Description
Course info
Rating
(36)
Level
Beginner
Updated
May 22, 2020
Duration
2h 9m
Description

There are a lot of common scenarios that occur when using a streaming platform inside an organization. In this course, Handling Streaming Data with a Kafka Cluster, you’ll learn to handle a variety of different scenarios you may encounter. First, you’ll explore why Kafka makes such a great solution for handling streaming data while exploring different options in terms of optimizations and integrations with other models. Next, you’ll discover how to manage your data and perform various operations against your Kafka Cluster. Finally, you’ll learn how to secure the data streams by applying different techniques. When you’re finished with this course, you’ll have the skills and knowledge of handling streaming data with Apache Kafka needed to build and manage streaming pipelines in your organization.

About the author
About the author

Bogdan Sucaciu is a Software Engineer at Axual in The Netherlands, where he is taking part in building a Streaming Platform designed to share information in real-time, enabling instant processing of incoming events. He has several years of experience "cooking" software with JVM-based languages, some flavors of web technologies and garnishing with automated testing.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi, my name is Bogdan Sucaciu, and welcome to my course, Handing Streaming Data with a Kafka Cluster. Streaming is not only about watching online videos and listening to podcasts on your favorite mobile app. You have actually already started experiencing streaming in more ways than you can imagine, probably without even realizing it. This beginner‑level course should get you started with the fascinating world of streaming data and how Apache Kafka can solve some of the most common pains encountered in large organizations. Some of the major topics that we'll cover include the basics of streaming data and why Apache Kafka can be considered a streaming platform, producing and consuming data to and from Kafka, how to manage data streams, and finally, we're going to take a look at how we can adapt non‑streaming models to work with Apache Kafka. By the end of this course, you'll be comfortable with handling different scenarios that are commonly encountered when using Apache Kafka inside your organization. There are no prerequisites for this course, but in order to ensure a smooth experience, I would recommend having some experience with the Java programming language, since I will be writing some Java code. Also, I will continuously be using Docker to keep system differences to a minimum, so it shouldn't matter if you use Windows, Linux, or Mac. From here, you should feel comfortable diving into Apache Kafka with courses on Kafka Connect, Kafka Streams, or KSQL. I hope you'll join me on this journey to learn about streaming and Apache Kafka with the Handling Streaming Data with a Kafka Cluster course, at Pluralsight.