Nasuni, a hybrid cloud storage solution, has announced the general availability of a cloud-native, distributed solution called Nasuni Edge for Amazon S3, that allows enterprises to accelerate data access and delivery times while ensuring low-latency access that is crucial for edge workloads, including cloud-based artificial intelligence and machine learning (AI/ML) applications, all through a single, unified platform.

Amazon S3 is an object storage service from Amazon Web Services (AWS) that offers industry-leading scalability, data availability, security, and performance. Nasuni Edge for Amazon S3 supports petabyte-sized workloads and allows customers to run S3-compatible storage that supports select S3 APIs on AWS Outposts, AWS Local Zones, and customers’ on-premises environments.

The Nasuni cloud-native architecture is designed to improve performance and accelerate business processes. Immediate file access is essential across various industries, including manufacturing, real estate, engineering, construction, and healthcare, where remote facilities with limited bandwidth generate large volumes of data that must be quickly processed and ingested into Amazon S3.

Nasuni Edge for Amazon S3 enhances data access in the following ways:

• Local performance at the edge: Customers can now deploy Nasuni Edge for Amazon S3 wherever high performance with low latency is required, in AWS Local Zones, on AWS Outposts, or in customers’ self-managed on-premises environments. Local caching via Nasuni provides LAN-like performance to meet application owner and user expectations.
• Multi-protocol read/write scenarios: Access to data often requires other protocols beyond Amazon S3, usually Server Message Block (SMB) or Network File System (NFS). Nasuni provides multi-protocol flexibility that facilitates a wide range of application access.
• Support for more file metadata: Nasuni extends file management scenarios where classification and compliance are important by supporting an extended number of tags, the number of characters in tags, and the size of file metadata.