Scale Dask In the Cloud…In Minutes

Coiled helps data scientists use Python for ambitious problems, scale to the cloud for computing power, ease, and speed—all tuned for the needs of teams and enterprises.

Join Thousands of Users

As soon as you sign up, you’ll have access to your Coiled dashboard. You can dive right in and start spinning up Dask clusters at scale in minutes!

“Quite literally ‘burst to the cloud from your laptop’ — everything I’ve been dreaming of since grad school.”

Eric Ma

Principal Data Scientist, Moderna

Coiled users benefit from faster cluster startup times, savings on cloud costs, and running their Python workloads faster

Enterprise-Ready Dask Deployments
…In Minutes

Dask on a




  • Running Dask on your laptop is super easy.
  • Just install and go.
  • But what if you want to scale up your computations?
  • That’s when things can get messy…

Dask self-managed
on the cloud





  • Dask lets you run at scale but can be complex to set up securely.
  • You need to orchestrate many different technologies like cloud VPCs, subnets, docker registries, and secure user credentials.
  • Dask on a cluster is powerful but time-consuming to get right.

Dask with





  • Coiled manages cloud infrastructure for you, providing the simple experience of a laptop with the scalability of the cloud.
  • This way you can focus on bigger problems while Coiled handles Dask DevOps.


Launch Dask Clusters
With ONE line of code:

Once they’re created, they’ll persist and scale according to your needs.

import coiled
cluster = coiled.Cluster(n_workers=20)

Coiled lets you scale Python to the cloud using tools you’re familiar with like NumPy, pandas, scikit-learn, and Jupyter Notebooks.


Seamless Integration With Your Favorite Cloud Tools

Read data from multiple data stores and use a Coiled cluster to run machine learning and advanced analytics. Enterprises can perform machine learning and data engineering workloads on their data, wherever it is stored, using Coiled’s seamless integrations. Run Dask on your cloud environment. Get your preferred software packages on the cluster, with ease!


Use Dask in production, the way you want to.

Ok, where does Coiled actually run? You can use either our cloud or your own. We built Coiled to help you unleash the power of computationally intensive Python in the cloud. We believe you should have the time and space to solve bigger problems, not infrastructure issues.

100% of Coiled data science users get to go back to their real jobs.

“Pangeo emerged from the Xarray development group, so Dask was a natural choice. We needed a parallel computing engine that does not strongly constrain the type of computations that can be performed nor require the user to engage with the details of parallelization.”

“Coiled becomes an exceedingly useful tool when working in teams with a wide variety of expertise and seniority. Using Coiled allows all of our developers and engineers to focus on the things that they already do really well, and to expand beyond the limits of their local machines, without too much concern for what’s happening “under the hood” on an infrastructural level.”

“Coiled is amazing technology. We were able to get an initial reduction across all of our pipelines — data curation to automated experiments. We saw our processing time drop from 66 hours to 35 minutes and, with additional tuning, down to 15 minutes. We gained 64 hours and 45 minutes using Coiled and Dask.”

What can you do with Coiled?

You’re a Data Scientist

You have terabytes of parquet data. What if you could ask questions of your data as easily as you do with Pandas?

You’re a Data Engineer

You need to modernize your Spark ETL pipelines. What if you could write everything in Python and still work at scale?

You’re DevOps

You want to empower your Python teams to scale. What if you could make them happy and secure at the same time?

In all of these scenarios, Coiled is the answer. Whether you’re a data scientist, data engineer, or DevOps engineer, Coiled will solve your problems so you can get back to doing what’s important.

Scale Python Without the Deployment Headaches

Join Thousands of Users