Amazon FSx for Lustre, is a fully managed service, that makes it easy and cost effective to launch and run the world’s most popular high-performance (HPC) Lustre file system.
Lustre is an open source file system designed for applications that require fast storage – where you want your storage to keep up with your compute
FSx handles the traditional complexity of setting up and managing high-performance Lustre file systems
FSx for Lustre is ideal for use cases where speed matters, such as machine learning, high performance computing (HPC), video processing, financial modeling, genome sequencing, and electronic design automation (EDA)
Amazon FSx provides multiple deployment options to optimize cost
Scratch file systems
designed for temporary storage and short-term processing of data.
data is not replicated and does not persist if a file server fails.
Persistent file systems
designed for long-term storage and workloads.
is highly available, and data is automatically replicated within the AZ that is associated with the file system.
data volumes attached to the file servers are replicated independently from the file servers to which they are attached.
FSx for Lustre is compatible with the most popular Linux-based AMIs, including Amazon Linux, Amazon Linux 2, Red Hat Enterprise Linux (RHEL), CentOS, SUSE Linux and Ubuntu.
FSx for Lustre can be accessed from a Linux instance, by installing the open-source Lustre client and mounting the file system using standard Linux commands.
FSx for Lustre with S3
Amazon FSx also integrates seamlessly with S3, making it easy to process cloud data sets with the Lustre high-performance file system.
Amazon FSx for Lustre file system transparently presents S3 objects as files and allows writing changed data back to S3.
Amazon FSx for Lustre file system can be linked with a specified S3 bucket, making the data in the S3 accessible to the file system.
S3 objects’ names and prefixes will be visible as files and directories
Amazon S3 objects are lazy loaded by default.
Objects are only loaded into the file system only when first accessed by the applications.
Amazon FSx for Lustre automatically loads the corresponding objects from S3 when accessed
Subsequent reads of these files are served directly out of the file system with low, consistent latencies.
Amazon FSx for Lustre file system can optionally batch hydrated
Amazon FSx for Lustre uses parallel data transfer techniques to transfer data from S3 at up to hundreds of GBs/s.
Files from the file system can be exported back to the S3 bucket
FSx for Lustre Security
FSx for Lustre provides encryption at rest for the file system and the backups, by default, using KMS
FSx encrypts data-in-transit when accessed from supported EC2 instances only
FSx for Lustre Scalability
Amazon FSx for Lustre file systems scale to hundreds of GB/s of throughput and millions of IOPS.
FSx for Lustre also supports concurrent access to the same file or directory from thousands of compute instances.
FSx for Lustre provides consistent, sub-millisecond latencies for file operations.
FSx for Lustre Availability and Durability
On a scratch file system, file servers are not replaced if they fail and data is not replicated.
On a persistent file system, if a file server becomes unavailable it is replaced automatically and within minutes.
Amazon FSx for Lustre provides a parallel file system, where data is stored across multiple network file servers to maximize performance and reduce bottlenecks, and each server has multiple disks.
Amazon FSx takes daily automatic incremental backups of the file systems, and allows manual backups at any point.
Backups are highly durable and file-system-consistent
AWS Certification Exam Practice Questions
Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
Open to further feedback, discussion and correction.
A solutions architect is designing storage for a high performance computing (HPC) environment based on Amazon Linux. The workload stores and processes a large amount of engineering drawings that require shared storage and heavy computing. Which storage option would be the optimal solution?