Course Outline

Introduction

  • Kafka vs Spark, Flink, and Storm

Overview of Kafka Streams Features

  • Stateful and stateless processing, event-time processing, DSL, event-time based windowing operations, etc.

Case Study: Kafka Streams API for Predictive Budgeting

Setting up the Development Environment

Creating a Streams Application

Starting the Kafka Cluster

Preparing the Topics and Input Data

Options for Processing Stream Data

  • High-level Kafka Streams DSL
  • Lower-level Processor

Transforming the Input Data

Inspecting the Output Data

Stopping the Kafka Cluster

Options for Deploying the Application

  • Classic ops tools (Puppet, Chef and Salt)
  • Docker
  • WAR file

Troubleshooting

Summary and Conclusion

Requirements

  • An understanding of Apache Kafka
  • Java programming experience
  7 Hours
 

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Testimonials

Recalling/reviewing keypoints of the topics discussed.

Paolo Angelo Gaton - SMS Global Technologies Inc.

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Roxane Santiago - SMS Global Technologies Inc.

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