Architecture Paradigm Service Based

---
name: architecture-paradigm-service-based
description: Employ a coarse-grained, service-based architecture (a lighter form of SOA) when microservices are not yet necessary but modular deployment is required. Use when building coarse-grained service-oriented systems.
version: 1.0.0
category: architectural-pattern
tags: [architecture, service-based, soa, modular, shared-database]
dependencies: []
tools: [api-gateway, service-registry, schema-management]
usage_patterns:
  - paradigm-implementation
  - monolith-refactoring
  - deployment-independence
complexity: medium
estimated_tokens: 700
---

# 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 ensure 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.