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Full Description
Batch reports arrive too late. In a world where decisions depend on seconds, waiting for yesterday's data is no longer enough. Streaming Data Pipelines with Apache Kafka shows you how to build real-time systems that answer now, turning every event into immediate insight.
Clear streaming foundations: Understand topics, partitions, offsets, and consumer groups to start thinking entirely in events.
Kafka Connect recipes: Move data in and out of databases, queues, and SaaS systems with almost no code.
Custom connector walk-through: Capture every change from any HTTP API and keep downstream analytics continuously fresh and correct.
Stateless and stateful streams: Transform, enrich, aggregate, and join events for split-second insights users can immediately exploit.
Performance tuning toolkit: Achieve millisecond latency, sustained gigabytes-per-second throughput, and rock-solid fault tolerance in production.
Streaming Data Pipelines with Apache Kafka delivers Stefan Sprenger's fifteen years of real-time expertise in practical form.
An ongoing Excellent Toys case study guides you from first connector to fully deployed production cluster. Each chapter mixes concept briefs, tested configurations, and troubleshooting playbooks you can copy today, ready.
Finish the book able to stream database changes, enrich events, and publish actionable dashboards instantly. You will speak the language of events and deliver answers while competitors still query yesterday.
Ideal for Java developers and data scientists new to Kafka yet hungry for real-time skills.
Contents
PART 1: FUNDAMENTALS
1 GETTING INTO DATA STREAMING
2 A WALK-THROUGH KAFKA AND ITS ECOSYSTEM
PART 2: INTEGRATING STREAMING DATA PIPELINES
3 INTEGRATING DATA SYSTEMS IN REAL-TIME WITH KAFKA CONNECT
4 BUILDING CUSTOM CONNECTORS WITH KAFKA CONNECT
PART 3: TRANSFORMING DATA IN REAL-TIME
5 STATELESS TRANSFORMATIONS WITH KAFKA STREAMS
6 STATEFUL TRANSFORMATIONS WITH KAFKA STREAMS
PART 4: DEPLOYING STREAMING DATA PIPELINES
7 PACKAGING AND DEPLOYMENT
8 MONITORING
9 PERFORMANCE
10 HANDLING ERRORS IN PRODUCTION
