# Architecture Paradigm Service Based

> Coarse-grained service architecture for deployment independence without microservices complexity. Triggers: service-based, SOA, coarse-grained services, domain services Use when: teams need deployment independence without microservices complexity DO NOT use when: fine-grained scaling needed - use microservices.

- Skill: `majiayu000/architecture-paradigm-service-based-3` (Agent Skill, multi-file: 2 files)
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- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/majiayu000/architecture-paradigm-service-based-3

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# The Service-Based Architecture Paradigm

## When to Employ This Paradigm
- When teams require a degree of deployment independence but are not yet prepared for the complexity of managing numerous microservices.
- When shared databases or large-scale systems (like ERPs) make full service autonomy unrealistic.
- When establishing clear service contracts for partner teams or external consumers.

## Adoption Steps
1. **Group Capabilities**: Bundle related business functions into a small set of well-defined services, each with a designated owner.
2. **Define Service Contracts**: Publish formal specifications using standards like OpenAPI or AsyncAPI, including Service Level Agreements (SLAs) and a clear versioning strategy.
3. **Control Database Schemas**: Even when services share a database, assign explicit ownership for each schema or table. Gate all breaking changes through a formal review process.
4. **Establish Service Mediation**: Use a service registry or an API gateway to handle routing, authentication, and observability.
5. **Plan for Evolution**: Identify architectural "hotspots" that are likely candidates for being split into more granular services in the future.

## Key Deliverables
- An Architecture Decision Record (ADR) that outlines service boundaries, data ownership rules, and coordination mechanisms.
- A suite of contract tests and consumer-driven contract tests for each service to validate stability.
- Runbooks that describe deployment procedures, rollback plans, and service dependencies.

## Risks & Mitigations
- **Coupling Through a Shared Database**:
  - **Mitigation**: Changes to a shared database can have cascading effects across services. Mitigate this by using database views, replication, or a formal schema deprecation schedule to manage change.
- **Architectural Degradation**:
  - **Mitigation**: Without strong governance, this architecture can degrade into a "distributed monolith"—a monolith with the added complexity of network hops. Track coupling metrics closely and enforce strict ownership of services and data to prevent this.