Stream Processing Design Patterns with Kafka Streams

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Free Online Course: Stream Processing Design Patterns with Kafka Streams provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Stream Processing Design Patterns with Kafka Streams is taught by Kumaran Ponnambalam.

Overview
  • Solve stream processing problems with Kafka Streams. Learn about using Kafka Streams and associated technologies to build stream-processing use cases leveraging popular patterns.

Syllabus
  • Introduction

    • Stream processing with Kafka
    • Prerequisites
    1. Stream Processing with Kafka Streams
    • What is stream processing?
    • Streaming opportunities and challenges
    • Streaming with Kafka Streams
    • Kafka Streams DSL
    • Setting up the exercise files
    • Setting up Kafka
    • Setting up MariaDB and Redis
    2. Streaming Analytics
    • Streaming analytics: Pattern
    • Streaming analytics: Use case design
    • Streaming analytics: Helper classes
    • Streaming analytics: Pipeline implementation
    • Streaming analytics: Results review
    3. Alerts and Thresholds
    • Alerts and thresholds: Pattern
    • Alerts and thresholds: Use case design
    • Alerts and thresholds: Helper classes
    • Alerts and thresholds: Pipeline implementation
    • Alerts and thresholds: Review
    4. Leaderboards
    • Leaderboards: Pattern
    • Leaderboards: Use case design
    • Leaderboards: Helper classes
    • Leaderboards: Pipeline implementation
    • Leaderboards: Review
    5. Real-Time Predictions
    • Real-time predictions: Pattern
    • Real-time predictions: Use case design
    • Real-time predictions: Helper classes
    • Real-time predictions: Pipeline implementation
    • Real-time predictions: Review
    6. Use Case Project
    • Use case definition
    • Design of the project
    • Code walk-through
    • Execute and analyze
    Conclusion
    • Next steps