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Book synopsis

Build scalable streaming systems and event-driven platforms for modern real-time applications

Modern systems no longer operate in batches alone.

Applications today process continuous streams of events from APIs, mobile devices, transactions, sensors, user interactions, and distributed services-all in real time.

Organizations need systems that can ingest, process, react to, and analyze data the moment it arrives.

"Stream Everything" is a practical, engineering-focused guide to building real-time data platforms using Python, Apache Kafka, and modern event-driven architecture patterns.

This book teaches developers how to design scalable streaming systems that remain reliable, observable, and resilient under production workloads.

Why real-time data engineering matters

Modern systems face challenges such as:

• processing massive event streams continuously
• scaling distributed consumers reliably
• handling late, duplicated, or out-of-order events
• maintaining low-latency processing pipelines
• coordinating asynchronous services
• ensuring reliability across distributed infrastructure

Batch-oriented systems alone cannot solve these problems effectively.

Streaming architectures enable systems to react instantly and scale dynamically.

What you will learn

• fundamentals of event-driven architecture
• Kafka architecture and distributed log concepts
• producers, consumers, topics, and partitions
• stream processing with Python
• event schema design and serialization
• exactly-once and at-least-once delivery semantics
• stream reliability and fault tolerance
• asynchronous messaging and distributed workflows
• monitoring and observability for streaming systems
• deploying and scaling Kafka infrastructure

From isolated services to event-driven systems

Throughout the book, you will learn how to:

• design scalable streaming architectures
• process real-time events efficiently
• coordinate distributed services asynchronously
• build fault-tolerant data pipelines
• optimize throughput and latency
• monitor streaming systems in production
• evolve event schemas safely over time

Each chapter focuses on practical engineering workflows used in modern distributed systems teams.

Practical applications

• real-time analytics platforms
• event-driven microservices
• financial transaction processing systems
• IoT and sensor data pipelines
• fraud detection and alerting systems
• machine learning event infrastructure

These examples reflect real-world streaming and distributed systems challenges.

Who this book is for

• backend engineers
• data engineers
• platform engineers
• cloud-native developers
• distributed systems engineers
• software architects building event-driven systems

If you want to build reliable, scalable, and real-time streaming platforms with Kafka and Python, this book provides the roadmap.

Stream continuously.
Process intelligently.
Engineer systems that react in real time.

Book details

• Full title: Stream Everything
• Subtitle: Real-Time Data Processing, Event-Driven Architectures, and Kafka Engineering with Python
• Author: Richard Boozman
• Language: English
• Binding: Paperback
• Number of pages: 312
• EAN: 9798180308702
• ID: 52841207
• Publisher: Independently published
• Weight: 381 g
• Dimensions: 229 × 152 × 20 mm
• Date of publishing: 11. June 2026

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