Tag: event-driven

How to build loosely coupled systems using events, event buses, message brokers, and event sourcing for growth-ready asynchronous communication between services.

Design event-driven microservices with message brokers, event sourcing, CQRS, and eventual consistency patterns.

Build an event-sourced system with CQRS separation using Python, event store persistence, projection rebuilds, snapshots, and idempotent event handlers for audit-ready architectures.

Build growth-ready event-driven systems using Apache Kafka with producers, consumers, consumer groups, and exactly-once semantics for reliable asynchronous messaging

Create Kafka consumer groups in Python with partition assignment, offset management, commit strategies, rebalance handling, and exactly-once semantics for scalable stream processing.

Use the transactional outbox pattern to reliably publish domain events alongside database changes, with a relay processor, polling strategies, and exactly-once delivery guarantees.

How to design loosely coupled systems using serverless functions triggered by events from message queues, databases, and webhooks.

Process SQS messages with Lambda using batch windows, partial batch responses, error handling, and dead-letter queues for resilient event-driven pipelines.

Capture and publish major occurrences within a domain model to decouple side effects from core business logic and enable reactive workflows.

Replicate state changes across services by publishing events that carry the full updated entity state, enabling consumers to maintain their own local copies without querying the source.

Process messages from a queue exactly once regardless of duplicates by using idempotent operations, unique identifiers, and deduplication strategies at the consumer level.

Use a dedicated inbox table or queue to record incoming events or requests, ensuring reliable delivery, deduplication, and idempotent processing even when downstream systems fail.

Define a subscription mechanism to notify multiple objects about events. A behavioral design pattern for event-driven communication.

Broadcast events to multiple independent subscribers. Publishers send messages to a topic without knowing which subscribers exist, enabling loose coupling between producers and consumers.

Compare sync vs async communication patterns for microservices. Covers REST, gRPC, message queues, event-driven, service mesh, and when to use each.

A practical guide to event-driven architecture: events vs commands, message brokers, patterns like CQRS and Saga, and when to choose async over sync.

A detailed analysis into Event Sourcing: persist state changes as events, reconstruct aggregates from history, and build audit trails by design.

A practical guide to serverless architecture: function design, cold starts, event-driven patterns, state management, and common pitfalls with AWS Lambda, Azure Functions, and GCP Cloud Functions.

A guide to designing software architecture: monoliths vs microservices, layered architecture, data flow, and technology selection criteria.

Master cache invalidation strategies: TTL expiration, event-driven invalidation, versioned keys, tag-based purging, and write-through invalidation. Covers multi-tier invalidation, race conditions, and consistency patterns.

A practical guide to stream processing: choosing between Kafka Streams, Flink, and Spark Streaming, designing event schemas, handling stateful operations, and building exactly-once processing pipelines for real-time data.

Design and operate event-driven backends. Covers event sourcing, CQRS, sagas, outbox pattern, idempotency, eventual consistency, and production patterns for reliable event-driven architectures.

Decide when to go serverless and when not to. Covers FaaS patterns, event-driven design, cold starts, cost models, vendor lock-in, and migration strategies for production serverless applications.