2.1 Inside the Kafka cluster2.2 Core concepts of data processing2.2.1 Partitioning the topic2.2.2 Processing data concurrently2.2.3 Ordering within a topic2.2.4 AsyncAPI: Capturing the architecture of topics, partitions, and more2.3 Replicating partitions2.3.1 Replica leaders and followers2.3.2 Choosing replication factor and minimal number of in-sync replicas2.3.3 Extending topic configuration with replication information2.4 Inside the topic2.4.1 Messages: Keys, values and headers2.4.2 First draft for documenting messages in AsyncAPI2.4.3 Message batches and offsets2.4.4 Physical representation of a topic2.4.5 Data retention2.4.6 Selecting the number of partitions2.4.7 Configuring topic metadata2.5 Compacted topics2.5.1 The idea of compaction2.5.2 How compaction works2.5.3 When compaction happens2.5.4 Making decisions about the compaction policy2.6 Online resources