How to Save State in Docker — A Data Scientist’s Guide

How to Save State in Docker — A Data Scientist’s Guide

In this post, we’re going to cover data persistence in Docker and how to get your images to interact with data outside of the container. Get started with persisting data and state when working with data science containers. A guide to data storage and persistence in Docker.

In this post, we’re going to cover data persistence in Docker and how to get your images to interact with data outside of the container. If you’re familiar with Docker or have already walked through the previous posts in this series skip to the next heading!

So far in this series, we’ve covered how to get a basic Hello World! web app built using Flask and Python and deployed using Docker. In Part 2 we walked through an end-to-end machine learning example, building a Random Forest Classifier for the Iris dataset and serving it as a prediction web app using Flask, before sharing it on the public Docker Hub repository.

In case you missed them:

Docker for data scientists — Part 1

Docker for data scientists-Part 2

Now you may not want to share your images publically in all cases. Luckily there are many options available for you to build and maintain private repositories. Each of the major cloud providers Azure, AWS, and GCP have hosted repository options that are pretty straightforward to get up and running. For those of you keen to use Azure, I’ve also written a quick guide on how to get a private repository running using Docker and the Azure CLI here:

Private Docker repositories for data science with Azure

If you’re already up and running and just want to get going with data persistence, let’s get started.


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