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Confluent Stream Processing using Apache Kafka® Streams & ksqlDB

Learn how to use Confluent ksqlDb and KStreams API to transform, enrich, filter, and aggregate streams of real-time data.

$1800

October 13 @ 9:00 am October 15 @ 5:00 pm UTC+8

About the event

Manipulating real-time data is increasingly becoming important for organizations of all sizes. With expertise in Apache Kafka® Streams and ksqlDB, you can help meet this demand.

Learn to identify patterns and use cases for real-time data and stream processing to unlock their potential. Take a deep dive into the architecture of Apache Kafka® Streams, master building apps for real-time data transformation, aggregation, and more. Get hands-on with ksqlDB, where the simplicity of SQL seamlessly meets Kafka Streams to write powerful queries.

After attending this event, you’ll be able to:

  • Develop real-time applications with Kafka Streams API.
  • Explore ksqlDB’s fault-tolerant, high-performance stream processing capabilities.
  • Learn to enrich real-time streaming data by ,filtering, transforming, aggregating, and joining data streams.
  • Gain insights into testing, securing, deploying, and monitoring applications.
  • Connect with fellow developers, architects, and data scientists.

Target Audience: This event will cater to application developers, architects, DevOps engineers, and data scientists aiming to create impactful real-time applications.

Prerequisites: Familiarity with Java (or similar languages like C# or Python) and Kafka architecture is recommended. To make the most of this event, consider taking the recommended prerequisites: Confluent Fundamentals for Apache Kafka® and Confluent Developer Skills for Building Apache Kafka®.

Don’t miss this opportunity to become a real-time data maestro. Reserve your spot today!

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
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
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