Explore strategies and techniques for managing out-of-order events in event-driven systems, ensuring accurate processing and maintaining system integrity.
Explore Apache Kafka Streams, a powerful client library for building real-time, scalable, and fault-tolerant stream processing applications within the Kafka ecosystem. Learn about setting up Kafka Streams, defining stream processing topologies, and implementing stateful operations with practical examples.
Explore the critical differences between event time and processing time in stream processing, their advantages, trade-offs, and implementation in frameworks like Apache Flink and Kafka Streams.
Explore Kafka Streams and kSQL for scalable, real-time stream processing and analytics in Apache Kafka. Learn about key features, implementation, and best practices.
Explore Apache Kafka, a distributed event streaming platform, and its role in microservices architecture. Learn about Kafka's architecture, installation, producing and consuming streams, Kafka Streams API, replication, fault tolerance, Kafka Connect, monitoring, and security features.