Real-Time Data Streaming: Architectures and Patterns
Learn real-time streaming architectures like Lambda, Kappa, CDC, and event sourcing. Understand when to choose streaming over batch processing.
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Learn real-time streaming architectures like Lambda, Kappa, CDC, and event sourcing. Understand when to choose streaming over batch processing.
Learn how to implement Dead Letter Queues in Kafka to gracefully handle failed messages with retry strategies, monitoring, and production patterns.
Master Kafka multi-cluster replication using MirrorMaker 2 with active-passive and active-active topologies, offset sync, and disaster recovery.
Build production-grade data pipelines using Kafka Connect, Debezium CDC, sink connectors, schema evolution, and dead letter queues for robust error handling.
Master event-driven architecture patterns including event sourcing, CQRS, and the saga pattern using Apache Kafka for real-world microservices systems.
Understand Kafka's three delivery guarantees, idempotent producers, transactional writes, and when you actually need exactly-once semantics in production.
Understand why Kafka is removing ZooKeeper, how KRaft consensus works, and master cluster operations including broker management and disaster recovery.
Learn the essential Kafka metrics to monitor, alerting strategies, operational tools like Prometheus and Grafana, and capacity planning for production clusters.
Explore how Netflix, Uber, LinkedIn, and others use Apache Kafka in production for recommendations, pricing, fraud detection, IoT, and log aggregation.
Master Kafka Connect for integrating external systems with Kafka using source and sink connectors, Debezium CDC, JDBC, Elasticsearch, REST API management, and SMTs.
A detailed look at Kafka's internal architecture — broker clusters, KRaft consensus, replication protocols, partition leadership, log segments, and how they combine to deliver fault tolerance at scale.
Master Kafka consumers and consumer groups including poll loops, offset management, rebalancing strategies, and partition assignment with Python and Java examples.
Step-by-step guide to running Apache Kafka locally using KRaft mode binaries and Docker Compose — includes Schema Registry, Kafka UI, topic creation, and CLI producer/consumer testing.
Master Apache Kafka performance tuning with partition strategies, producer and consumer optimization, compression trade-offs, and real-world architecture patterns.
Learn how Kafka producers work including batching, partitioning, serialization, delivery guarantees, and idempotent production with Python and Java examples.
Learn how Confluent Schema Registry manages Avro schemas for Kafka producers and consumers, enabling safe schema evolution and decoupled services.
Configure SSL/TLS encryption, SASL authentication with SCRAM-SHA-256, and ACL authorization to secure your Apache Kafka cluster in production.
Learn Kafka Streams for real-time data processing including KStream, KTable, windowed aggregations, joins, exactly-once semantics, and state stores with Java examples.
A deep dive into Kafka's core data model — how topics organize data, how partitions enable parallelism and ordering, how offsets track consumer progress, and how retention and compaction manage storage.
A practical introduction to Apache Kafka — what it is, why it exists, its core concepts, and how it differs from traditional message queues. Includes your first producer and consumer code.
Compare RabbitMQ, Apache Kafka, and Amazon SQS with working code examples, architecture diagrams, and decision criteria for choosing the right message queue.
Compare popular message brokers across delivery guarantees, ordering, throughput, and operations to pick the right tool for the job.
A senior-engineer comparison of Kafka and RabbitMQ: log vs queue semantics, throughput, ordering, retention, and the real selection criteria.