Google Cloud Managed Lustre delivers a high-performance, fully managed parallel
file system optimized for AI and HPC applications. With multi-petabyte-scale
capacity and up to 10 TBps throughput, Managed Lustre
facilitates the migration of demanding workloads to the cloud.

## Highlights

- Developed in collaboration with DDN, the leading provider and primary maintainer of the Lustre file system.
- Supports extreme IOPs and low latency.
- POSIX compliance ensures compatibility with existing applications, tools, and workflows.
- Integrated with Compute Engine and Google Kubernetes Engine, allowing you to mount high-performance storage to your client machines and containerized applications.
- Provides high-speed on-demand data transfers to and from Cloud Storage, and automated synchronization from Cloud Storage with a [Cloud Storage mirror](https://docs.cloud.google.com/managed-lustre/docs/storage-mirror.md.txt).

## Specifications

| Metric | Result |
|---|---|
| Storage capacity | From 9,000 GiB up to 84,016,000 GiB (80.1 PiB) |
| Throughput | Up to 10 TBps |
| IOPS | Up to 5,800 read IOPS per TiB Up to 5,600 write IOPS per TiB |
| Metadata performance | Per 72 GBps of throughput, up to: - 410,000 stats per second - 115,000 creates per second - 95,000 deletes per second Up to a maximum of 22 times the base value. |
| Maximum file size | 0.5 PiB |

For more information about the different performance tiers available, see
[Performance tiers](https://docs.cloud.google.com/managed-lustre/docs/performance-tiers.md.txt). For more
information about quotas and limits, see
[Quotas and limits](https://docs.cloud.google.com/managed-lustre/docs/quotas.md.txt).

## Use Cases

- **High-performance computing**: Managed Lustre excels in HPC
  environments where multiple compute nodes need fast and consistent access to
  shared data for simulations, modeling, and analysis.

- **Machine learning**: Managed Lustre can handle the large
  datasets and high throughput requirements of machine learning workloads,
  enabling efficient training and inference.

- **Automated training data synchronization** : With a
  [Cloud Storage mirror](https://docs.cloud.google.com/managed-lustre/docs/storage-mirror.md.txt), training corpora,
  models, and supporting libraries hosted in Cloud Storage are automatically
  synchronized to your file system.

## Data protection

Managed Lustre encrypts data at rest and data in transit.

## Encryption at rest

All data stored in a Managed Lustre file system is encrypted at
rest.

For more information, see
[Encryption at rest](https://docs.cloud.google.com/docs/security/encryption/default-encryption.md.txt).

## Encryption in transit

While the Lustre protocol itself doesn't encrypt traffic between clients and
servers, all in-transit data to and within Google Cloud is encrypted. This
includes data transfers between Managed Lustre and
Cloud Storage.

For more information, see
[Encryption in transit](https://docs.cloud.google.com/docs/security/encryption-in-transit.md.txt).

## Pricing

See the [Pricing](https://cloud.google.com/products/managed-lustre/pricing) page
for details.