialized solutions to help accelerate and de-risk end-to-end application transformation to Google Cloud: Mainframe Assessment Tool**:** Parses legacy mainframe codebases, extracts business rules, maps application and data dependencies to generate cloud-ready target application specifications and power agentic modernization workflows.
Dual Run**:** Substantially reduces cutover risk by replaying live production transaction streams simultaneously across the mainframe and the new cloud applications, verifying functional equivalence before going live.
Mainframe Connector**:** Copies mainframe data directly into Google Cloud services (BigQuery, AlloyDB, GCS and others), , unlocking legacy data and supports hybrid architectures.
Intesa Sanpaolo used Google Cloud mainframe modernization solutions to accelerate their core banking transformation off the mainframe and onto Google Cloud:
“To confidently move forward with Mainframe Modernization, we will need to provide confidence and assure the bank's leadership and internal control units as well as get approval from the regulators. One of the enablers for this is Google Cloud Dual Run, which is gradually providing the evidences to build such confidence to all three groups.” - Claudio Balbo, Head of IT Architecture, Intesa Sanpaolo
Deutsche Börse Group transitioned its mission-critical SAP S/4HANA environment and DAX® index calculations to Google Cloud, cutting disaster recovery times from hours to minutes, reducing aggregation latency by over 50%, and shortening development cycles from months to days.
To deliver these capabilities at enterprise scale, we are also collaborating with our global partner ecosystem to integrate Google Cloud Modernize with enterprise delivery frameworks, including Cognizant:
“Google’s modernization offering heralds the next frontier of AI-native modernization — enabling enterprises to autonomously decode legacy complexity and accelerate into cloud-first, intelligent architectures. Coupled with Cognizant's AI-led, governed delivery engine, we amplify this shift through agentic business processing, unlocking faster, outcome-driven value at scale.” - Nishant Upadhyaya, Global Practice Head – Digital Engineering, Cognizant
Modernizing your infrastructure and applications is the baseline requirement for enterprise AI agility. Google Cloud Modernize equips teams to navigate each phase safely and efficiently as they pursue AI readiness and adoption.
Get started:
Join the webinar: Register for our upcoming session on November 17 to see live demos of Modernization Hub and our agentic migration tools.
Explore the console: Log into the Google Cloud Modernize console to access Modernization Hub.
Start planning: Visit the Google Cloud Modernize webpage, or request a modernization assessment at no cost today.