Deprecated

This chart has been deprecated.

See the chart in stable/dask instead.

Dask Distributed Helm Chart

Dask Distributed allows distributed computation in Python the chart also includes a single user Jupyter Notebook.

This chart will do the following:

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

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

bash

$ helm install --name my-release stable/dask-distributed

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

Parameter	Description	Default
`worker.name`	Dask worker name	`dask-worker`
`worker.image`	Container image name	`daskdev/dask`
`worker.imageTag`	Container image tag	`1.5.1_v3`
`worker.replicas`	k8s hpa and deployment replicas	`3`
`worker.replicasMax`	k8s hpa max replicas	`10`
`worker.component`	k8s selector key	`dask-worker`
`worker.containerPort`	Container listening port	`7077`
`worker.resources`	Container resources	`{}`

Specify each parameter using the --set key=value[,key=value] argument to helm install.

Alternatively, a YAML file that specifies the values for the parameters can be provided while installing the chart. For example,

bash

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

Tip: You can use the default values.yaml