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INDUSTRY
TRAINING TYPECOURSEOR URL

Confluent Stream Processing using
Apache Kafka® Streams and ksqlDB
Course Objectives

Prerequisites

The lessons and activities in this course enable participants toAttendees should be familiar with developing professionalbuild the skills to:apps in Java (preferred), .NET, C#, Python, or another major• Identify common patterns and use cases for real-time

programming language.

stream processing• Describe the high-level architecture of Apache Kafka Streams• Write real-time applications with the Kafka Streams API tofilter, transform, enrich, aggregate, and join data streams• Describe how ksqlDB combines the elastic, fault-tolerant,
high-performance stream processing capabilities of KafkaStreams with the simplicity of a SQL-like syntax• Author ksqlDB queries that showcase their balance of powerand simplicity• Test, secure, deploy, and monitor Kafka Streams applications
and ksqlDB queries

Hands-on Training• It is highly encouraged for key members of the team tocomplete training beforehand to ensure familiarity with therelevant concepts. Visit www.confluent.io/training to learn thefundamentals of data streaming and Apache Kafka
Participants are required to provide a laptop computer withunobstructed internet access to fully participate in the class.
To sign-up for one of our courses, visit us here.

Who Should Attend?
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.

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

Exercises include:• Exploring the 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© 2022 Confluent, Inc. | Confluent.io1

Datasheet | Confluent Stream Processing using Apache Kafka Streams and ksqlDB

Content

This course will enable your skills to:

Introduction toKafka Streams• Gain a better understanding of the fundamentals of Apache Kafka• Delve into how Apache Kafka uses the group management protocol to balance resources• Give a description of some Stream Processing concepts

Working withKafka Streams• Describe the anatomy of a Kafka Streams application

Introduction toksqlDB• Examine end-to-end examples for using ksqlDB• Write a streams application employing components of the Kafka Streams DSL—stateless and statefultransformations, and optimizations• Interact with ksqlDB• Integrate connectors with ksqlDBUsing ksqlDB• Perform data transformations with ksqlDB• Exploring scalar and table functions in ksqlDB• Review the concept of time in Apache Kafka Streams
StatefulTransformation• Use the stateful operations of windowing, aggregations, and joins with Kafka Streams and ksqlDB
Using Kafka Streams
and ksqlDB

Advanced Concepts• Explore foreign key joins in Kafka Streams• Creating user-defined functions with ksqlDB• Use the Kafka Streams Processor API

Testing, Monitoring• Perform testing with Apache Kafka Streams

and Troubleshooting• Evaluate some of the options available for monitoring with JMX, Confluent Control Center, and explain someksqlDB-specific considerations• Discuss common errors and troubleshooting approaches
Deployment
Strategies andSecurity Basics• Discuss these deployment strategies and describe when to use them: parallelism, capacity planning, elasticity, fault
tolerance, and ksqlDB-specific considerations• Explore the security basics needed to begin to design your security architecture:• Security overview• Access Control examples

Visit confluent.io/training for more information.

© 2022 Confluent, Inc. | Confluent.io2