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

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

From building eventdriven applications to performing realtime analytics, teams that put stream processing into practice can unlock realtime 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, cloudnative 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/getstarted/

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

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