Apache Storm Training

The Apache Storm course introduces learners to a powerful open-source distributed real-time computation system originally developed by Twitter. Designed to process massive data streams with high speed and low latency, Apache Storm integrates seamlessly with the Hadoop ecosystem and relies on Apache Zookeeper for coordination. Built with Java and Clojure, it allows multiple programming languages and serves industries that require fast, reliable, and scalable stream processing.

In this course, learners will understand Storm's core architecture, including its key components Topology, Spouts, Bolts, and Streams, which work together to process data in parallel. Participants will explore how Storm clusters operate using Nimbus, Supervisor, and Zookeeper nodes, ensuring fault tolerance and efficient task execution.

The course highlights Storm's ability to process millions of tuples per second, making it ideal for real-time analytics, event processing, fraud detection, sensor monitoring, and live data pipelines. Learners will also study practical use cases from companies like Twitter, Spotify, and various e-commerce and supply chain organizations that use Storm for streaming, logging, searching, and instant data computation.

By the end of the course, participants can build, deploy, and manage real-time data-processing applications using Apache Storm and leverage its high-speed, reliable distributed computing capabilities.

• Basic knowledge of programming (Java, Clojure, or Python recommended)

• Basic understanding of how distributed systems and data processing work

• Familiarity with big data tools like Hadoop is helpful

• Basic understanding of networking and cluster computing.

• Aspiring data engineers and data scientists

• Developers interested in real-time data processing

• IT professionals working with big data and streaming applications

• Hadoop users looking to implement faster, real-time processing

• Anyone interested in building scalable, low-latency streaming solutions.