A comprehensive guide to Kafka Connect — connector architecture, Debezium CDC, Single Message Transforms, exactly-once delivery, schema evolution with Schema Registry, and running at scale on Kubernetes with Strimzi.
Kafka
-
Kafka Connect Deep Dive -
Apache Pulsar vs Kafka: Architecture, Trade-offs, and When to Choose Each Architecture differences, subscription models, multi-tenancy, geo-replication, tiered storage, schema registry, and an honest decision framework for choosing between Kafka and Pulsar in 2026.
-
Change Data Capture with Debezium: Streaming Database Changes in Real Time A comprehensive guide to Change Data Capture with Debezium—covering how CDC works at the database level, setting up connectors for PostgreSQL and MySQL, routing events through Kafka, handling schema evolution, transforming records with SMTs, and building production-grade CDC pipelines.
-
Real-Time Streaming with Apache Flink: Stateful Stream Processing at Scale A deep dive into Apache Flink — stateful stream processing, windowing, exactly-once semantics, checkpointing, and deploying production Flink jobs on Kubernetes.
-
Apache Kafka Deep Dive A comprehensive guide to Apache Kafka — how it works internally, producers and consumers, partitions and consumer groups, exactly-once semantics, schema management, and running Kafka reliably in Kubernetes with Strimzi.
-
Data Pipeline Patterns: ETL vs ELT, Streaming, Batch Processing, and Orchestration A practical guide to data pipeline architecture — ETL vs ELT trade-offs, streaming with Kafka and Flink, batch transformation with dbt, and orchestration with Airflow and Dagster.
-
Event-Driven Architecture Explained Event-driven architecture trades the simplicity of a function call for loose coupling and scale, and the bill comes due in the hard parts: delivery semantics, ordering, the dual-write problem, schema evolution, and debugging a flow with no stack trace. A practical guide to what an event actually is, the patterns that work, and when not to reach for any of it.