Apache Flink: Stream Processing for Real-Time Use Cases - Ohad Israeli

Описание: In this session, led by Ohad Israeli from Confluent, we will dive into the role of Apache Flink as a powerful compute layer within the modern data streaming stack. We’ll explore how Flink enables real-time processing at the point of data ingestion, unlocking significant benefits in terms of performance, scalability, and architecture simplicity.

By processing data as it arrives - rather than relying solely on downstream systems—we can achieve lower latency, greater data portability, and improved cost-efficiency. We'll examine practical use cases and architectural patterns where Flink shines, and discuss how integrating Flink early in the data pipeline can streamline operations and reduce overhead.

Whether you're building event-driven applications, real-time analytics, or modern data platforms, this session will help you understand why Flink is increasingly becoming the go-to compute engine for streaming-first architectures.

We will answer:
1. What is Apache Flink’s role in the modern data streaming stack?
2. Why should we process data at the ingestion point instead of downstream?
3. How does Flink help reduce latency in real-time data pipelines?
4. In what ways does Flink improve data portability across systems?
5. How can using Flink at the compute layer lead to cost savings?
6. What are common use cases or architectures that benefit from using Flink?
7. How does Flink compare to other stream processing frameworks?


00:00 Intro
03:01 Why stream processing is more critical than ever
06:41 How real time data changes business decisions
12:18 Why Apache Flink is becoming the de facto standard
13:34 Why flink ecosystem makes development easier
26:10 Demo and wrap up