# Filesystems A _filesystem_ is a high-capacity regional file store you can attach to your instance to store datasets and back up system state. In most regions, each filesystem has a capacity of 8 EB (8,000,000 TB), and you can create up to 24 total filesystems. In the Texas, USA (us-south-1) region, filesystems are currently limited to 10 TB of capacity. For information on how filesystems are billed, see the [Billing overview](https://docs.lambda.ai/public-cloud/billing/#filesystems). ## Accessing your filesystem ### Accessing from another instance or a 1-Click Cluster To access a filesystem from within Lambda Cloud: - The filesystem must reside in the same region as the instance or cluster. - You must attach the filesystem to your instance or cluster at the time that the instance or cluster is launched. - You must have access to the workspace in which the filesystem resides. Note Filesystems cannot currently be transferred between regions. ### Accessing remotely You can remotely access your filesystem in two ways: - _Filesystem S3 Adapter (select regions only):_ This adapter allows you to use S3-compatible tools like `rclone` and `s5cmd` to copy files to and from your filesystems and perform common file operations. For more information, including a list of supported regions, see [Filesystem S3 Adapter](https://docs.lambda.ai/public-cloud/s3-adapter-filesystems/). - `rsync`: If your filesystem's region doesn't support the Filesystem S3 Adapter yet, you can use `rsync` to copy files to and from your instance and any filesystem mounted on that instance. For more information, see [Importing and exporting data](https://docs.lambda.ai/public-cloud/importing-exporting-data/). Note Filesystems can't be attached to running instances and can't be mounted remotely using NFS or similar protocols. ## Managing your filesystems ### Creating a new filesystem In most cases, you create and attach a filesystem when you create a new instance or 1-Click Cluster (1CC). To create a filesystem _without_ immediately attaching it to an instance or 1CC: Warning You can't attach a filesystem after you've created an instance or launched a 1CC. 1. In the Lambda Cloud console, navigate to the [Storage page](https://cloud.lambda.ai/file-systems). 2. Click **Create filesystem**. A dialog appears. 3. Name your filesystem and select the region in which you want to create the filesystem. You must create your filesystem in the same region and workspace as the instance or 1CC you plan to attach it to. 4. Click **Create filesystem**. You can also create and filesystems using the Cloud API. For more information, see [Create filesystem](https://docs.lambda.ai/api/cloud#createFilesystem) in the Cloud API docs. ### Viewing your existing filesystems To view your existing filesystems, visit the [Storage page](https://cloud.lambda.ai/file-systems) in the Lambda Cloud console. You can also list existing filesystems using the Cloud API. For more information, see [List filesystems](https://docs.lambda.ai/api/cloud#listFilesystems) in the Cloud API docs. ### Deleting a filesystem To delete a filesystem: 1. If needed, back up any important data on the instance your filesystem is connected to, and then terminate that instance. Your filesystem must be detached from all instances before it can be deleted. 2. If needed, back up any important data from your filesystem. For guidance on how to back up data, see [Importing and exporting data](https://docs.lambda.ai/public-cloud/importing-exporting-data/). 3. In the Lambda Cloud console, navigate to the [Storage page](https://cloud.lambda.ai/file-systems). 4. In the row for the filesystem you want to delete, in the **Actions** column, click **Delete**. A dialog appears. 5. Follow the instructions in the dialog and click **Delete filesystem**. You can also delete a filesystem using the Cloud API. For more information, see [Delete filesystem](https://docs.lambda.ai/api/cloud#filesystemDelete) in the Cloud API docs. ## Managing cost ### Viewing filesystem usage To view your monthly usage, navigate to the [Usage page](https://cloud.lambda.ai/usage) in the Lambda Cloud console and then click the **Filesystems** tab. ### Setting usage limits Currently, you can't set a limit (quota) on your filesystem usage. You can see the usage of a filesystem from within an instance by running `df -h -BG`. This command produces output similar to: ``` Filesystem 1G-blocks Used Available Use% Mounted on tmpfs 44G 1G 44G 1% /run efivarfs 1G 1G 1G 2% /sys/firmware/efi/efivars /dev/vda1 3969G 24G 3946G 1% / tmpfs 216G 1G 216G 1% /dev/shm tmpfs 1G 0G 1G 0% /run/lock /dev/vda15 1G 1G 1G 7% /boot/efi 10.12.69.11:/768f824a-2608-4200-8a6a-3d2996d10587 6792422G 0G 6792422G 0% /lambda/nfs/persistent-storage tmpfs 44G 1G 44G 1% /run/user/1000 ``` In the example output, above: - The name of the filesystem is `persistent-storage`. - The size of the filesystem is `6792422G`. - The available capacity of the filesystem is `6792422G`. - The used percentage of the filesystem is `0%`. - The filesystem is mounted on `/lambda/nfs/persistent-storage`. Note You can also use the Cloud API's `/file-systems` endpoint to find out your filesystem usage. For details, see [List filesystems](https://docs.lambda.ai/api/cloud#listFilesystems) in the Cloud API browser. ### Managing auto-generated application data Applications that follow the Freedesktop.org [Trash Specification](https://specifications.freedesktop.org/trash-spec/1.0/), such as JupyterLab, might create hidden `.Trash-*` directories on your mounted filesystems. Files moved to these directories are not automatically deleted and **will count towards your billed storage usage** until you permanently delete them. For guidance on managing your `.Trash-*` directories, see [Emptying `.Trash-*` directories](https://docs.lambda.ai/public-cloud/on-demand/managing-system-environment/#emptying-trash-directories). ## Next steps - For guidance on transferring data to and from your Lambda filesystems, see [Importing and exporting data](https://docs.lambda.ai/public-cloud/importing-exporting-data/).