Confluent Stream Processing using Apache Kafka® Streams & ksqlDB

Learn how to use Confluent ksqlDb to transform, enrich, filter, and aggregate streams of real-time data using SQL-like language.

Duration

3 Days

Level

Beginner to Intermediate Level

Design and Tailor this course

Official content and labs

Edit Content

During this hands-on course, you will learn to:

Identify common patterns and use cases for real-time stream processing
Understand the high level architecture of Apache Kafka® Streams
Write real-time applications with the Kafka Streams API to filter, transform, enrich, aggregate, and join data streams
Describe how ksqlDB combines the elastic, fault-tolerant, high-performance stream processing capabilities of Kafka Streams with the simplicity of a SQL-like syntax
Author ksqlDB queries that showcase its balance of power and simplicity
Test, secure, deploy, and monitor Kafka Streams applications and ksqlDB queries

Edit Content

This course is designed for application developers, architects, DevOps engineers, and data scientists who need to interact with Kafka clusters to create real-time applications to filter, transform, enrich, aggregate, and join data streams to discover anomalies, analyze behavior, or monitor complex systems.

Edit Content

Motivation and Concepts for Streams

Motivation and Use Cases for Real-Time Streaming
High Level Comparison of Kafka Streams and ksqlDB
Stream Processing Concepts

Kafka Streams Architecture

Kafka Streams’ Place in the Kafka Ecosystem
High Level Architecture Design
Kafka Streams Data Types

Writing Kafka Streams Applications

Get streams of data into and out of Kafka with Kafka Connect and REST Proxy
Maintain data formats and ensure compatibility with Schema Registry and Avro
Build real-time streaming applications with Confluent ksqlDB & Kafka Streams

Testing Kafka Streams Applications

The Confluent Platform

Unit Tests
Integration Tests
Stress Tests
End-to-end Tests

Introduction to ksqlDB

Sample Use Cases
End-to-end Examples
Interacting with ksqlDB

Using ksqlDB

Data Manipulation
Aggregations
Testing

Deployment

Parallelism
Elasticity
Fault tolerance
Capacity planning
Troubleshooting
ksqlDB-specific considerations

Security

Security Overview
Access Control
Examples
ksqlDB-specific considerations

Monitoring

JMX
Confluent Control Center
ksqlDB-specific Considerations

Hands-on

Throughout the course, you will interact with hands-on lab exercises to reinforce stream processing concepts.

Exercises include:

Anatomy of a Kafka Streams Application
Joining Two Streams
Using the Kafka Streams Processor API
Testing a Kafka Streams Application
Using ksqlDB
Using the ksqlDB REST API
Scaling a Kafka Streams Application
Securing a Kafka Streams Application
Getting Metrics from a Kafka Streams Application
Using JConsole to monitor a Kafka Streams Application
Monitoring a Kafka Streams Application in Confluent Control Center

Edit Content

Attendees should be familiar with developing professional apps in Java (preferred), .NET, C#, Python, or another major programming language.
Additionally, students require a strong knowledge of Kafka architecture as well as knowledge of Kafka client application development, either through:

Prior experience, or
By taking the recommended prerequisites: Confluent Fundamentals for Apache Kafka® and Confluent Developer Skills for Building Apache Kafka®

Participants are required to provide a laptop computer with unobstructed internet access to fully participate in the class.

FIND YOUR COURSE

Topics

Brands

Confluent Stream Processing using Apache Kafka® Streams & ksqlDB

Duration

Level

Design and Tailor this course

our Footprints

Quick Links

our Offerings

Follow Us

Sign up for DataCouch Communications

Connect

we'd love to have your feedback on your experience so far