Managed high-performance parallel file system for HPC and ML workloads.
What is Google Cloud Managed Lustre?
Google Cloud Managed Lustre is a fully managed parallel file system for workloads with extreme I/O requirements. Based on open-source Lustre technology and developed jointly with DDN, the service provides the high throughput and high IOPS performance required for High-Performance Computing (HPC), machine learning training, and scientific simulations. The service is generally available (GA).
Lustre is an established file system in the supercomputing world. Google Cloud Managed Lustre brings this technology to the cloud as a managed service: automatic provisioning, scaling, and management of the file system without teams needing to build their own Lustre expertise.
The service integrates with Compute Engine, GKE, and Batch. Compute nodes mount the Lustre file system over the network and access data in parallel, allowing many VMs to access the same dataset simultaneously.
Core Features
- Parallel Access: Many compute nodes access the same file system simultaneously
- Selectable Performance Tiers: Multiple throughput levels per TiB of capacity, plus a dynamic tier that automatically adapts to growing AI and HPC datasets
- High IOPS Performance: Designed for very high read and write IOPS as well as high metadata operation rates
- Fully Managed: Automatic provisioning, scaling, and maintenance without Lustre expertise
Typical Use Cases
Machine Learning Training
ML training jobs with large datasets benefit from Managed Lustre. GPU clusters load training data with high throughput from the file system, increasing GPU utilization and potentially reducing training time.
High-Performance Computing and Simulations
HPC workloads such as genomics analysis, financial modeling, and engineering simulations require parallel access to large datasets. Managed Lustre provides the I/O performance these applications need for efficient execution.
Benefits
- High throughput and high IOPS performance for I/O-intensive workloads
- No need to build in-house Lustre expertise
- Integration with Compute Engine, GKE, and Batch
- Selectable performance tiers for different cost-performance requirements
Integration with innFactory
As a certified Google Cloud Partner, innFactory supports you with Google Cloud Managed Lustre: HPC architecture design, ML training pipeline optimization, storage sizing, and integration with existing compute workloads.
Typical Use Cases
Frequently Asked Questions
What is Google Cloud Managed Lustre?
Google Cloud Managed Lustre is a fully managed parallel file system based on open-source Lustre technology, developed jointly with DDN. It is optimized for AI and HPC workloads with very high throughput and IOPS requirements, without requiring you to run your own Lustre infrastructure. The service is generally available (GA).
Which workloads is Managed Lustre suited for?
Managed Lustre is suited for workloads with high I/O requirements such as ML training, genomics analysis, financial modeling, simulations, and media rendering. The service is ideal when many compute nodes need to access large datasets simultaneously.
How does Managed Lustre differ from Filestore?
Filestore provides NFS file storage for general workloads. Managed Lustre provides a parallel file system with significantly higher throughput for HPC and ML, offering several selectable performance tiers per TiB of capacity.
How is Managed Lustre billed?
Billing is based on provisioned capacity in TiB, tiered by performance level (different throughput per TiB), plus a dynamic tier that automatically adapts performance to the access pattern. The official pricing page lists exact prices.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of Google Cloud (official documentation). This page does not represent an offer by Google Cloud.
