Scaling Jupyter Notebooks for Data Science

This chapter explores the evolution of Jupyter Notebook and its ecosystem, focusing on scalable solutions like JupyterHub and Enterprise Gateway for data science applications. The discussion highlights how these tools facilitate multi-user environments, efficient resource management, and the integration of computing frameworks such as Spark and Kubernetes. Additionally, it addresses customization trends, challenges in functionality, and the advantages of enhanced UI in JupyterLab for improved workflow efficiency.