Kafka For Data Engineers
In this hands-on training course we will learn how to deploy and interact with Apache Kafka clusters in order to deploy reliable streaming and real time data solutions.
Apache Kafka is the leading data streaming platform which allows you to publish, distribute and consume streams of data with high performance, scalability and reliability. It is a key component for businesses which are looking to build real time user experiences, and to move from batch data processes to modern streaming architectures.
In this course we will learn how to operate and interact with Kafka, including publishing and consuming data and optimising your cluster for performance. We will also look at some of the supporting tools in the Kafka and Confluent ecosystem such as Kafka Streams.
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Introduction To Apache Kafka
In this lesson we will introduce Apache Kafka and explain some of it's key features and use cases.
Core Concepts Of Kafka
In this lesson we will introduce some of the core concepts and terminology associated with Kafka.
Setting Up Your Kafka Broker
In this lesson we will set up a Kafka broker in standalone mode.
Administering Kafka Topics
In this lesson we will learn more about Kafka Topics, including what they are and how to configure and optimise them.
Publishing Data To Kafka
In this lesson we will learn more about publishing data to Kafka using Kafka producers.
Consuming Data From Kafka
In this lesson we will learn about consuming data from Kafka.
Kafka Consumer Groups
In this lesson we will learn about Kafka Consumer Groups and how they can be used to control message flow.
In this lesson we will learn about Kafka partitions and how they help to improve parallelism and therefore performance of your Kafka deployment.
Kafka Performance Test Scripts
In this lesson we will learn about the Kafka performance test scripts, which can be used for measuring the performance of your Kafka deployment for both producers and consumers.
Introducing Kafka Streams, the component of the Kafka ecosystem which can be used for stream processing.