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Kafka

Learn Kafka as a connected topic across chapters, concepts, simulations, and interview reasoning.

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Learn Kafka as a connected topic across chapters, concepts, simulations, and interview reasoning.

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System Design
Architecture
Distributed Systems
Data Engineering

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Article 1Kafka and Spark Structured Streaming: Building a Production Pipeline📖 The 500K-Event Problem: When a Naive Kafka Consumer Falls Apart An analytics platform at a mid-sized fintech company needs to process 500,000 payment events per second from a Kafka cluster. The tea23 minArticle 2How Kafka Works: The Log That Never ForgetsTLDR: Kafka is a distributed event store. Unlike a traditional queue (RabbitMQ) where messages disappear after reading, Kafka stores them in a persistent Log. This allows multiple consumers to read th13 minArticle 3Change Feed vs Change Stream: CDC Internals, Reliability, and When to Avoid EachIn the summer of 2023, the platform team at a fast-growing e-commerce company was handling 100,000 orders per day across three microservices: Order Service, Inventory Service, and Billing Service. All49 minArticle 4The Dual Write Problem: Why Two Writes Always Fail Eventually — and How to Fix ItTLDR: Any service that writes to a database and publishes a message in the same logical operation has a dual write problem. try/catch retries don't fix it — they turn failures into duplicates. The Tra23 minArticle 5How CDC Works Across Databases: PostgreSQL, MySQL, MongoDB, and BeyondA data engineering team at a fintech company built what they believed was a robust Change Data Capture pipeline: three source databases (PostgreSQL, MongoDB, and Cassandra), Debezium connectors wired 37 minArticle 6Kappa Architecture: Streaming-First Data PipelinesTLDR: Kappa architecture replaces Lambda's batch + speed dual codebases with a single streaming pipeline backed by a replayable Kafka log. Reprocessing becomes replaying from offset 0. One codebase, n21 min

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