Event-Driven Architecture and Message Queues
How events and message queues enable decoupled, resilient shop integrations: retry, partitioned ordering, idempotency and the dead letter queue explained.
Whether point-to-point connections or a central middleware — the architecture decides how expensive the tenth integration becomes. This category sets out the options: direct interfaces, queues and event-driven transfer, scheduled synchronisation, data mapping and transformation, interface versioning, and monitoring and retrying failed transfers. We explain when a dedicated integration layer pays off, which logging and traceability requirements are sensible and how to limit dependencies on individual providers. Documentation is part of it too: without described data flows, every later change becomes a risk — no matter how cleanly the first implementation was built. We also show which metrics describe the state of an integration — from the number of pending queue items to the duration of a full synchronisation.
How events and message queues enable decoupled, resilient shop integrations: retry, partitioned ordering, idempotency and the dead letter queue explained.
Idempotency keys, exponential backoff with jitter and dead letter queues: how to make order and inventory syncs between store and ERP safely repeatable.
Webhooks or polling for shop-to-ERP integration? A comparison of latency, delivery guarantees, HMAC security and resilience with practical recommendations.