When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
Confluent Stream Processing using Apache Kafka Streams & KSQL
In this three-day, hands-on training course, you will learn how to use Confluent KSQL to transform, enrich, filter and aggregate streams of real-time data using a SQL-like language. You will learn to...
Read MoreIn this three-day, hands-on training course, you will learn how to use Confluent KSQL to transform, enrich, filter and aggregate streams of real-time data using a SQL-like language. You will learn to use the Streams library to build applications, and then learn how to test, monitor, secure, scale and integrate them.
Skills Gained
During this instructor-led, 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 KSQL combines the elastic, fault-tolerant, high-performance stream processing capabilities of Kafka Streams with the simplicity of a SQL-like syntax
- Author KSQL queries that showcase its balance of power and simplicity
- Test, secure, deploy, and monitor Kafka Streams applications and KSQL queries
Who Can Benefit
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.
Prerequisites
Attendees should be familiar with developing professional apps in Java (preferred), .NET, C#, Python, or another major programming language. Participants are required to provide a laptop computer with unobstructed internet access to fully participate in the class.
Additionally, students require a strong knowledge of the 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.
Course Details
Hands-on Training
Throughout the course, you will interact with hands-on lab exercises to reinforce stream processing concepts. Some exercises include:
- Anatomy of a Kafka Streams Application
- Joining Two Streams
- Using the Kafka Streams Processor API
- Testing a Kafka Streams Application
- Using KSQL
- Using the KSQL 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
Course Outline
Motivation and Concepts for Streams
- Motivation and Use Cases for Real-Time Streaming
- High Level Comparison of Kafka Streams and KSQL
- 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
- Anatomy of a Kafka Streams Application
- Kafka Streams DSL — Stateless Operations
- Kafka Streams DSL — Aggregations
- Kafka Streams DSL — Windowed aggregations
- Kafka Streams DSL — Joins
- Kafka Streams DSL — Summary
- Processor API
- Optimizations
Testing 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 KSQL & Kafka Streams
The Confluent Platform
- Unit Tests
- Integration Tests
- Stress Tests
- End-to-end Tests
Introduction to KSQL
- Sample Use Cases
- End-to-end Examples
- Interacting with KSQL
Using KSQL
- Data Manipulation
- Aggregations
- Testing
Deployment
- Parallelism
- Elasticity
- Fault tolerance
- Capacity planning
- Troubleshooting
- KSQL-specific considerations
Security
- Security Overview
- Access Control
- Examples
- KSQL-specific considerations
Monitoring
- JMX
- Confluent Control Center
- KSQL-specific Considerations
