High-Performance Data Visualization with Datashader and Dask

Address performance issues for large-scale data visualizations by making smart choices about cluster memory, data types and data partitioning.

Prioritizing Pragmatic Performance for Dask

This article will go into a few things that I think are great ideas, but are not yet major bottlenecks and why. Then it will go into a few things that I think are less-than-exciting-but-really-important improvements for common workloads.

Cost Savings with Dask and Coiled

Coiled can often save money for an organization running Dask. This article goes through the most common ways in which we see that happen. 

How Popular is Matplotlib?

Anecdotally the Matplotlib maintainers were told "About 15% of arXiv papers use Matplotlib" arXiv is the preeminent repository for scholarly preprint articles. It stores millions of journal articles used across science. It's also public access, and so we can just scrape the entire thing given enough compute power.

Why we passed on Kubernetes

Kubernetes is great if you need to organize many always-on services and have in-house expertise, but can add an extra burden and abstraction when deploying a single bursty service like Dask, especially in a user environment with quickly changing needs.‍

Coiled Cloud Architecture

Over the last couple of years, Coiled has made a cloud-SaaS application that runs Dask for folks smoothly and securely in the cloud. We thought you would like to hear a bit about the choices we made and why.

Enterprise Dask Support

Along with the Cloud SaaS product, Coiled sells enterprise support for Dask. This article will be a more informal description of how we operate and why.

Dask vs Spark | Dask as a Spark Replacement

This article discusses the problems users looking for a Spark/Databricks replacement face, the relative strengths of Dask/Coiled for large-scale ETL processing, and also the current shortcomings.

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