- name
- architecture-paradigm-service-based
- description
- |
- version
- 1.8.2
- triggers
- metadata
- {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/archetypes", "emoji": "\�\�\️"}}
- source
- claude-night-market
- source_plugin
- archetypes
Night Market Skill — ported from claude-night-market/archetypes. For the full experience with agents, hooks, and commands, install the Claude Code plugin.
The Service-Based Architecture Paradigm
When To Use
- Multi-team organizations with domain-aligned services
- Systems requiring independent deployment of components
When NOT To Use
- Single-team projects small enough for a monolith
- Latency-sensitive systems where inter-service calls are prohibitive
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
- Group Capabilities: Bundle related business functions into a small set of well-defined services, each with a designated owner.
- Define Service Contracts: Publish formal specifications using standards like OpenAPI or AsyncAPI, including Service Level Agreements (SLAs) and a clear versioning strategy.
- 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.
- Establish Service Mediation: Use a service registry or an API gateway to handle routing, authentication, and observability.
- 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.
Troubleshooting
Common Issues
Command not found Ensure all dependencies are installed and in PATH
Permission errors Check file permissions and run with appropriate privileges
Unexpected behavior Enable verbose logging with --verbose flag