Lustre is a high-performance distributed file system designed for large-scale environments that require fast access to massive amounts of data. It is optimized for low-latency, high-throughput workloads by distributing I/O across multiple storage nodes and using efficient RPC-based communication over high-speed networks like InfiniBand or Ethernet via LNet.
It separates metadata and data storage by using Metadata Servers (MDS) for namespace operations (such as file creation, lookup, permissions, and directory traversal) and Object Storage Servers (OSS) for serving actual file data stored on Object Storage Targets (OSTs). This separation prevents metadata operations from becoming a bottleneck and allows independent scaling.
It supports parallel I/O, allowing a single file to be accessed across multiple storage targets simultaneously for higher throughput. Files are striped across multiple OSTs with configurable stripe count and stripe size, enabling multiple clients or threads to read and write different parts of the file in parallel.
It can scale to handle petabytes to exabytes of data and thousands of client nodes at the same time. This scalability is achieved by adding more OSS/OST pairs for data capacity and throughput, and scaling metadata performance using multiple MDTs (DNE – Distributed Namespace Environment).
It is widely used in high-performance computing (HPC), research, and data-intensive workloads such as simulations and analytics. Its POSIX-compliant interface, combined with features like distributed locking (LDLM), recovery mechanisms, and support for large clusters, makes it suitable for demanding applications like AI/ML pipelines, scientific simulations, and large-scale data processing.
If you want to learn more about the Lustre file system, refer to the Lustre Operations Manual: https://www.lustre.org/documentation/