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Architecture choice

Архитектурные развилки и как их решать: монолит или микросервисы, выбор хранилищ, sync или async, MVC или WebFlux, ADR для фиксации решений, роль архитектора и AI-скиллы.

The forks in the road you hit on every new project. Each one gets its own article with a checklist, selection criteria, and common mistakes.

Articles in this section

  1. Monolith, modular monolith, or microservices — a "6-point" checklist for the start of a project, a comparison of the three options on a single marketplace case study, and scenarios for moving between them without a rewrite.
  2. PostgreSQL or MongoDB: how to make the call — ten criteria for choosing a relational vs document database, the typical antipatterns (Mongo "because NoSQL is trendy", PG "because it's familiar"), and scenarios where both databases work within a single service.
  3. PostgreSQL or ClickHouse: when to add OLAP — eight criteria and a checklist: where the line "analytics in PG is still fine" sits, and when it's time to bring in a second store.
  4. Search: PostgreSQL FTS or Elasticsearch — what tsvector and pg_trgm can do, where their ceiling is, and when you need a full-blown search engine.
  5. Files: in the database or in object storage — the boundary based on size and traffic, two-phase upload, and "database + S3" consistency.
  6. Between services: synchronous call or events — criteria for each interaction, with the synchronous saga and RPC-over-Kafka as antipatterns.
  7. The web stack: Spring MVC, WebFlux, or virtual threads — which of WebFlux's arguments Loom has closed, and where reactive is still justified.
  8. ADRs: how to record architectural decisions — the format, the statuses, when to write one; each fork above deserves a record.
  9. What an architect does — and which tasks AI skills cover — the seven responsibilities of the role and which ucp skills automate each.
  • Use Case Pattern — the methodology survives each of these modes without a rewrite.
  • The PostgreSQL section — the details of ACID, replication, and sharding.
  • The MongoDB section — the details of read/write concerns, replica sets, and sharded clusters.
  • The C4 model — how to describe a system once the architectural choice has been made.
  • AMQP vs Kafka — choosing a broker, if the sync/async fork resolved in favor of events.