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Summary

Event Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments.

About the Technology

Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications.

About the Book

Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain.

What's inside

Validating and monitoring event streams
Event analytics
Methods for event modeling
Examples using Apache Kafka and Amazon Kinesis

About the Reader

For readers with experience coding in Java, Scala, or Python.

About the Author

Alexander Dean developed Snowplow, an open source event processing and analytics platform. Valentin Crettaz is an independent IT consultant with 25 years of experience.

Table of Contents

Part 1 - Event Streams and Unified Logs
Introducing event streams
The unified log 24
Event stream processing with Apache Kafka
Event stream processing with Amazon Kinesis
Stateful stream processing
Part 2 - Data Engineering with Streams
Schemas
Archiving events
Railway-oriented processing
Commands
Part 3 - Event Analytics
Analytics-on-read
Analytics-on-write