Volumes

Modal Volumes provide a high-performance distributed file system for your Modal applications. They are designed for write-once, read-many I/O workloads, like creating machine learning model weights and distributing them for inference.

Creating a Volume

The easiest way to create a Volume and use it as a part of your app is to use the modal volume create CLI command. This will create the Volume and output some sample code:

% modal volume create my-volume
Created volume 'my-volume' in environment 'main'.

To attach an existing Volume to a Modal Function, use Volume.from_name:

vol = modal.Volume.from_name("my-volume")


@app.function(volumes={"/data": vol})
def run():
    with open("/data/xyz.txt", "w") as f:
        f.write("hello")
    vol.commit()  # Needed to make sure all changes are persisted before exit

You can also browse and manipulate Volumes from an ad hoc Modal Shell:

% modal shell --volume my-volume --volume another-volume

Volumes will be mounted under /mnt.

Creating Volumes lazily from code

You can also create Volumes lazily from code using:

vol = modal.Volume.from_name("my-volume", create_if_missing=True)

This will create the Volume if it doesn’t exist.

Volumes can also be used outside Modal via the Python SDK or our CLI.

Using a Volume from local code

You can interact with Volumes from anywhere you like using the modal Python client library.

vol = modal.Volume.from_name("my-volume")

with vol.batch_upload() as batch:
    batch.put_file("local-path.txt", "/remote-path.txt")
    batch.put_directory("/local/directory/", "/remote/directory")
    batch.put_file(io.BytesIO(b"some data"), "/foobar")

For more details, see the reference documentation.

Using a Volume via the command line

You can also interact with Volumes using the command line interface. You can run modal volume to get a full list of its subcommands:

% modal volume
Usage: modal volume [OPTIONS] COMMAND [ARGS]...

 Read and edit modal.Volume volumes.
 Note: users of modal.NetworkFileSystem should use the modal nfs command instead.

╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --help          Show this message and exit.                                                                                                                                                            │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ File operations ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ cp       Copy within a modal.Volume. Copy source file to destination file or multiple source files to destination directory.                                                                           │
│ get      Download files from a modal.Volume object.                                                                                                                                                    │
│ ls       List files and directories in a modal.Volume volume.                                                                                                                                          │
│ put      Upload a file or directory to a modal.Volume.                                                                                                                                                 │
│ rm       Delete a file or directory from a modal.Volume.                                                                                                                                               │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Management ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ create   Create a named, persistent modal.Volume.                                                                                                                                                      │
│ delete   Delete a named, persistent modal.Volume.                                                                                                                                                      │
│ list     List the details of all modal.Volume volumes in an Environment.                                                                                                                               │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

For more details, see the reference documentation.

Volume commits and reloads

Unlike a normal filesystem, you need to explicitly reload the Volume to see changes made since it was first mounted. This reload is handled by invoking the .reload() method on a Volume object. Similarly, any Volume changes made within a container need to be committed for those the changes to become visible outside the current container. This is handled periodically by background commits and directly by invoking the .commit() method on a modal.Volume object.

At container creation time the latest state of an attached Volume is mounted. If the Volume is then subsequently modified by a commit operation in another running container, that Volume modification won’t become available until the original container does a .reload().

Consider this example which demonstrates the effect of a reload:

import pathlib
import modal

app = modal.App()

volume = modal.Volume.from_name("my-volume")

p = pathlib.Path("/root/foo/bar.txt")


@app.function(volumes={"/root/foo": volume})
def f():
    p.write_text("hello")
    print(f"Created {p=}")
    volume.commit()  # Persist changes
    print(f"Committed {p=}")


@app.function(volumes={"/root/foo": volume})
def g(reload: bool = False):
    if reload:
        volume.reload()  # Fetch latest changes
    if p.exists():
        print(f"{p=} contains '{p.read_text()}'")
    else:
        print(f"{p=} does not exist!")


@app.local_entrypoint()
def main():
    g.remote()  # 1. container for `g` starts
    f.remote()  # 2. container for `f` starts, commits file
    g.remote(reload=False)  # 3. reuses container for `g`, no reload
    g.remote(reload=True)   # 4. reuses container, but reloads to see file.

The output for this example is this:

p=PosixPath('/root/foo/bar.txt') does not exist!
Created p=PosixPath('/root/foo/bar.txt')
Committed p=PosixPath('/root/foo/bar.txt')
p=PosixPath('/root/foo/bar.txt') does not exist!
p=PosixPath('/root/foo/bar.txt') contains hello

This code runs two containers, one for f and one for g. Only the last function invocation reads the file created and committed by f because it was configured to reload.

Background commits

Modal Volumes run background commits: every few seconds while your Function executes, the contents of attached Volumes will be committed without your application code calling .commit. A final snapshot and commit is also automatically performed on container shutdown.

Being able to persist changes to Volumes without changing your application code is especially useful when training or fine-tuning models using frameworks.

Model serving

A single ML model can be served by simply baking it into a modal.Image at build time using run_function. But if you have dozens of models to serve, or otherwise need to decouple image builds from model storage and serving, use a modal.Volume.

Volumes can be used to save a large number of ML models and later serve any one of them at runtime with much better performance than can be achieved with a modal.NetworkFileSystem.

This snippet below shows the basic structure of the solution.

import modal

app = modal.App()
volume = modal.Volume.from_name("model-store")
model_store_path = "/vol/models"


@app.function(volumes={model_store_path: volume}, gpu="any")
def run_training():
    model = train(...)
    save(model_store_path, model)
    volume.commit()  # Persist changes


@app.function(volumes={model_store_path: volume})
def inference(model_id: str, request):
    try:
        model = load_model(model_store_path, model_id)
    except NotFound:
        volume.reload()  # Fetch latest changes
        model = load_model(model_store_path, model_id)
    return model.run(request)

For more details, see our guide to storing model weights on Modal.

Model checkpointing

Checkpoints are snapshots of an ML model and can be configured by the callback functions of ML frameworks. You can use saved checkpoints to restart a training job from the last saved checkpoint. This is particularly helpful in managing preemption.

For more, see our example code for long-running training.

Hugging Face `transformers`

To periodically checkpoint into a modal.Volume, just set the Trainer’s output_dir to a directory in the Volume.

import pathlib

volume = modal.Volume.from_name("my-volume")
VOL_MOUNT_PATH = pathlib.Path("/vol")

@app.function(
    gpu="A10G",
    timeout=2 * 60 * 60,  # run for at most two hours
    volumes={VOL_MOUNT_PATH: volume},
)
def finetune():
    from transformers import Seq2SeqTrainer
    ...

    training_args = Seq2SeqTrainingArguments(
        output_dir=str(VOL_MOUNT_PATH / "model"),
        # ... more args here
    )

    trainer = Seq2SeqTrainer(
        model=model,
        args=training_args,
        train_dataset=tokenized_xsum_train,
        eval_dataset=tokenized_xsum_test,
    )

Volumes versus Network File Systems

Like the modal.NetworkFileSystem, Volumes can be simultaneously attached to multiple Modal Functions, supporting concurrent reading and writing. But unlike the modal.NetworkFileSystem, the modal.Volume has been designed for fast reads and does not automatically synchronize writes between mounted Volumes.

Volume performance

Volumes work best when they contain less than 50,000 files and directories. The latency to attach or modify a Volume scales linearly with the number of files in the Volume, and past a few tens of thousands of files the linear component starts to dominate the fixed overhead.

There is currently a hard limit of 500,000 inodes (files, directories and symbolic links) per Volume. If you reach this limit, any further attempts to create new files or directories will error with ENOSPC (No space left on device).

Filesystem consistency

Concurrent modification

Concurrent modification from multiple containers is supported, but concurrent modifications of the same files should be avoided. Last write wins in case of concurrent modification of the same file — any data the last writer didn’t have when committing changes will be lost!

The number of commits you can run concurrently is limited. If you run too many concurrent commits each commit will take longer due to contention. If you are committing small changes, avoid doing more than 5 concurrent commits (the number of concurrent commits you can make is proportional to the size of the changes being committed).

As a result, Volumes are typically not a good fit for use cases where you need to make concurrent modifications to the same file (nor is distributed file locking supported).

While a commit or reload is in progress the Volume will appear empty to the container that initiated the commit. That means you cannot read from or write to a Volume in a container where a commit or reload is ongoing (note that this only applies to the container where the commit or reload was issued, other containers remain unaffected).

For example, this is won’t work:

volume = modal.Volume.from_name("my-volume")


@app.function(image=modal.Image.debian_slim().pip_install("aiofiles"), volumes={"/vol": volume})
async def concurrent_write_and_commit():
    async with aiofiles.open("/vol/big.file", "w") as f:
        await f.write("hello" * 1024 * 1024 * 500)

    async def f():
        await asyncio.sleep(0.1)  # Wait for the commit to start
        # This is going to fail with:
        # PermissionError: [Errno 1] Operation not permitted: '/vol/other.file'
        # since the commit is in progress when we attempt the write.
        async with aiofiles.open("/vol/other.file", "w") as f:
            await f.write("hello")

    await asyncio.gather(volume.commit.aio(), f())

Busy Volume errors

You can only reload a Volume when there no open files on the Volume. If you have open files on the Volume the .reload() operation will fail with “volume busy”. The following is a simple example of how a “volume busy” error can occur:

volume = modal.Volume.from_name("my-volume")


@app.function(volumes={"/vol": volume})
def reload_with_open_files():
    f = open("/vol/data.txt", "r")
    volume.reload()  # Cannot reload when files in the Volume are open.

Can’t find file on Volume errors

When accessing files in your Volume, don’t forget to pre-pend where your Volume is mounted in the container.

In the example below, where the Volume has been mounted at /data, “hello” is being written to /data/xyz.txt.

import modal

app = modal.App()
vol = modal.Volume.from_name("my-volume")


@app.function(volumes={"/data": vol})
def run():
    with open("/data/xyz.txt", "w") as f:
        f.write("hello")
    vol.commit()

If you instead write to /xyz.txt, the file will be saved to the local disk of the Modal Function. When you dump the contents of the Volume, you will not see the xyz.txt file.

Further examples

Character LoRA fine-tuning with model storage on a Volume
Protein folding with model weights and output files stored on Volumes
Dataset visualization with Datasette using a SQLite database on a Volume