Event-driven backend on RabbitMQ and Kafka

I design and build asynchronous, event-driven backends that keep your services decoupled, resilient and easy to scale. When a request no longer has to wait for every downstream step to finish, your API stays fast and your background work runs on its own schedule. I model the message flow first: which events matter, who publishes them, who consumes them, and what has to happen when something fails. From that model I build the actual topology in RabbitMQ or Kafka, with clean naming, sensible routing and clear ownership for every queue and topic.

On the RabbitMQ side I set up exchanges, queues and bindings that match your real routing needs, then write workers that acknowledge correctly, prefetch sensibly and never lose a message on restart. I add retry policies with exponential backoff, dead-letter exchanges for messages that keep failing, and idempotent handlers so a redelivery never double-charges or double-sends. For higher-throughput event streams I use Kafka: partitioned topics, consumer groups, offset management and replay, so you can reprocess history when you ship a new feature. Either way I care about back-pressure, ordering guarantees and what happens under load, not just the happy path.

You get background processing that survives spikes and outages: heavy jobs, notifications, integrations and data pipelines all run through the broker instead of blocking the user. I deliver clear diagrams of the flow, tested producers and consumers, health checks, metrics and dashboards, plus runbooks for the on-call cases that actually occur. I can extend an existing system or stand one up from scratch, and I hand it over documented so your team can keep building on it.

— Topology design: exchanges, queues, topics, partitions, routing
— Reliable workers: acks, prefetch, retries, dead-letter handling
— Idempotency, ordering and back-pressure under real load
— Monitoring, alerting and runbooks for production