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dev-environment

The dev-environment configuration type allows running dev environments.

Configuration files must be inside the project repo, and their names must end with .dstack.yml (e.g. .dstack.yml or dev.dstack.yml are both acceptable). Any configuration can be run via dstack apply.

Examples

Python version

If you don't specify image, dstack uses its base Docker image pre-configured with python, pip, conda (Miniforge), and essential CUDA drivers. The python property determines which default Docker image is used.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

# If `image` is not specified, dstack uses its base image
python: "3.10"

ide: vscode
nvcc

By default, the base Docker image doesn’t include nvcc, which is required for building custom CUDA kernels. If you need nvcc, set the corresponding property to true.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

# If `image` is not specified, dstack uses its base image
python: "3.10"
# Ensure nvcc is installed (req. for Flash Attention) 
nvcc: true

ide: vscode

Docker

If you want, you can specify your own Docker image via image.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

# Any custom Docker image
image: ghcr.io/huggingface/text-generation-inference:latest

ide: vscode
Private registry

Use the registry_auth property to provide credentials for a private Docker registry.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

# Any private Docker image
image: ghcr.io/huggingface/text-generation-inference:latest
# Credentials of the private Docker registry
registry_auth:
  username: peterschmidt85
  password: ghp_e49HcZ9oYwBzUbcSk2080gXZOU2hiT9AeSR5

ide: vscode

Docker and Docker Compose

All backends except runpod, vastai and kubernetes also allow to use Docker and Docker Compose inside dstack runs.

Resources

If you specify memory size, you can either specify an explicit size (e.g. 24GB) or a range (e.g. 24GB.., or 24GB..80GB, or ..80GB).

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

resources:
  # 200GB or more RAM
  memory: 200GB..
  # 4 GPUs from 40GB to 80GB
  gpu: 40GB..80GB:4
  # Shared memory (required by multi-gpu)
  shm_size: 16GB
  # Disk size
  disk: 500GB

The gpu property allows specifying not only memory size but also GPU vendor, names and their quantity. Examples: nvidia (one NVIDIA GPU), A100 (one A100), A10G,A100 (either A10G or A100), A100:80GB (one A100 of 80GB), A100:2 (two A100), 24GB..40GB:2 (two GPUs between 24GB and 40GB), A100:40GB:2 (two A100 GPUs of 40GB).

Google Cloud TPU

To use TPUs, specify its architecture via the gpu property.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

resources:
  gpu: v2-8

Currently, only 8 TPU cores can be specified, supporting single TPU device workloads. Multi-TPU support is coming soon.

Shared memory

If you are using parallel communicating processes (e.g., dataloaders in PyTorch), you may need to configure shm_size, e.g. set it to 16GB.

Environment variables

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

# Environment variables
env:
  - HF_TOKEN
  - HF_HUB_ENABLE_HF_TRANSFER=1

ide: vscode

If you don't assign a value to an environment variable (see HF_TOKEN above), dstack will require the value to be passed via the CLI or set in the current process.

For instance, you can define environment variables in a .envrc file and utilize tools like direnv.

System environment variables

The following environment variables are available in any run and are passed by dstack by default:

Name Description
DSTACK_RUN_NAME The name of the run
DSTACK_REPO_ID The ID of the repo
DSTACK_GPUS_NUM The total number of GPUs in the run

Spot policy

You can choose whether to use spot instances, on-demand instances, or any available type.

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

# Use either spot or on-demand instances
spot_policy: auto

The spot_policy accepts spot, on-demand, and auto. The default for dev environments is on-demand.

Backends

By default, dstack provisions instances in all configured backends. However, you can specify the list of backends:

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

# Use only listed backends
backends: [aws, gcp]

Regions

By default, dstack uses all configured regions. However, you can specify the list of regions:

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

# Use only listed regions
regions: [eu-west-1, eu-west-2]

Volumes

Volumes allow you to persist data between runs. To attach a volume, simply specify its name using the volumes property and specify where to mount its contents:

type: dev-environment
# The name is optional, if not specified, generated randomly
name: vscode    

ide: vscode

# Map the name of the volume to any path
volumes:
  - name: my-new-volume
    path: /volume_data

Once you run this configuration, the contents of the volume will be attached to /volume_data inside the dev environment, and its contents will persist across runs.

Instance volumes

If data persistence is not a strict requirement, use can also use ephemeral instance volumes.

Limitations

When you're running a dev environment, task, or service with dstack, it automatically mounts the project folder contents to /workflow (and sets that as the current working directory). Right now, dstack doesn't allow you to attach volumes to /workflow or any of its subdirectories.

The dev-environment configuration type supports many other options. See below.

Root reference

ide - The IDE to run.

version - (Optional) The version of the IDE.

init - (Optional) The bash commands to run.

name - (Optional) The run name.

image - (Optional) The name of the Docker image to run.

privileged - (Optional) Run the container in privileged mode.

entrypoint - (Optional) The Docker entrypoint.

working_dir - (Optional) The path to the working directory inside the container. It's specified relative to the repository directory (/workflow) and should be inside it. Defaults to "." .

home_dir - (Optional) The absolute path to the home directory inside the container. Defaults to /root. Defaults to /root.

registry_auth - (Optional) Credentials for pulling a private Docker image.

python - (Optional) The major version of Python. Mutually exclusive with image.

nvcc - (Optional) Use image with NVIDIA CUDA Compiler (NVCC) included. Mutually exclusive with image.

env - (Optional) The mapping or the list of environment variables.

setup - (Optional) The bash commands to run on the boot.

resources - (Optional) The resources requirements to run the configuration.

volumes - (Optional) The volumes mount points.

ports - (Optional) Port numbers/mapping to expose.

backends - (Optional) The backends to consider for provisioning (e.g., [aws, gcp]).

regions - (Optional) The regions to consider for provisioning (e.g., [eu-west-1, us-west4, westeurope]).

instance_types - (Optional) The cloud-specific instance types to consider for provisioning (e.g., [p3.8xlarge, n1-standard-4]).

spot_policy - (Optional) The policy for provisioning spot or on-demand instances: spot, on-demand, or auto. Defaults to on-demand.

retry - (Optional) The policy for resubmitting the run. Defaults to false.

retry_policy - (Optional) The policy for resubmitting the run. Deprecated in favor of retry.

max_duration - (Optional) The maximum duration of a run (e.g., 2h, 1d, etc). After it elapses, the run is forced to stop. Defaults to off.

max_price - (Optional) The maximum instance price per hour, in dollars.

pool_name - (Optional) The name of the pool. If not set, dstack will use the default name.

instance_name - (Optional) The name of the instance.

creation_policy - (Optional) The policy for using instances from the pool. Defaults to reuse-or-create.

termination_policy - (Optional) The policy for instance termination. Defaults to destroy-after-idle.

termination_idle_time - (Optional) Time to wait before destroying the idle instance. Defaults to 5m for dstack run and to 3d for dstack pool add.

resources

cpu - (Optional) The number of CPU cores. Defaults to 2...

memory - (Optional) The RAM size (e.g., 8GB). Defaults to 8GB...

shm_size - (Optional) The size of shared memory (e.g., 8GB). If you are using parallel communicating processes (e.g., dataloaders in PyTorch), you may need to configure this.

gpu - (Optional) The GPU requirements. Can be set to a number, a string (e.g. A100, 80GB:2, etc.), or an object.

disk - (Optional) The disk resources.

resources.gpu

vendor - (Optional) The vendor of the GPU/accelerator, one of: nvidia, amd, google (alias: tpu).

name - (Optional) The GPU name or list of names.

count - (Optional) The number of GPUs. Defaults to 1.

memory - (Optional) The RAM size (e.g., 16GB). Can be set to a range (e.g. 16GB.., or 16GB..80GB).

total_memory - (Optional) The total RAM size (e.g., 32GB). Can be set to a range (e.g. 16GB.., or 16GB..80GB).

compute_capability - (Optional) The minimum compute capability of the GPU (e.g., 7.5).

resources.disk

size - The disk size. Can be a string (e.g., 100GB or 100GB..) or an object.

registry_auth

username - The username.

password - The password or access token.

volumes[n]

name - The name of the network volume to mount.

path - The absolute container path to mount the volume at.

instance_path - The absolute path on the instance (host).

path - The absolute path in the container.

Short syntax

The short syntax for volumes is a colon-separated string in the form of source:destination

  • volume-name:/container/path for network volumes
  • /instance/path:/container/path for instance volumes