Dask is a parallel computing library for Python. I think of it as being like MPI without actually having to write MPI code, which I greatly appreciate!

Dask natively scales Python

Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love

https://dask.org

One of the cooler aspects of Dask is that you scale across computers/servers/nodes/pods/container/etc. This is why I say it's like MPI.

What we'll be talking about today are:

• Advantages to using Kubernetes
• Disadvantages to using Kubernetes
• Install the Dask Helm Chart
• Scale your Dask Workers Up / Down with kubectl scale
• Modify the Dask Helm Chart to add Extra Packages
• Autoscale your Dask Workers with Horizontal Pod AutoScalers

Benfits to Dask on Kubernetes

Let's talk about some of the (many!) benefits to using Kubernetes!

Customizable Configuration

Another very important aspect of Dask, at least for me, is that I can set it up so that the infrastructure side of things is completely...