For specialized support, we also provide a comprehensive modernization assessment at no cost through our Rapid Migration & Modernization Program (RaMP).
Platform modernization
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:
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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.
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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.
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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.
Cloud elasticity for VMware environments
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 (GKE), BigQuery, and Gemini Enterprise, allowing teams to ground autonomous agents in operational data without code changes.
Automated container transitions to GKE
The new EKS-to-GKE Agentic Migration (Public Preview) automates transitions from AWS Elastic Kubernetes Service to GKE thanks to:
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An automated pipeline: Manages discovery, Kubernetes manifest translations, storage and network mappings across clouds.
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Enterprise-grade security: Built-in Human-in-the-Loop (HITL) approval gates and in-memory credential security maintain strict GitOps compliance.
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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
Application modernization with Modernization Hub
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.
.NET and Java modernization
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.
