Distributed computing is hard, distributed debugging is even harder. Dask tries to simplify this process as much as possible. Coiled adds additional observability features for your Dask clusters and processes them to help users understand their workflows better.| Blog
The cloud offers amazing scale, but it can be difficult for Python data developers to use. This post walks through how to use Coiled Functions to run your existing code in parallel on the cloud with minimal code changes.Comparing code runtime between a laptop, single cloud VM, and multiple cloud VMs in parallel| Blog
Patrick Hoefler| Blog
While it’s trivial to measure the end-to-end runtime of a Dask workload, the next logical step - breaking down this time to understand if it could be faster - has historically been a much more arduous task that required a lot of intuition and legwork, for novice and expert users alike. We wanted to change that.Populated Fine Performance Metrics dashboard| Blog
Coiled Functions make it easy to improve performance and reduce costs by moving your computations next to your cloud data.| Blog
Patrick Hoefler| Blog
Patrick Hoefler| Blog
Patrick Hoefler, Hendrik Makait| Blog
We recently pushed out a new, experimental notebooks feature for easily launching Jupyter servers in the cloud from your local machine. We’re excited about Coiled notebooks because they:| Blog
Hendrik Makait2023-05-16| Blog
At Coiled we develop Dask and automatically deploy it to large clusters of cloud workers (sometimes 1000+ EC2 instances at once!). In order to avoid surprises when we publish a new release, Dask needs to be covered by a comprehensive battery of tests — both for functionality and performance.Nightly tests report| Blog
You can use Coiled Run| phofl.github.io
We recently pushed out two new and experimental features Coiled Jobs| phofl.github.io
We recently pushed out two new and experimental features coiled jobs| phofl.github.io
Getting notified of a significant performance regression the day before release sucks, but quickly identifying and resolving it feels great!| phofl.github.io