Explore the role of message queues in load balancing and distribution, enhancing scalability and reliability in event-driven systems. Learn about consumer scaling, sharding queues, message routing, and more.
Explore techniques for ensuring message reliability in event-driven systems, including message persistence, acknowledgments, duplicate handling, retry mechanisms, and more.
Explore the implementation of the Request-Reply pattern in Event-Driven Architecture, focusing on correlation identifiers, reply-to addressing, handling replies, and security considerations.
Explore the diverse use cases of the Competing Consumers pattern in Event-Driven Architecture, including high-volume order processing, real-time data ingestion, and more.
Explore data synchronization strategies in microservices, including event-driven synchronization, Change Data Capture, conflict resolution, and best practices for maintaining data consistency.
Explore choreography-based sagas in microservices, focusing on event-driven coordination, implementation of event handlers, and best practices for managing distributed transactions.
Explore the concept of Weighted Load Balancing in Event-Driven Architectures, its implementation mechanisms, advantages, disadvantages, and practical use cases.
Explore the Observer pattern's use cases in software design, including event handling, data binding, notification systems, and real-time data feeds, along with considerations and best practices for implementation.
Explore essential metrics for monitoring and optimizing consumer performance in event-driven architectures, including message throughput, processing latency, and more.
Explore techniques for identifying and resolving bottlenecks in event-driven systems, focusing on queue depth analysis, consumer performance metrics, and more.
Explore the concept of streaming in computing, its components, data flow, and real-world applications. Learn how streaming differs from batch processing and its evolution over time.
Explore the key criteria for comparing streaming frameworks, including Apache Kafka Streams, Apache Flink, and others, focusing on performance, scalability, and ease of use.
Explore strategies for ensuring consistency and reliability in streaming event-driven architectures, focusing on exactly-once semantics, idempotent processing, and state store consistency.
Explore the critical role of middleware in event-driven architecture, facilitating communication, decoupling services, enabling scalability, ensuring reliability, and more.