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Magnus HedemarkandGitHub
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Engineering: backend-engineering, frontend-engineering, data-engineering, ml-engineering, platform-engineering, qa-methodology Executive: go-to-market, legal-strategy, operational-design, org-design, product-strategy ml-engineering: added missing training-infrastructure.md reference qa-methodology: added test-data-management, performance-testing, security-testing references All frontmatter converted to agent-skills convention. Source: https://github.com/magnus919/hermes-profiles
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Service Patterns
Architecture Styles
| Style | Separation axis | Best for | Tradeoff |
|---|---|---|---|
| Layered | Technical layer (controller → service → repository) | Simple CRUD services, convention-based frameworks | Business logic leaks across layers |
| Clean Architecture | Dependency direction (outer → inner) | Complex business logic, long-lived projects | Boilerplate for interfaces |
| Hexagonal (Ports & Adapters) | External vs internal (ports as boundaries) | Services with multiple I/O sources | More interfaces upfront |
| Pipeline | Request flow through stages | Data processing, middleware-heavy services | Composable but hard to trace |
Request Lifecycle
Request → Middleware 1 → Middleware N → Router → Controller → Service → Repository → Database
↓
Response ← Middleware N ← Middleware 1 ←
Each layer has a distinct responsibility:
| Layer | Responsibility | Doesn't do |
|---|---|---|
| Middleware | Auth, logging, rate limiting, CORS, tracing | Business logic, data access |
| Controller | Request parsing, validation, response formatting | Business decisions, database queries |
| Service | Business rules, workflow orchestration, state mgmt | HTTP concerns, direct database access |
| Repository | Data access, query construction, result mapping | Business rules, request parsing |
Background Job Processing
| Pattern | When to use | Concerns |
|---|---|---|
| In-process worker | Lightweight, no external deps | Memory, process lifecycle, scaling |
| Message queue | Reliable async processing | Queue management, retry, DLQ |
| Scheduled cron | Periodic batch work | Timing guarantees, overlap |
| Event-driven streaming | Real-time event processing | State management, ordering |
Every background job should be: idempotent, retryable, and have a defined failure path (dead letter or alert).