API Server: Extension and Operating Patterns
API Server: Extension and Operating Patterns
This page collects forward-looking guidance and operating patterns for the
aicrd API server that go beyond what is implemented in
pkg/api /
pkg/server today.
The code samples are illustrative — they describe how a feature would be
implemented or operated, not behavior that ships in the current binary.
For what the API server actually does today (architecture, request flow, implemented endpoints, current observability, security model), see API Server Architecture.
Status: Patterns and code in this document are aspirational unless explicitly noted otherwise. Treat them as a roadmap and reference, not as wired-up behavior. Do not link them from runbooks without verifying the underlying capability exists in the current build.
Future Enhancements
Near-Term Ideas
-
Authentication & Authorization
Rationale: Protect API from unauthorized access, enable usage tracking
Implementation: API key middleware with HMAC-SHA256 verification
Example:Reference: HTTP Authentication
-
CORS Support
Use Case: Enable browser-based clients (web dashboards)
Implementation:rs/corsmiddleware with configurable origins
Configuration:Reference: CORS Specification
-
Response Compression
Benefit: Reduce bandwidth by 70-80% for JSON responses
Implementation:gziphandlermiddleware with quality thresholdTrade-off: CPU usage (+5-10%) vs bandwidth savings
Reference: gziphandler -
Native TLS Support
Rationale: Eliminate need for reverse proxy in simple deployments
Implementation:http.ListenAndServeTLSwith Let’s Encrypt integrationReference: autocert Package
-
API Versioning
Use Case: Support /v2 API with breaking changes while maintaining /v1
Pattern: URL-based versioning with version-specific handlersReference: API Versioning Best Practices
Mid-Term Ideas
-
OpenTelemetry Integration
Use Case: Distributed tracing across services
Implementation: OTLP exporter with automatic instrumentationReference: OpenTelemetry Go
-
Recipe Caching
Benefit: 95%+ cache hit rate for repeated queries
Implementation: Redis with TTL, fallback to recipe builderReference: go-redis
-
GraphQL API
Rationale: Enable clients to request only needed fields
Implementation:graphql-gowith recipe schemaTrade-off: Added complexity vs flexible querying
Reference: GraphQL Go
Longer-Term Ideas
-
gRPC Support
Benefit: 5-10x better performance, smaller payloads
Implementation: Protobuf definition with streaming supportDeployment: Run HTTP/2 and gRPC on same port with
cmux
Reference: gRPC Go -
Multi-Tenancy
Use Case: SaaS deployment with per-customer isolation
Implementation: Tenant ID from API key, separate rate limitsDatabase: Separate recipe stores per tenant
-
Admin API
Use Case: Runtime configuration updates without restart
Endpoints:POST /admin/config/rate-limit- Update rate limitsPOST /admin/config/log-level- Change log verbosityGET /admin/debug/pprof- CPU/memory profilingPOST /admin/cache/flush- Clear recipe cache Security: Separate admin API key with IP allowlist
-
Feature Flags
Rationale: A/B testing, gradual rollouts, instant rollback
Implementation: LaunchDarkly or custom flag serviceReference: LaunchDarkly Go SDK
Production Deployment Patterns
Pattern 1: Kubernetes with Horizontal Pod Autoscaler
Use Case: Auto-scale API servers based on request rate
Deployment Manifest:
Ingress with TLS:
Pattern 2: Service Mesh with mTLS
Use Case: Zero-trust security with automatic mTLS encryption
Istio VirtualService:
Pattern 3: Load Balancer with Health Checks
Use Case: Bare-metal deployment with HAProxy
HAProxy Configuration:
Pattern 4: Blue-Green Deployment
Use Case: Zero-downtime updates with instant rollback
Kubernetes Service Switching:
Reliability Patterns
Circuit Breaker
Use Case: Prevent cascading failures when recipe store is slow
Implementation:
Reference: gobreaker
Bulkhead Pattern
Use Case: Isolate resources for different endpoints
Implementation:
Benefit: Recipe slowness doesn’t affect snapshot endpoint
Retry with Exponential Backoff
Use Case: Resilient calls to external APIs (recipe store, etc.)
Implementation:
Reference: backoff
Graceful Degradation
Use Case: Serve stale/cached data when primary source fails
Implementation:
Performance Optimization
Connection Pooling
HTTP Client with Keep-Alive:
Response Caching
In-Memory Cache with TTL:
Request Coalescing
Deduplicate Concurrent Identical Requests:
Benefit: 10 concurrent identical requests = 1 recipe build