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Choose based on team size, deployment independence needs, and actual scale. For small teams and moderate traffic, a modular monolith avoids distributed-systems costs like network failures and eventual consistency. Extract services only when a real bottleneck or organizational boundary demands it.

Base the choice on your data access patterns, consistency requirements, and expected data volume. Relational databases fit structured data with relationships and strong consistency needs; NoSQL fits flexible schemas or extreme write scale. Get real numbers on reads, writes, and growth before deciding.

Buy when the component is commodity functionality like authentication, payments, or email—building these creates months of work and ongoing security liability. Build only what differentiates your product or when hard constraints like compliance or air-gapped environments force custom solutions.

The critical ones are expected load (requests per second, data size, growth rate), latency targets, uptime requirements, consistency needs, budget, and team skills. Designs change completely between 100 RPS and 100k RPS, so surface these numbers before choosing an architecture.

Start with the simplest design that meets verified requirements, not imagined future scale. Avoid queues, caches, and orchestration platforms until a measured bottleneck justifies them. Mark load-bearing assumptions and revisit the design only when real usage data challenges them.