👋 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.
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)
# 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")