Files
goplt/docs/content/adr/0030-service-communication-strategy.md
0x1d 38a251968c docs: Align documentation with true microservices architecture
Transform all documentation from modular monolith to true microservices
architecture where core services are independently deployable.

Key Changes:
- Core Kernel: Infrastructure only (no business logic)
- Core Services: Auth, Identity, Authz, Audit as separate microservices
  - Each service has own entry point (cmd/{service}/)
  - Each service has own gRPC server and database schema
  - Services register with Consul for service discovery
- API Gateway: Moved from Epic 8 to Epic 1 as core infrastructure
  - Single entry point for all external traffic
  - Handles routing, JWT validation, rate limiting, CORS
- Service Discovery: Consul as primary mechanism (ADR-0033)
- Database Pattern: Per-service connections with schema isolation

Documentation Updates:
- Updated all 9 architecture documents
- Updated 4 ADRs and created 2 new ADRs (API Gateway, Service Discovery)
- Rewrote Epic 1: Core Kernel & Infrastructure (infrastructure only)
- Rewrote Epic 2: Core Services (Auth, Identity, Authz, Audit as services)
- Updated Epic 3-8 stories for service architecture
- Updated plan.md, playbook.md, requirements.md, index.md
- Updated all epic READMEs and story files

New ADRs:
- ADR-0032: API Gateway Strategy
- ADR-0033: Service Discovery Implementation (Consul)

New Stories:
- Epic 1.7: Service Client Interfaces
- Epic 1.8: API Gateway Implementation
2025-11-06 08:54:19 +01:00

3.2 KiB

ADR-0030: Service Communication Strategy

Status

Accepted

Context

Services need to communicate with each other in a microservices architecture. All communication must go through well-defined interfaces that support network calls.

Decision

Use a service client-based communication strategy with API Gateway as the entry point:

  1. API Gateway (Entry Point):

    • All external traffic enters through API Gateway
    • Gateway routes requests to backend services via service discovery
    • Gateway handles authentication (JWT validation via Auth Service)
    • Gateway handles rate limiting, CORS, request transformation
  2. Service Client Interfaces (Primary for synchronous calls):

    • Define interfaces in pkg/services/ for all services
    • All implementations are network-based:
      • internal/services/grpc/client/ - gRPC clients (primary)
      • internal/services/http/client/ - HTTP clients (fallback)
    • Gateway uses service clients to communicate with backend services
    • Services use service clients for inter-service communication
  3. Event Bus (Primary for asynchronous communication):

    • Distributed via Kafka
    • Preferred for cross-service communication
    • Event-driven architecture for loose coupling
  4. Shared Infrastructure (For state):

    • Redis for cache and distributed state
    • PostgreSQL instance for persistent data (each service has its own schema)
    • Kafka for events

Service Client Pattern

// Interface in pkg/services/
type IdentityServiceClient interface {
    GetUser(ctx context.Context, id string) (*User, error)
    CreateUser(ctx context.Context, user *User) (*User, error)
}

// gRPC implementation (primary)
type grpcIdentityClient struct {
    conn *grpc.ClientConn
    client pb.IdentityServiceClient
}

// HTTP implementation (fallback)
type httpIdentityClient struct {
    baseURL string
    httpClient *http.Client
}

Communication Flow

Client → API Gateway → Backend Service (via service client)
Backend Service → Other Service (via service client)

All communication goes through service clients - no direct in-process calls even in development mode.

Development Mode

For local development, services run in the same repository but as separate processes:

  • Each service has its own entry point (cmd/{service}/)
  • Services communicate via service clients (gRPC or HTTP) - no direct in-process calls
  • Docker Compose orchestrates all services
  • This ensures the architecture is consistent with production

Consequences

Positive

  • Unified Interface: Consistent interface across all services
  • Easy Testing: Can mock service clients
  • Type Safety: gRPC provides type-safe contracts
  • Clear Boundaries: Service boundaries are explicit
  • Scalability: Services can be scaled independently

Negative

  • Network Overhead: All calls go over network
  • Interface Evolution: Changes require coordination
  • Versioning: Need service versioning strategy
  • Development Complexity: More setup required for local development

Implementation

  • All services use gRPC clients (primary)
  • HTTP clients as fallback option
  • Service registry for service discovery
  • Circuit breakers and retries for resilience