Confluent Developer Skills for Apache Kafka®

Join Our Apache Kafka® Application Development Event

Unlock the world of seamless application development for Apache Kafka® at our upcoming public event! Whether you're an application developer, architect, or programming enthusiast, this event is your gateway to mastering Apache Kafka® integration.

Discover the art of application development, leveraging the prowess of Apache Kafka®:

Language Inclusivity: While we use Java in our examples during the event, developers skilled in C# and Python can also thrive.

Calling all professional app developers fluent in Java (preferred), C#, or Python, who aspire to elevate their skills in Apache Kafka® integration. A solid experience in application development within your chosen language is recommended. A working knowledge of Apache Kafka® architecture would be an added advantage. You can gain this either through prior experience or by taking the "Confluent Fundamentals for Apache Kafka®" course.

Broaden Your Skills: Even if Java isn't your primary language, you'll find immense value and growth opportunities in the event.

By joining us, you'll:

• Learn from Experts: Gain insights from seasoned professionals proficient in Apache Kafka® application development.
• Hands-On Skill Enhancement: Engage in practical exercises simulating real-world scenarios to deepen your understanding.
• Networking Opportunities: Connect with fellow developers and architects, fostering collaborations and knowledge exchange.

Join us and step into the world of proficient Apache Kafka® application development. Secure your spot now for an enlightening learning journey!

Topics Covered

Fundamentals of Apache Kafka®

• Explain the value of a *Distributed Event Streaming Platform*
• Explain how the “log” abstraction enables a distributed event streaming platform
• Explain the basic concepts of:    
• Brokers, Topics, Partitions, and Segments
• Records (a.k.a. Messages, Events)
• Retention Policies
• Producers, Consumers, and Serialization
• Replication
• Kafka Connect

Producing Messages to Kafka

• Sketch the high level architecture of a Kafka producer
• Illustrate key-based partitioning
• Explain the difference between `acks=0`, `acks=1`, and `acks=all`
• Configure `delivery.timeout.ms` to control retry behavior
• Create a custom `producer.properties` file
• Tune throughput and latency using batching
• Create a producer with Confluent REST Proxy

Consuming Messages from Kafka

• Describe Kafka schemas and how they work
• Use the Confluent Schema Registry to guide schema evolution
• Write and read messages using schema-enabled Kafka

Schema Management in Apache Kafka®

Stream Processing with Kafka Streams

• Compare KStreams to KTables
• Create a Custom `streams.properties` file
• Explain what co-partitioning is and why it is important
• Write an application using the Streams DSL (Domain-Specific Language)

Data Pipelines with Kafka Connect

• Explain the motivation for Kafka Connect
• List commonly used Connectors
• Explain the differences between standalone and distributed mode
• Configure and use Kafka Connect

Event Streaming Apps with ksqlDB

• Use ksqlDB to filter and transform a stream
• Write a ksqlDB query that joins two streams or a stream and a table
• Write a ksqlDB query that aggregates values per key and time window
• Write Push and Pull queries and explain the differences between them
• Create a Connector with ksqlDB

Design Decisions

• List ways to avoid large message sizes
• Decide when to use ksqlDB vs. Kafka Streams vs. Kafka Connect SMTs
• Explain differences and tradeoffs between processing guarantees
• Address decisions that arise from key-based partitioning
• Authenticate a client app with a secure Kafka cluster

Confluent Cloud

• Explain what “fully-managed” means in the context of Confluent Cloud
• Authenticate a Kafka client to Confluent Cloud
• Do basic operations with the `ccloud` CLI

Hands-on

The hands-on lab exercises in the course follow the coherent story of building and upgrading a driver location app. Throughout the course concepts are applied directly to a working application. Exercises are available in Java, C# and Python. Exercises include:

• Working with Kafka command line tools
• Producing driver location data to Kafka and consuming that data in real-time
• Refactoring the application to use Avro and Schema Registry
• Creating a Kafka Streams application to do real-time distance aggregation
• Extracting a table from an external database into Kafka using Kafka Connect
• Creating a full event streaming application using ksqlDB that enriches driver location data with driver profile data
• Experimenting with semantic partitioning

DATES & TIMES: May 20, 2024, 9:00 AM GMT+8 – May 20, 2024, 5:00 PM GMT+8

                                 May 21, 2024, 9:00 AM GMT+8 – May 21, 2024, 5:00 PM GMT+8

                                 May 22, 2024, 9:00 AM GMT+8 – May 22, 2024, 5:00 PM GMT+8