NetApp and Google Cloud expand AI-related data services

NetApp has introduced new solutions with Google Cloud aimed at helping enterprises manage data for AI with reduced complexity and cost.

  • Tuesday, 28th April 2026 Posted 2 hours ago in by Sophie Milburn

NetApp, a data infrastructure company, recently announced a set of new offerings aimed at improving how enterprises use their data for artificial intelligence (AI) applications. A key element of these developments is its collaboration with Google Cloud, focused on enabling data movement and management in cloud environments.

A common challenge for organisations is using existing data for AI projects, particularly when data is spread across multiple environments. This can lead to increased costs and delays. NetApp and Google Cloud aim to address these issues by providing solutions that support running enterprise applications, databases, and AI workloads in the cloud without requiring significant changes to existing architectures.

At the Google Cloud Next 2026 event, the two companies presented updates intended to help customers use AI-related workloads. One of these is the NetApp Data Migrator (NDM), a multi-cloud migration service designed to simplify data transfers across different environments and reduce the need for specialised migration expertise.

Another offering is Google Cloud NetApp Volumes Flex Unified Service Level, a storage solution that supports both file and block workloads and is available across all Google Cloud regions. It is designed for a range of use cases, including high-performance computing and electronic design automation, without requiring changes to existing applications.

By supporting a more centralised data approach, NetApp and Google Cloud aim to reduce some of the complexity associated with moving data between environments. The updates reflect efforts to improve access to data suitable for AI workloads, using Google Cloud’s data and AI services.

Overall, the collaboration focuses on making it easier for organisations to manage and use data in cloud-based AI projects while maintaining operational flexibility.