Coiled helps individuals and teams manage their resources, control costs, and collaborate with one another. Team members can share resources, track usage, and consolidate billing with anyone else on the same account.

Users and accounts#

When you sign up for Coiled, an account is automatically created for your user, and the name of the account is the same as your username. For example, if you sign up with the username awesome-dev, then the awesome-dev user is automatically added to an account also named awesome-dev.

If you want to work with a team of two or more users, you can either:

  1. Add other users to your existing account by using the Team page at<YOUR-ACCOUNT-NAME>/team

  2. Reach out to us at to create an additional account to use for your team such as<YOUR-COMPANY-NAME>/team

Taking the screenshot below as an example, note that this user Kris (seen in the avatar on the top right) is viewing the Team page of the Coiled account (seen in the dropdown on the left).

Coiled team page with three users

Sharing resources#

You can create clusters, software environments, and other resources from any account of which you are a member.

To see all available accounts, select your avatar from the top right, then select Profile. The Accounts section is at the bottom of the page. In the example below, user sarah-johnson is a user on both the sarah-johnson account and the sarahs-team account.

This user has access to the sarah-johnson and the sarahs-team accounts.

In this example, the default account is sarah-johnson. You can change the account by using the account keyword argument commonly accepted in API commands.


Once you are added to an account, you can use the cloud provider resources and credentials that have already been set up for your team. Similarly, any tokens you’ve created will work for any account to which you belong (there is no need to create a new token).

For example, if sarah-johnson wants to create a cluster in sarahs-team:

import coiled

cluster = coiled.Cluster(n_workers=5, account="sarahs-team")

Or create a software environment accessible to other team members:

import coiled

    pip=["dask[complete]", "xarray==0.15.1", "numba"],

You can also configure the default account using the local coiled configuration file.

Tracking usage#

You can see usage for a single account on the Dashboard page:

A one by five table with columns for account core limit, account running cores, user core limit, user running cores, and credits remaining. Bar chart below of CPU Hours over time.

Additionally, on the Billing page (only visible to account admins) you can see more detailed information on account usage such as your credit balance, credits used, and percentage of free credits used.

Monthly billing table available for PAYG customers.

If you have added a credit card to your account, you will also have visibility into your Coiled bill for the month:

Monthly billing table available for PAYG customers.

If your usage stays below the amount of free credits, then this value will always show $0 since you don’t have to pay Coiled anything.

Managing resources#

Administrators for a Coiled team can set resource limits for team members including:

  1. Team-level vCPUs. The number of virtual CPUs that can be running for a team at a given time. If you’d like to change this setting, please reach out to us at

  2. User-level vCPUs. The number of virtual CPUs that can be running in a user’s account at a given time. You can set this limit for any user on your team from the Team page.

  3. Monthly spend. You can set this from the billing page, see Setting a spend limit below.

Setting a spend limit#


This spend limit only applies to your Coiled bill, not the bill you receive from your cloud provider.

By default, your Coiled account doesn’t have a spend limit. You can set a monthly spend limit to ensure your Coiled bill will not exceed a maximum specified value. This limit will be enforced once you have used up your free Coiled credits.

Setting spend limit

Once the spend limit is reached, users will not be able to create new clusters and running clusters will be automatically shut down. You can uncheck Shut down running clusters if spend limit reached to not impact already running clusters.