Learn the basics of Apache Flink® and how to get started with simple, serverless Flink!

Flink is a powerful, battle-hardened stream processor that has rapidly grown in popularity, becoming the de facto standard for stream processing and a top-five Apache project. Kai Waehner, Field CTO at Confluent, explains how Flink fits into your data streaming architecture, why stream processing is needed for real-time data, and how Flink’s underlying architecture provides a number of advantages.

From building event-driven applications to performing real-time analytics, teams that put stream processing into practice can unlock real-time use cases and save on redundant downstream processing costs. Developers choose Flink because of its performant runtime engine, resiliency for failure recovery, support for streaming and batch modes, and APIs and language flexibility. Getting started with Flink is easy and seamless using Confluent Cloud, where you can experience both Flink and Apache Kafka® on a unified, cloud-native data streaming platform.

00:00 Overview of data streaming
1:07 Why stream processing?
2:58 Introduction to Flink
5:12 A look at Flink’s architecture
7:36 Flink as a fully managed service

LEARN MORE
►Apache Flink® 101 course: https://developer.confluent.io/course...
►Get started on Confluent Cloud for free: https://www.confluent.io/get-started/

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ABOUT CONFLUENT
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

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