Go Backend Patterns I Use in Production

After two years building Go backends in production — at a logistics company, an RAG platform, and several hackathon projects — these are the patterns that actually held up.

Clean Architecture (the parts that matter)

Everyone talks about Clean Architecture. Here's what actually works in Go services at a small scale: keep your business logic in pure functions that take and return structs. Put the database behind an interface. Let the HTTP handler parse the request and call the domain function. That's it — you don't need 47 layers of abstraction.

Event-driven with Kafka

Kafka makes sense when you have genuine service boundaries that need to stay decoupled. For a small team, the pattern I use: one producer topic per event type, one consumer per service that cares about it, and a dead-letter queue for anything that fails. Don't overthink the topic structure — start with what your services actually need, not what you think you might need in 5 years.

Semantic caching with Qdrant

If you're doing RAG, semantic caching saves real money. Hash the query embedding, store it in Qdrant, and before you call the expensive LLM for context retrieval, check if a similar query already exists. We implemented this at Hagoon — it cut token usage by a meaningful amount while keeping response quality consistent.

The takeaway

Patterns should serve your team size and service complexity, not the other way around. Start simple, make it work, then only add complexity when the pain of keeping it simple becomes real.