Google Cloud integrates NetApp Volumes with Vertex AI for enhanced data management

In recent months, Google Cloud and NetApp have been working collaboratively to enhance the NetApp Volumes storage service, allowing it to better integrate with Google Cloud's Vertex AI platform. This integration aims to significantly improve the management and processing of larger datasets, facilitate independent scaling of capacity and performance, and ensure adherence to regional compliance requirements. The full integration of these services is anticipated to accelerate the development of generative AI, enabling organizations to streamline their AI data engineering processes while avoiding the pitfalls of data management complexities. The Google Cloud NetApp Volumes, or GCNV, is a fully managed cloud file service based on the ONTAP operating system. This cloud-native service supports various protocols including NFS V3, V4.1, and SMB, which is crucial for diverse modern cloud applications. Notably, users can create storage volumes ranging from 15TiB up to 1PiB, optimizing throughput and avoiding the need to partition data across multiple volumes. This flexibility positions GCNV as a robust solution for industries that process petabyte-scale datasets for critical workloads like AI applications and electronic design automation (EDA). Google Cloud's Vertex AI provides an integrated platform for data engineering, data science, and machine learning (ML) workflows, including the deployment and customization of large language models (LLMs). This service also extends access to advanced AI models, enhancing the capabilities of organizations in developing AI applications. The collaboration between Google Cloud and NetApp is expected to ease the complexities of building custom agents and managing data pipelines—specifically for retrieval-augmented generation applications—by providing a more seamless experience for users. Moreover, the upcoming features in the NetApp Volumes service include the Flex Service Level, which enables users to independently scale both storage capacity and performance. This allows organizations to optimize costs while ensuring that performance needs are met without over-provisioning resources. The integration will also support the Assured Workloads framework used by Google Cloud, helping customers maintain controlled environments that meet specific compliance requirements. With these developments, both companies are prepared to offer a powerful solution that enhances digital transformations for their customers, setting the stage for long-term success in the increasingly competitive AI landscape.