Coiled Docs¶
👋 Welcome to Coiled’s documentation!
What is Coiled?¶
Coiled provides cluster-as-a-service functionality to provision hosted Dask clusters on demand. It takes the DevOps out of data science and enables data engineers and data scientists to spend more time on their real job and less time setting up networking, managing fleets of Docker images, creating AWS IAM roles, etc.
Hosted Dask Clusters
Securely deploy Dask clusters from anywhere you run Python.
Software Environments
Build, manage, and share conda, pip, and Docker environments. Use them locally or in the cloud.
Manage Teams & Costs
Manage teams, collaborate, set resource limits, and track costs.
Coiled at a glance¶
Coiled manages Dask clusters and everything you need to scale Python in the cloud robustly and easily. Learn more in the Dask clusters docs.
# Launch a cluster with Coiled
import coiled
cluster = coiled.Cluster(
n_workers=5,
worker_cpu=4,
worker_memory="16 GiB",
)
# Connect Dask to your cluster
from dask.distributed import Client
client = Client(cluster)
Coiled helps you manage software environments by building Docker images from pip and conda environment files for you. Learn more in the software environment docs.
# Create a custom "ml-env" software environment
# with the packages you want
import coiled
coiled.create_software_environment(
name="ml-env",
conda=["dask", "scikit-learn", "xgboost"],
)
# Create a Dask cluster which uses your "ml-env"
# software environment
cluster = coiled.Cluster(software="ml-env")