Explore integration issues in event-driven architecture, comparing synchronous request-response models with asynchronous messaging across microservices and cloud-native distributed systems. Learn about notification services and cross-language flexibility.

Explore how an e-commerce system with 10 million users manages concurrent requests through horizontal scaling, resource buffering, and a hybrid event-driven messaging approach versus the request-response model.

Explore how health care workflows use event-driven architecture to enable loosely coupled messaging and request-response models, supporting bookings, payments, pre-checks, and notifications through robust queuing and data buffering.

Delve into the trade-offs between synchronous and asynchronous approaches in event-driven messaging. Weigh deterministic request-response models against send-and-forget patterns to design resilient, traceable systems.

Reframe the booking flow as a notification driven architecture, using an orchestrator and message broker to emit booking confirmed events, email or sms, and enforce completion after notification is sent.

Explore how messages become events in an event driven architecture, with json payloads, event id, type, timestamp, and source, and how keys, correlation, and locality influence ordering and partitions.

Explore event driven messaging and architecture, including the observer design pattern, request-reply, and fire-and-forget. See how brokers and queues enable loose coupling and topic-based broadcasting in distributed systems.

Understand the core components of event driven architecture, including messages and events, brokers and channels, producers and consumers, and the observer pattern.

Explore queue versus topic in an event-driven microservice order system, detailing message sequencing, partitions, and Kafka-based guarantees for throughput, offset tracking, and reliable consumption.

Explore data safety in event-driven systems using a messaging broker, producer, and consumer with durable queues and acknowledgments. Learn how retention policies and persistence mitigate failures and ensure reliable delivery.

Explore RabbitMQ producer and consumer patterns, including queues, quorum, replication, and message persistence options. Practice publish and read workflows with acknowledgement modes and message IDs.

Publish and consume messages with RabbitMQ using a simple Java producer and consumer. Configure AMQP connections, exchanges, queues, routing keys, and delivery acknowledgements for reliable event driven architecture.

Explore data safety in distributed, event-driven architectures through RabbitMQ clustering, replication, and quorum strategies, comparing raft and paxos consensus to prevent single points of failure.

Learn to implement a Go-based producer and consumer for RabbitMQ, using channels for async publish to an exchange and queue with JSON messages.

Explore an event driven architecture case study for an online retailer, detailing legacy modernization with a unified message translator, channel adapters, and API-driven data flows.

Explore how change data capture enables real-time data synchronization within an event-driven architecture using CDC agents, Kafka Connect, and data virtualization to support reporting and BI from multiple sources.

Explore high availability, durability, and scalability in event-driven architectures, comparing Kafka, Kinesis, and RabbitMQ for handling millions of events, with serverless options and Kubernetes tradeoffs.

Explore how to set up a Kafka producer to send messages in an event-driven architecture, using Kafka Streams and functional programming operators to build a data pipeline.

Explore Apache Kafka as an engine with dockerized setup, Kafka UI, topics and producers and consumers, plus Kafka Streams and KTable concepts for building event-driven architectures.

Explore retry strategies and failure handling in event driven architectures, including idempotency, poison pills, and dead letter queues in RabbitMQ and Kafka.

Learn how the outbox pattern mitigates dual-write challenges in event-driven architectures by persisting events in a database table and asynchronously publishing them to Kafka.

Explore event-driven architecture by structuring a modular project with directory or package layouts, an api layer, and a core business logic wired to infrastructure and libraries.

Learn why and how event driven architecture enables streaming with Apache Kafka and RabbitMQ, detailing event payloads, headers, metadata, immutability, and traceability through correlation IDs and timestamps.

Modernize legacy systems by migrating to a modern architecture with an exposed data boundary and APIs and event streams, using asynchronous processing and change data capture with Kafka.