Developing Real-Time Data Pipelines with Apache Kafka
Speaker: Joe Stein Big Data Track Slides: http://www.slideshare.net/SpringCentr... Developing Real-Time Data Pipelines with Apache Kafka http://kafka.apache.org/ is an introduction for developers about why and how to use Apache Kafka. Apache Kafka is a publish-subscribe messaging system rethought of as a distributed commit log. Kafka is designed to allow a single cluster to serve as the central data backbone. A single Kafka broker can handle hundreds of megabytes of reads and writes per second from thousands of clients. It can be elastically and transparently expanded without downtime. Data streams are partitioned and spread over a cluster of machines to allow data streams larger than the capability of any single machine and to allow clusters of coordinated consumers. Messages are persisted on disk and replicated within the cluster to prevent data loss. Each broker can handle terabytes of messages. For the Spring user, Spring Integration Kafka and Spring XD provide integration with Apache Kafka.

High Performance Stream Processing

Building microservices with event sourcing and CQRS

DDD & REST - Domain Driven APIs for the web - Oliver Gierke

Hadoop - Just the Basics for Big Data Rookies

I can't believe it's not a queue: Using Kafka with Spring

Developing microservices with aggregates - Chris Richardson

Spring Office Hours: S5E16 - May Release Train Shift & What's Coming in Spring Boot 4.1

Apache Spark for Big Data Processing

Architecting for cloud native data: Data Microservices done right using Spring Cloud

Securing Microservices with Spring Cloud Security

Reactive Kafka

Event-Driven Architectures for Spring Developers

From Zero to Hero with Spring Boot - Brian Clozel

Spring For Apache Kafka

REST-Ful API Design

