Admin-mandated adaptive scaling

[cslovell]

For those of us in public sector research groups where costs are always an issue, having the ability to run a cluster that mandates adaptive scaling for key user groups would be a fantastic feature that would enable more unrestricted usage. Something like this comes to mind. The idea would be that this would "disable" the ability to "fix" the size of a cluster, and it would always run in adaptive mode.

dask-gateway:
  gateway:
    extraConfig:
      optionHandler: |
        from dask_gateway_server.options import Options, Integer, Float, String
        import logging
        def cluster_options(user):  
            def option_handler(options):
                if ":" not in options.image:
                    raise ValueError("When specifying an image you must also provide a tag")
                extra_labels = {
                    "hub.jupyter.org/username": user.name,
                    "dask/username": user.name,
                }
                if "dask-high-compute-users" in user.groups:
                  return {
                      "worker_cores": options.worker_cores,
                      "worker_memory": int(options.worker_memory * 2 ** 30),
                      "image": options.image,
                      "scheduler_extra_pod_labels": extra_labels,
                      "worker_extra_pod_labels": extra_labels,
                      "cluster_max_workers": 32,
                  }
                else: 
                  return {
                    "worker_cores": options.worker_cores,
                      "worker_memory": int(options.worker_memory * 2 ** 30),
                      "image": options.image,
                      "scheduler_extra_pod_labels": extra_labels,
                      "worker_extra_pod_labels": extra_labels,
                      "cluster_max_workers": 32,
                      "apative":  true, 
                      "adaptive_min_workers": 0,
                    }
            return Options(
                Float("worker_cores", default=0.8, min=0.8, max=0.8, label="Worker Cores"),
                Float("worker_memory", default=3.3, min=3.3, max=3.3, label="Worker Memory (GiB)"),
                String("image", default="pangeo/base-notebook:2021.05.04", label="Image"),
                handler=option_handler,
            )
        c.Backend.cluster_options = cluster_options