Asynchronous backend on RabbitMQ and Kafka

I design and build asynchronous, event-driven backends that make services independent of each other, resilient to failures and ready for growing load. When a request doesn't wait for all downstream steps to complete, your API stays fast and background work progresses at its own pace. First I model the message flow: which events matter, who publishes them, who consumes them and what should happen on error. Using this model I build the real topology in RabbitMQ or Kafka with clear names, thoughtful routing and explicit responsibility for each queue and topic.

In RabbitMQ I configure exchanges, queues and bindings for your actual routes, then write workers that properly acknowledge messages, sensibly use prefetch and don't lose data on restart. I add a retry policy with exponential backoff, dead-letter exchanges for stuck messages and idempotent handlers so redelivery doesn't cause double charging or duplicate sends. For high-volume streams I use Kafka: partitioned topics, consumer groups, offset management and history replay so you can reprocess data after deploying a new feature. Either way I focus on back-pressure, ordering guarantees and behavior under load, not just ideal scenarios.

You get background processing that survives spikes and outages: heavy tasks, notifications, integrations and data pipelines flow through the broker instead of blocking users. I provide clear flow diagrams, tested producers and consumers, health checks, metrics and dashboards, plus incident runbooks for on-call. I can extend an existing system or build one from scratch with full documentation so your team confidently develops the solution further.

— Topology design: exchanges, queues, topics, partitions
— Reliable workers: ack, prefetch, retries, dead-letter
— Idempotency, ordering and back-pressure under real load
— Monitoring, alerts and production runbooks