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The CCDAK exam covers a wide range of topics, including Kafka architecture, data modeling, stream processing, and security. CCDAK examination comprises multiple-choice questions and hands-on exercises that require the candidate to demonstrate their practical knowledge of Kafka. Successful completion of the CCDAK exam certifies that the individual has the expertise to design, build, and maintain Kafka-based solutions, making them a valuable asset to any organization that uses Kafka for data processing and messaging.
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Apache Kafka has emerged as the leading distributed streaming platform in the IT industry, enabling businesses to handle real-time data feeds, messaging, and stream processing. The Confluent Certified Developer for Apache Kafka (CCDAK) certification examination is an industry-recognized validation of one's knowledge and experience with the Kafka platform. It is intended for developers who work with Kafka and have a thorough understanding of its architecture, design, configuration, and management.
The CCDAK certification exam is a comprehensive and globally recognized certification program that validates an individual's knowledge and skills in Apache Kafka technology. It is designed for developers who work with Kafka and want to demonstrate their expertise in the field. Achieving the certification is a valuable asset for both individuals and organizations, as it ensures that developers have the necessary skills to develop and maintain Kafka-based applications.
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Confluent CCDAK (Confluent Certified Developer for Apache Kafka) Certification Exam is a globally recognized certification exam that tests the expertise of developers in Apache Kafka. Apache Kafka is an open-source distributed event streaming platform that is widely used by companies for building real-time data pipelines and streaming applications. The CCDAK exam is designed to test the knowledge and skills of developers in building and managing Kafka-based applications.
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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Developing with Kafka Consumers | 15-20% | - Deserialization - Offset Management - Consumer Interceptors - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Multi-threaded Consumers - Commit Strategies (Auto, Manual, Cooperative) |
| Schema Management | 5-10% | - Schema Registration and Retrieval - Protobuf and JSON Schemas - Schema Registry Architecture - Schema Evolution and Compatibility - Avro Schemas |
| Monitoring and Operations | 5-10% | - Log Compaction - Kafka Metrics and Monitoring - Consumer Lag and Health Checks - Disaster Recovery - Cross-region Replication |
| Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Broker Configuration Parameters - Partition Assignment Strategies |
| Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms - Source and Sink Connectors - Offset Management in Connect - Connector Configuration |
| Security | 5-10% | - Authorization (ACLs) - Encryption in Transit - Authentication (SASL, SSL/TLS) - Securing Schema Registry |
| Kafka Streams | 20-25% | - Interactive Queries - Transformation Operations (map, filter, join, aggregate) - State Stores and Processors - Windowed Operations (Tumbling, Hopping, Session) - Testing Kafka Streams Applications - Streams Architecture and Topology - Exactly-Once Processing |
| Developing with Kafka Producers | 15-20% | - Producer Configuration and Tuning - Idempotent Producers - Partitioning Strategies - Producer Interceptors - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) - Error Handling and Retry Logic |
| Kafka Fundamentals | 10-15% | - Topics, Partitions, and Offsets - Log Segments and Retention - Brokers and Clusters - Replication Factor and ISR - Producer and Consumer Basics |
