What is the N+1 query problem and how do you solve it in Go?

You have a Go function that fetches a list of users and then, inside a loop, queries the DB for each user's profile. What problem might you see and how would you rewrite it?

If the number of database queries grows proportionally to the number of items returned, what steps would you take in Go to reduce that count?

We added an endpoint that returns orders with their line items, and latency doubled after release. Walk me through how you'd check if an N+1 query is the cause and how you'd fix it in Go.

Our service uses GORM and we see a spike in DB connections when loading a product catalog. Explain why an N+1 pattern might be happening and which GORM features you could use to prevent it.

Design a Go data‑access layer that avoids N+1 queries across multiple services, considering caching, batching, and transaction boundaries. What trade‑offs do you evaluate?

A microservice aggregates data from three tables using separate queries per row, causing N+1 at millions of rows. How would you refactor the queries and what impact on consistency and latency would you expect?

How would you instrument a Go application in production to detect N+1 query patterns and what automated mitigations could you deploy?

We are migrating a legacy monolith written in Go that suffers from pervasive N+1 queries to an event‑driven architecture. How would you plan the migration to eliminate N+1 while preserving business logic?

Different teams use various ORMs, leading to inconsistent eager loading handling. As a staff engineer, how would you establish a company‑wide strategy to prevent N+1 queries and ensure maintainability?

For a high‑throughput read‑heavy service serving billions of requests daily, discuss architectural choices (read replicas, CQRS, materialized views) you would make to guarantee N+1 queries never become a bottleneck.