Scaling clusters

After you’re created a cluster with Coiled, you can scale it up or down using the coiled.Cluster.scale() functionality. You can input the number of desired worker nodes to scale up or down to as an integer, as in:


For example, to create a cluster with 10 workers and then scale it up to 15 workers, you would run the following commands:

import coiled

cluster = coiled.Cluster(n_workers=10)

You’ll see the new desired cluster size reflected in the Coiled dashboard, and the new worker nodes will be added and ready to receive work after they are provisioned and join the Dask cluster.


When scaling a cluster up or down with cluster.scale(), the operation will return asynchronously after the scaling request is acknowledged but before the desired cluster size is reached.

If you need to wait for the cluster to reach a specific number of workers before continuing, then you can use the client.wait_for_workers() functionality in the Dask client.


If you’re configured Coiled with a backend that runs on your own cloud account, make sure that you’ve requested a sufficient number of instances per your quota/limits to support the desired amount of compute resources that you are requesting. Otherwise, Coiled will encounter quota limits when requesting additional compute resources, and your clusters will not be able to scale up to the desired sizes.