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Use Case Guides

Welcome to the KSML Use Case Guides! These guides demonstrate how to apply KSML to solve real-world business problems and implement common stream processing patterns.

Unlike the tutorials that focus on specific KSML features, these guides take a problem-first approach, showing you how to combine various KSML capabilities to address practical use cases.

Available Use Case Guides

Data Transformation

This guide covers common data transformation patterns:

  • Format conversion (JSON to Avro, CSV to JSON, etc.)
  • Data normalization and cleansing
  • Schema evolution handling
  • Complex data transformations

Event-Driven Applications

Learn how to build event-driven applications with KSML:

  • Implementing the event sourcing pattern
  • Building event-driven microservices
  • Command-query responsibility segregation (CQRS)
  • Event notification systems

IoT Data Processing

Learn how to process IoT data streams with KSML:

  • Handling high-volume sensor data
  • Device state tracking
  • Geospatial data processing
  • Edge-to-cloud data pipelines

Real-time Analytics

Learn how to implement real-time analytics solutions with KSML:

  • Building real-time dashboards
  • Calculating key performance indicators
  • Implementing sliding window analytics
  • Detecting anomalies in streaming data

Fraud Detection

This guide demonstrates how to implement fraud detection systems:

  • Pattern recognition in transaction streams
  • Real-time risk scoring
  • Multi-factor anomaly detection
  • Alert generation and notification

How to Use These Guides

Each guide includes:

  1. Problem Statement: A clear description of the business problem or use case
  2. Solution Architecture: An overview of the KSML solution design
  3. Implementation: Step-by-step instructions with KSML code examples
  4. Testing and Validation: How to test and validate the solution
  5. Production Considerations: Tips for deploying to production environments

You can follow these guides end-to-end to implement the complete solution, or adapt specific patterns to your own use cases.

Additional Resources