Demystifying Apache Flink

Track: Frameworks

Abstract

As Data Streaming is taking over the world one event at a time, you cannot ignore it. Getting fresh and consistent data to the right place in the right format gives your company a competitive edge.
You are probably asking yourself, but what is this streaming all about? If you are new to this, don't worry; this session is for you! Join me in delving into Flink's architecture and building scalable and robust data processing pipelines for real-time data. You will learn about Flink's core concepts, like event time processing, state management, and components architecture. This session is designed for beginners but can be a suitable refreshment for experienced data streaming engineers.

Adi Polak

Adi is an experienced software engineer and people manager. For most of her professional life, she dealt with data and machine learning for transactional and analytics workloads by building large-scale systems. As a data practitioner, she developed software to solve real-world problems with Apache Spark, Kafka, HDFS, K8s, AWS, and Azure in high-throughput, high-scale production environments for companies like Akamai and Microsoft. Adi has taught Spark to thousands of students throughout the years and is the author of the successful book — Scaling Machine Learning with Spark. When not thinking up new architecture, teaching new tech or pondering on a distributed systems challenge, you can find her at the local cultural scene.