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

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