Alluxio AI

Alluxio AI is a distributed caching and data-access layer for AI infrastructure. It sits between AI compute workloads and persistent storage, caching data closer to GPUs and other compute resources while leaving the source-of-truth data in object storage, data lakes, HDFS, NFS, or other supported systems.

The platform is designed for I/O-intensive AI workloads, including model training, checkpoint loading and writing, feature-store access, model deployment, and inference serving. It can cache data on local NVMe capacity in GPU nodes or dedicated compute nodes, reducing repeated reads from remote cloud or network storage. Cache behavior can be configured by dataset, workload priority, time-to-live, and access pattern, and teams can preload data before workloads begin.

Alluxio AI provides S3-compatible access, a POSIX interface, and a Python SDK so applications can use cached data without changing the persistent data location or rewriting existing workflows. It supports cloud, on-premises, hybrid, and multi-cloud environments, and integrates with frameworks such as PyTorch, TensorFlow, Ray, and Spark. Built-in metrics and APIs expose cache hit rates, latency, and throughput, while Kubernetes deployment and management are supported through an operator.

Alluxio Community Edition is available free with community support. Alluxio Enterprise AI is sold by quote and includes enterprise software capabilities and SLA-based technical support.