Confluent Kafka Developer study guide
Confluent Kafka Developer · Work through your exam, one topic at a time.
The Confluent Certified Developer for Apache Kafka - also referred to as CCDAK or the Confluent Kafka Developer Certification - is a vendor credential for developers who design, build, and operate applications on Apache Kafka and the Confluent data streaming platform. It fits backend engineers, data engineers, and platform developers who already write producer and consumer code and now need to demonstrate they can do it correctly, safely, and at scale. The exam is delivered in multiple choice and multiple response format across four domains, each weighted equally at 25 percent: Kafka Fundamentals; Kafka Application Design; Building Data Pipelines with Kafka; and Confluent Platform and Cloud Components, which covers Schema Registry, Connect, stream processing, and governance. Because the weighting is flat, no single strong domain can carry a passing result - a weak area costs exactly as much as a strong one earns. The Confluent Kafka Developer study guide has 4 sections and about 1,267 words.
01Kafka Fundamentals
A Kafka topic is a named, partitioned, replicated append-only log. Each partition is an ordered sequence with monotonically increasing offsets ; ordering is guaranteed only within a partition, never across a topic.
319 words, about 2 min02Kafka Application Design
Partitioning: the record key is hashed (murmur2) to pick a partition, so the key controls ordering and distribution. A null key uses the sticky partitioner - good for throughput, useless for ordering.
320 words, about 2 min03Building Data Pipelines with Kafka
A worker runs connectors , each split into tasks ( tasks.max ) that do the actual copying. In distributed mode the cluster state lives in Kafka itself: config.storage.topic , offset.storage.topic (compacted), and status.storage.topic .
319 words, about 2 min04Confluent Platform and Cloud Components
Schemas are registered under a subject and assigned a globally unique ID per version. The default subject naming strategy is TopicNameStrategy ( <topic -key , <topic -value ); alternatives are RecordNameStrategy (schema per record type, good for shared event types) and TopicRecordNameStrategy (per topic+type).
309 words, about 2 min