How FSx for Lustre Works

• FSx for Lustre is a fully managed service that makes it easy and cost-effective to launch and run the high-performance Lustre file system1.
• It is designed for applications that require fast storage, providing sub-millisecond latencies, up to hundreds of GBps of throughput, and up to millions of IOPS1.
• FSx for Lustre eliminates the traditional complexity of setting up and managing Lustre file systems, enabling you to spin up and run a high-performance file system in minutes1.
• It provides multiple deployment options so you can optimize cost for your needs1.
• FSx for Lustre is POSIX-compliant, so you can use your current Linux-based applications without having to make any changes1.

Benefits of FSx for Lustre

• It accelerates compute workloads with shared storage that provides sub-millisecond latencies, up to hundreds of GBs/s of throughput, and millions of IOPS2.
• It allows you to access and process Amazon S3 data from a high-performance file system by linking your file systems to S3 buckets2.
• It offers a range of deployment options to optimize price and performance2.
• It provides a native file system interface and works as any file system does with your Linux operating system1.

Limitations of FSx for Lustre

• There are quotas for Amazon FSx for Lustre per AWS account, per AWS Region3.
• There are limits on Amazon FSx for Lustre resources for each file system in an AWS Region3.
• Creating large files with low stripe counts can cause I/O performance bottlenecks4.

Use Cases for FSx for Lustre

• It can be used to accelerate machine learning (ML) by reducing training times with maximized throughput to your compute resources and seamless access to training data stored in Amazon S32.
• It enables high performance computing (HPC) by powering the most demanding HPC workloads with fast, highly scalable storage, natively integrated with AWS compute and orchestration services2.
• It unlocks big data analytics by supporting thousands of compute instances running complex analytics workloads on petabytes of data2.