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Data Overload Vol. 8

Data Overload Vol. 8

Welcome to Data Overload Vol. 8, the monthly newsletter with company updates from Orchest!

Orchest on Kubernetes now a reality ๐Ÿ‹

We announced a new release of Orchest powered by Kubernetes that has been a long time in the making. It will help our users scale their data pipelines with ease and deploy Orchest on their own k8s clusters, so we are beyond excited. You can read the complete announcement in our blog.

We were trending on GitHub during Data Council โญ

Our lightning talk at Data Council Austin went great, we got the opportunity to talk to a lot of likeminded people in the Data Engineering and MLOps ecosystems, and to make the experience even better, we were trending on GitHub during the event. Thanks for those stars!

Educational content ๐ŸŽ“

We want to publish top-quality educational content on our blog about Data Science and Data Engineering concepts, and we started by writing an introduction to Apache Arrow that was quite well received. Check it out!

Thank you!

Our community is growing both on GitHub and our public Slack workspace and we are receiving super useful feedback from users. Thank you all!

- Juan Luis Cano (Data Scientist Advocate)

Product updates

๐Ÿ“‚ New file manager

Fully integrated with the pipeline editor so you have more visibility of your files.

new-file-manager.gif

๐Ÿ› JupyterLab debugger

The upgrade to JupyterLab 3.2 brought a few niceties, including the debugger!

jupyterlab-debugger.gif

๐Ÿค Panning and pinching on the pipeline editor

Useful if you have a multitouch device.

zoom-pan-pipeline.gif

What we're reading

  • Using Research to Untangle Our Documentation (blog post)

    Why we like it: The Product Design team of Auth0 does an insightful walkthrough of some of the changes they did to their documentation navigation and Information Architecture to make it more consistent, and adds several useful recommendations that we will definitely keep in mind while improving our own docs.

Orchest is an open-source project that simplifies the development and deployment of data pipelines. Get started for free or download the open-source version!