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Architecture patterns

Skill AhmedHabiba/architor/.claude/skills/architecture-patterns

Structured, phase-gated architecture design powered by Claude Code. Enforces decision gates, challenges assumptions, and produces documented architecture decisions.

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Knowledge base for architecture patterns, trade-offs, and selection criteria. Activates when recommending or evaluating architecture patterns like microservices, monolith, serverless, event-driven, CQRS, or hybrid approaches.

SKILL.md

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Architecture Patterns Knowledge

Pattern Selection Framework

When recommending a pattern, evaluate against these criteria:

Team Fit

  • Team size < 5 → Strongly favor monolith or modular monolith
  • Team size 5-15 → Modular monolith or bounded microservices
  • Team size 15+ → Microservices viable if org supports it
  • No DevOps/Platform team → Avoid Kubernetes-heavy architectures
  • Junior-heavy team → Favor simpler patterns with clear boundaries

Operational Reality

  • 1 DevOps engineer → Cannot sustain >3 independently deployed services
  • No dedicated DBA → Avoid polyglot persistence
  • Limited monitoring experience → Start with monolith + good observability
  • Budget constrained → Serverless for spiky loads, monolith for steady

Requirement Signals

  • Independent scaling needs → Microservices or serverless
  • Strong consistency requirements → Monolith or synchronous microservices
  • Event-heavy domain → Event-driven architecture
  • Read/write asymmetry → CQRS
  • Rapid experimentation needed → Modular monolith (fastest to change)
  • Regulatory isolation → Service per compliance boundary

Pattern Comparison Quick Reference

Monolith

  • Best for: Small teams, rapid development, strong consistency needs
  • Risks: Scaling bottleneck, deployment coupling, team scaling limits
  • Migrate to: Modular monolith → microservices (progressive)

Modular Monolith

  • Best for: Teams 3-10, need clear boundaries without operational overhead
  • Risks: Module coupling creep, single deployment unit
  • Migrate to: Extract modules to services as needed

Microservices

  • Best for: Large teams, independent scaling, polyglot needs
  • Risks: Distributed system complexity, data consistency, operational overhead
  • Prerequisite: CI/CD maturity, monitoring, team autonomy

Event-Driven

  • Best for: Async workflows, decoupled services, audit trails
  • Risks: Eventual consistency complexity, debugging difficulty, event schema evolution
  • Prerequisite: Team comfort with async patterns, good monitoring

Serverless-First

  • Best for: Spiky workloads, cost optimization at low scale, rapid prototyping
  • Risks: Cold starts, vendor lock-in, debugging difficulty, cost at scale
  • Prerequisite: Cloud-native comfort, stateless design skills

CQRS

  • Best for: Read-heavy systems, different read/write models, event sourcing
  • Risks: Complexity, eventual consistency, increased codebase size
  • Prerequisite: Strong domain modeling skills

Red Flags by Pattern

  • Microservices with shared database → "You have a distributed monolith"
  • Event sourcing without replay testing → "You'll lose data"
  • Serverless with persistent connections → "Wrong pattern for this workload"
  • CQRS for simple CRUD → "Over-engineered"
  • Monolith with 50+ developers → "Deployment bottleneck incoming"

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