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You can use the command "print(client)" in your notebook to view the status of the cluster (as described in the Local Dask Cluster case). Just keep refreshing the "print(client)" command until the values of "processes" and "threads"changes from 0 to a positive number before jumping to the next cell.Pre-defined ARE Dask cluster

Pre-defined Dask cluster

If you wanted to use the ARE to directly set up a DASK cluster, (e.g., for interactive debugging over 2 nodes which is 96 cores) then you request all the resources needed when starting an ARE JupyterLab session.