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Confluent Developer Skills for Apache Kafka®
Confluent Developer Skills for Apache Kafka®

Mon, Dec 18

|

Virtual

Confluent Developer Skills for Apache Kafka®

Learn how to build event-driven applications the right way with Kafka Cluster

Time & Location

Dec 18, 2023, 9:00 AM GMT+8 – Dec 20, 2023, 5:00 PM GMT+8

Virtual

Guests

About the event

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: Dec 18, 9:00 AM GMT+8 – Dec 18, 5:00 PM GMT+8

                                 Dec 19, 9:00 AM GMT+8 – Dec 19, 5:00 PM GMT+8

                                 Dec 20, 9:00 AM GMT+8 – Dec 20, 5:00 PM GMT+8

Tickets

  • Confluent Developer Skills

    Sale ends: Dec 14, 11:50 PM GMT+8

    *Inclusive of all taxes

    $1,800.00

Total

$0.00

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