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What is Apache Kafka® and how does it work?
Apache Kafka was built with the vision to become the central nervous system that makes real-time data available to all the applications that need to use it, with numerous use cases like stock trading and fraud detection, to transportation, data integration, and real-time analytics.
This four-part online talk series provides an overview of what Kafka is, what it's used for, and the core concepts that enable it to power a highly scalable, available and resilient real-time event streaming platform. The series begins with an introduction to the shift toward real-time data streaming, and continues all the way through to best practices for developing applications with Apache Kafka and how to integrate Kafka into your environment.
Whether you’re just getting started or have already built stream processing applications, you will find actionable insights in this series that will enable you to further derive business value from your data systems.
Register now to learn Apache Kafka from Confluent, the company founded by Kafka’s original developers.
This talk explains how companies are using event-driven architecture to transform their business and how Apache Kafka serves as the foundation for streaming data applications.
Learn how major players in the market are using Kafka in a wide range of use cases such as microservices, IoT and edge computing, core banking and fraud detection, cyber data collection and dissemination, ESB replacement, data pipelining, ecommerce, mainframe offloading and more.
Also discussed in this talk are the differences between Apache Kafka and Confluent Platform.
This session explains Apache Kafka’s internal design and architecture. Companies like LinkedIn are now sending more than 1 trillion messages per day to Apache Kafka. Learn about the underlying design in Kafka that leads to such high throughput.
This talk provides a comprehensive overview of Kafka architecture and internal functions, including:
Pick up best practices for developing applications that use Apache Kafka, beginning with a high level code overview for a basic producer and consumer. From there we’ll cover strategies for building powerful stream processing applications, including high availability through replication, data retention policies, producer design and producer guarantees.
We’ll delve into the details of delivery guarantees, including exactly-once semantics, partition strategies and consumer group rebalances. The talk will finish with a discussion of compacted topics, troubleshooting strategies and a security overview.
Integrating Apache Kafka with other systems in a reliable and scalable way is a key part of an event streaming platform. This session will show you how to get streams of data into and out of Kafka with Kafka Connect and REST Proxy, maintain data formats and ensure compatibility with Schema Registry and Avro, and build real-time stream processing applications with Confluent KSQL and Kafka Streams.