Chart version: 3.1.1
Api version: v1
App version: 1.1.5
DEPRECATED Distributed computation in Python with task scheduling
Chart Type
Set me up:
helm repo add center
Install Chart:
helm install dask center/stable/dask
Versions (0)

Dask Helm Chart - DEPRECATED

This chart is deprecated! You can find the new chart in:

helm repo add dask

Dask allows distributed computation in Python.

Chart Details

This chart will deploy the following:

  • 1 x Dask scheduler with port 8786 (scheduler) and 80 (Web UI) exposed on an external LoadBalancer (default)
  • 3 x Dask workers that connect to the scheduler
  • 1 x Jupyter notebook (optional) with port 80 exposed on an external LoadBalancer (default)
  • All using Kubernetes Deployments

Tip: See the Kubernetes Service Type Docs for the differences between ClusterIP, NodePort, and LoadBalancer.

Installing the Chart

To install the chart with the release name my-release:

helm install --name my-release stable/dask

Depending on how your cluster was setup, you may also need to specify a namespace with the following flag: --namespace my-namespace.

Default Configuration

The following tables list the configurable parameters of the Dask chart and their default values.

Dask scheduler

Parameter Description Default Dask scheduler name scheduler
scheduler.image Container image name daskdev/dask
scheduler.imageTag Container image tag 1.1.5
scheduler.replicas k8s deployment replicas 1
scheduler.tolerations Tolerations []
scheduler.nodeSelector nodeSelector {}
scheduler.affinity Container affinity {}

Dask webUI

Parameter Description Default Dask webui name webui
webUI.servicePort k8s service port 80
webUI.ingress.enabled Enable ingress controller resource false
webUI.ingress.hostname Ingress resource hostnames
webUI.ingress.tls Ingress TLS configuration false
webUI.ingress.secretName Ingress TLS secret name dask-scheduler-tls
webUI.ingress.annotations Ingress annotations configuration null

Dask worker

Parameter Description Default Dask worker name worker
worker.image Container image name daskdev/dask
worker.imageTag Container image tag 1.1.5
worker.replicas k8s hpa and deployment replicas 3
worker.resources Container resources {}
worker.tolerations Tolerations []
worker.nodeSelector nodeSelector {}
worker.affinity Container affinity {}


Parameter Description Default Jupyter name jupyter
jupyter.enabled Include optional Jupyter server true
jupyter.image Container image name daskdev/dask-notebook
jupyter.imageTag Container image tag 1.1.5
jupyter.replicas k8s deployment replicas 1
jupyter.servicePort k8s service port 80
jupyter.resources Container resources {}
jupyter.tolerations Tolerations []
jupyter.nodeSelector nodeSelector {}
jupyter.affinity Container affinity {}
jupyter.ingress.enabled Enable ingress controller resource false
jupyter.ingress.hostname Ingress resource hostnames
jupyter.ingress.tls Ingress TLS configuration false
jupyter.ingress.secretName Ingress TLS secret name dask-jupyter-tls
jupyter.ingress.annotations Ingress annotations configuration null

Jupyter Password

When launching the Jupyter server, you will be prompted for a password. The default password set in values.yaml is dask.

  password: 'sha1:aae8550c0a44:9507d45e087d5ee481a5ce9f4f16f37a0867318c' # 'dask'

To change this password, run jupyter notebook password in the command-line, example below:

$ jupyter notebook password
Enter password: dask
Verify password: dask
[NotebookPasswordApp] Wrote hashed password to /home/dask/.jupyter/jupyter_notebook_config.json

$ cat /home/dask/.jupyter/jupyter_notebook_config.json
  "NotebookApp": {
    "password": "sha1:aae8550c0a44:9507d45e087d5ee481a5ce9f4f16f37a0867318c"

Replace the jupyter.password field in values.yaml with the hash generated for your new password.

Custom Configuration

If you want to change the default parameters, you can do this in two ways.

YAML Config Files

You can change the default parameters in values.yaml, or create your own custom YAML config file, and specify this file when installing your chart with the -f flag. Example:

helm install --name my-release -f values.yaml stable/dask

Tip: You can use the default values.yaml for reference

Command-Line Arguments

If you want to change parameters for a specific install without changing values.yaml, you can use the --set key=value[,key=value] flag when running helm install, and it will override any default values. Example:

helm install --name my-release --set jupyter.enabled=false stable/dask

Customizing Python Environment

The default daskdev/dask images have a standard Miniconda installation along with some common packages like NumPy and Pandas. You can install custom packages with either Conda or Pip using optional environment variables. This happens when your container starts up.

Note: The IP:PORT of this chart’s services will not be accessible until extra packages finish installing. Expect to wait at least a minute for the Jupyter Server to be accessible if adding packages below, like numba. This time will vary depending on which extra packages you choose to install.

Consider the following YAML config as an example:

      value: numba xarray -c conda-forge
      value: s3fs dask-ml --upgrade

      value: numba xarray -c conda-forge
      value: s3fs dask-ml --upgrade

Note: The Jupyter and Dask-worker environments should have matching software environments, at least where a user is likely to distribute that functionality.