German
Following its recent announcement of a collaboration with Google Cloud, NetApp has rolled out new features to streamline how enterprises leverage their existing data for AI workloads in cloud environments. These updates focus on lowering the operational complexity and expenses tied to transferring and managing data across hybrid and multi-cloud infrastructures.
At a basic level, the joint initiative addresses a widespread enterprise pain point: organizations aim to apply AI to their existing datasets, but data gravity, fragmentation, and migration costs frequently hinder adoption. NetApp and Google Cloud are positioning their integration to let customers move data into Google Cloud once and utilize it across various services—eliminating the need for repeated transfers or duplication.
Google Cloud NetApp Volumes and NetApp Migrator
A cornerstone of this strategy is Google Cloud NetApp Volumes, which enables enterprises to run file- and block-based workloads in Google Cloud without reworking their applications. NetApp noted that customers can migrate their existing datasets directly into the service and instantly access Google Cloud’s native tools—including AI and analytics solutions—using that data. This reduces the requirement for parallel data pipelines and lessens the latency and costs associated with data duplication.
NetApp Cloud Volumes gaphic
NetApp also revealed the general availability of NetApp Data Migrator (NDM), a multi-cloud data migration service built to transfer data across environments without the need for specialized skills. The service is designed to simplify data movement between on-premises systems and cloud platforms, ensuring more consistent data access for AI and other advanced workloads.
Pravjit Tiwana, Senior Vice President and General Manager of Cloud Storage and Services at NetApp, stated that customers can effortlessly move their enterprise data into Google Cloud NetApp Volumes and access Google Cloud services—including AI applications—without transferring or duplicating the data. These enhancements reduce costs, delays, and complexities in adopting AI.
Flex Unified Service Level for Google Cloud NetApp Volumes
On Google Cloud’s side, the companies highlighted the general availability of the Flex Unified Service Level for Google Cloud NetApp Volumes. This introduces a single storage pool that supports both file and block workloads across all Google Cloud regions. The unified model is engineered to accommodate a variety of enterprise use cases—such as databases, high-performance computing, electronic design automation, and VMware environments—without requiring application modifications or separate storage architectures.
Googlle Cloud Storage Graphic
Sameet Agarwal, Vice President and General Manager of Storage at Google Cloud, emphasized that AI innovation depends on AI-ready data supported by flexible, unified architectures that eliminate data silos. He noted that the partnership with NetApp reduces barriers to data migration, allowing organizations to quickly leverage Google Cloud’s advanced data and AI capabilities to drive business innovation.
Overall, the integration extends NetApp’s hybrid cloud storage model to align more closely with Google Cloud’s AI and data services. The combined approach focuses on enabling enterprises to keep data within a unified storage layer while utilizing cloud-native AI features—instead of repeatedly moving data between different systems.
Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
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Email: yangyd@qianxingdata.com
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Sandy Yang/Global Strategy Director
WhatsApp / WeChat: +86 13426366826
Email: yangyd@qianxingdata.com
Website: www.qianxingdata.com/www.storagesserver.com
Business Focus:
ICT Product Distribution/System Integration & Services/Infrastructure Solutions
With 20+ years of IT distribution experience, we partner with leading global brands to deliver reliable products and professional services.
“Using Technology to Build an Intelligent World”Your Trusted ICT Product Service Provider!