Build reliable real time data pipelines with Debezium and Kafka that your engineers can run and your auditors can trust. Batch ETL creates stale views and brittle dual writes. Teams struggle with delayed updates, schema drift, and incident recovery that takes too long. This book shows how to stream committed database changes into Kafka, shape events for safe upserts, and operate a platform that scales without drama. Debezium event model in practice, keys, headers, and transaction metadata - Single Message Transforms for unwrapping, masking, and topic routing - Outbox pattern setup with table schema and clean SMT configuration - Kafka 4.x on KRaft, controller quorum basics, and client compatibility - Kafka Connect distributed mode, internal topics, and REST lifecycle - Exactly once for source connectors with idempotent sinks and limits - Initial and incremental snapshots with signals, scheduling, and throttling - Heartbeat topics and low traffic tables while keeping WAL and binlog healthy - Schema choices with Avro, Protobuf, and JSON Schema plus converters - Schema Registry and Apicurio policies for safe evolution and compatibility - Data contracts in CI and at runtime with validation and breaking change guards - PostgreSQL logical decoding with slots and pgoutput retention strategy - MySQL binlog and GTID setup, privileges, retention, and failover safety - SQL Server CDC enablement, retention tuning, and LSN based recovery - Oracle via LogMiner or XStream with supplemental logging, RAC and CDB notes - Cassandra CDC commit logs, per node deployment, and cdc_total_space planning - MongoDB Change Streams with pre and post images and resume tokens - Event shaping for NoSQL with stable keys and idempotent consumers - Observability with JMX and Prometheus with practical alert thresholds - Failure drills with Debezium Testcontainers and controlled chaos exercises - Security with TLS and authentication, field masking with SMTs for compliance - Streaming analytics with Flink, changelog tables, and materialized views - Cloud patterns on Confluent Cloud and MSK Connect - Debezium Server to Kinesis or Pub Sub for non Kafka targets - Migrations and disaster recovery with offset translation and blue green cutovers This is a code heavy guide with working configurations and runnable examples that map directly to production use cases, from connector JSON to Flink jobs and deployment scripts. Grab your copy today.