This article explains Apache Zeppelin's features, architecture, and how to deploy and customize it on Kubernetes to achieve scalability, resource isolation, multi‑tenant support, and persistent storage for interactive big‑data analytics.
This guide demonstrates how to build a Docker‑based Spark standalone environment, configure Apache Zeppelin to connect to it, and perform data analysis on local CSV files, HDFS, and streaming sources such as Twitter and Kafka, with complete code examples.
This tutorial introduces Apache Zeppelin, explains REPL and Jupyter concepts, outlines its core features and project structure, and provides step‑by‑step instructions for installing Zeppelin, creating notebooks, and connecting to databases, Spark, and Flink with practical code examples.
During a weekend project, we configured Apache Zeppelin to use HTTPS with a domain certificate, added optional mutual TLS, and modified its source code to restrict shell and Python execution, enabling the client’s security team to pass penetration testing while preserving Zeppelin’s core functionality.
