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Exam Code: CCDAK
Exam Name: Confluent CCDAK Confluent Certified Developer for Apache Kafka
Number of questions: ~60 questions (multiple-choice and scenario-based)
Exam duration: 90 minutes (1 hour 30 minutes)
Passing Marks: ~70-75%
Format: Multiple choice (and possibly multiple response/scenario questions)
Proctoring: Remote proctor or testing center (webcam required)

Introductory Concepts
- Write code to connect to a Kafka cluster
- Distinguish between leaders and followers and work with replicas
- Explain what a segment is and explore retention
- Use the CLI to work with topics, producers, and consumers

Working with Producers

- Describe the work a producer performs, and the core components needed to produce messages
- Create producers and specify configuration properties
- Explain how to configure producers to know that Kafka receives messages
- Delve into how batching works and explore batching configurations
- Explore reacting to failed delivery and tuning producers with timeouts
- Use the APIs for Java, C#/.NET, or Python to create a Producer

Consumers, Groups, and Partitions

- Create and manage consumers and their property files
- Illustrate how consumer groups and partitions provide scalability and fault tolerance
- Explore managing consumer offsets
- Tune fetch requests
- Explain how consumer groups are managed and their benefits
- Compare and contrast group management strategies and when you might use each
- Use the API for Java, C#/.NET, or Python to create a Consumer

Schemas and the Confluent Schema Registry

- Describe Kafka schemas and how they work
- Write an Avro compatible schema and explore using Protobuf and JSON schemas
- Write schemas that can evolve
- Write and read messages using schema-enabled Kafka client applications
- Using Avro, the API for Java, C#/.NET, or Python, write a schema-enabled producer or consumer that leverages the Confluent Schema Registry

Streaming and Kafka Streams

- Develop an appreciation for what streaming applications can do for you back on the job
- Describe Kafka Streams and explore steams properties and topologies
- Compare and contrast steams and tables, and relate events in streams to records/messages in topics
- Write an application using the Streams DSL (Domain-Specific Language)

Introduction to Confluent ksqlDB

- Describe how Kafka Streams and ksqlDB relate
- Explore the ksqlDB CLI
- Use ksqlDB to filter and transform data
- Compare and contrast types of ksqlDB queries
- Leverage ksqlDB to perform time-based stream operations
- Write a ksqlDB query that relates data between two streams or a stream and a table Kafka Connect
- List some of the components of Kafka Connect and describe how they relate
- Set configurations for components of Kafka Connect
- Describe connect integration and how data flows between applications and Kafka
- Explore some use-cases where Kafka Connect makes development efficient
- Use Kafka Connect in conjunction with other tools to process data in motion in the most efficient way
- Create a Connector and import data from a database to a Kafka cluster

Design Decisions and Considerations

- Delve into how compaction affects consumer offsets
- Explore how consumers work with offsets in scenarios outside of normal processing behavior and understand how to manipulate offsets to deal with anomalies
- Evaluate decisions about consumer and partition counts and how they relate
- Address decisions that arise from default key-based partitioning and consider alternative partitioning strategies
- Configure producers to deliver messages without duplicates and with ordering guarantees
- List ways to manage large message sizes
- Describe how to work with messages in transactions and how Kafka enables transactions

Robust Development

- Compare and contrast error handling options with Kafka Connect, including the dead letter queue
- Distinguish between various categories of testing
- List considerations for stress and load test a Kafka system