API Gateway
The Gateway is the runtime enforcement point for all API traffic, providing security, routing, observability, and policy enforcement.
1.1 Core Gateway Components
High-Level Architecture
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flowchart LR
Client[API Consumer]
subgraph Gateway["API Gateway"]
RequestPipeline[Request Pipeline]
ResponsePipeline[Response Pipeline]
end
Backend[Backend APIs]
Registry[API Registry]
Auditor[API Auditor]
Client --> RequestPipeline
RequestPipeline --> Backend
Backend --> ResponsePipeline
ResponsePipeline --> Client
Registry -.->|Config & Policy| Gateway
Gateway -.->|Logs & Metrics| Auditor
Request Processing Pipeline
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flowchart TB
Request[Incoming
Request]
subgraph Security["Security Layer"]
Auth[Authentication]
Authz[Authorization]
end
subgraph Traffic["Traffic Management"]
RateLimit[Rate Limiting]
Cache[Cache Check]
end
subgraph Processing["Request Processing"]
Transform[Transformation]
SecurityFilter[Security Filter]
Circuit[Circuit Breaker]
end
subgraph Observability["Observability"]
Logging[Logging]
Metrics[Metrics]
end
Backend[Backend
API]
Request --> Auth
Auth --> Authz
Authz --> RateLimit
RateLimit --> Cache
Cache --> Transform
Transform --> SecurityFilter
SecurityFilter --> Circuit
Circuit --> Backend
Auth -.-> Logging
Authz -.-> Logging
RateLimit -.-> Logging
Auth -.-> Metrics
Authz -.-> Metrics
RateLimit -.-> Metrics
Response Processing Pipeline
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flowchart TB
Backend[Backend
Response]
subgraph Processing["Response Processing"]
Circuit[Circuit Breaker]
SecurityFilter[Security Filter]
Transform[Transformation]
end
subgraph Caching["Caching"]
CacheStore[Cache Store]
end
subgraph Observability["Observability"]
Logging[Logging]
Metrics[Metrics]
end
Client[Response to
Consumer]
Backend --> Circuit
Circuit --> SecurityFilter
SecurityFilter --> Transform
Transform --> CacheStore
CacheStore --> Client
Circuit -.-> Logging
SecurityFilter -.-> Logging
Transform -.-> Logging
Circuit -.-> Metrics
SecurityFilter -.-> Metrics
Transform -.-> Metrics
CacheStore -.-> Metrics
Gateway Supporting Infrastructure
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flowchart LR
subgraph Core["Gateway Core Modules"]
Router[Reverse Proxy &
Router]
Auth[Authentication]
RateLimit[Rate Limiting]
Transform[Transformation]
end
subgraph Observability["Observability"]
Logging[Logging &
Audit]
Metrics[Metrics &
Telemetry]
end
subgraph Data["Data Layer"]
Redis[Redis
Cache & Counters]
Registry[API Registry
Config]
IDP[Registry Subscription DB]
end
subgraph External["External Systems"]
LogInfra[Log Infrastructure
Splunk/ELK]
MonitoringPlatform[Monitoring Platform
Prometheus/Datadog]
end
Core --> Redis
Core <--> Registry
Auth <--> IDP
Logging --> LogInfra
Metrics --> MonitoringPlatform
Core -.-> Logging
Core -.-> Metrics
Reverse Proxy / Request Router
Purpose: Routes incoming requests to appropriate backend services based on API version, endpoint, and routing rules.
Key Responsibilities:
- HTTP/HTTPS request handling and connection management
- TLS termination and re-encryption for backend communication
- Request routing based on path, method, headers, and query parameters
- Load balancing across backend instances (round-robin, least-connections, weighted)
- Health checking of backend services with automatic failover
- Connection pooling and keepalive management for performance
- Request/response buffering and streaming support
Technical Implementation:
- Built on proven reverse proxy frameworks: NGINX, Envoy, Kong, or AWS API Gateway
- High availability: deployed as clustered service with shared routing configuration
- Horizontal scaling: stateless design allows adding instances for capacity
- Configuration hot-reload: routing rules updated without gateway restarts
Inputs:
- Routing configuration from Registry (API endpoints, backend URLs, versions)
- Health check status from backend services
- Traffic management policies (canary routing percentages, A/B test rules)
Outputs:
- Routed requests to backend API services
- Routing metrics (requests per route, latency per backend)
- Health status of backend pools
Authentication Module
Purpose: Validates the identity of API consumers before allowing access.
Key Responsibilities:
- Credential validation for multiple authentication schemes:
- OAuth 2.0 / OpenID Connect (OIDC) token validation
- JWT (JSON Web Token) parsing and signature verification
- API key validation against Registry
- Mutual TLS (mTLS) certificate validation
- SAML assertion validation for enterprise SSO
- Token introspection with identity provider (IDP) for revocation checks
- Caching of validated tokens to reduce IDP load (with configurable TTL)
- User identity extraction and context propagation to downstream services
- Service-to-service authentication with short-lived credentials
- Rate limiting authentication attempts to prevent brute force attacks
Technical Implementation:
- OAuth/OIDC: Integration with enterprise identity providers (Okta, Auth0, Azure AD, Keycloak)
- JWT validation: Local signature verification using IDP public keys (JWKS endpoint)
- API key lookup: Fast in-memory cache backed by Registry database
- mTLS: Certificate validation against trusted CA, subject name verification
- Plugin architecture: extensible to support custom authentication schemes
Inputs:
- Authentication credentials from request (headers, certificates, cookies)
- Public keys / certificates from identity providers
- API key registry from subscription database
- Revocation lists (CRLs, OCSP responses) for certificate validation
Outputs:
- Authenticated identity (user ID, service account, application ID)
- Authentication result (success/failure with reason codes)
- Identity claims and attributes for authorization decisions
- Authentication metrics (success rate, failure reasons, latency)
Error Handling:
- 401 Unauthorized for missing or invalid credentials
- 403 Forbidden for valid credentials with insufficient permissions
- Detailed error codes for troubleshooting (expired token, invalid signature, revoked key)
Authorization Module
Purpose: Determines whether an authenticated caller is permitted to access a specific API endpoint.
Key Responsibilities:
- Subscription validation: verify caller has active subscription for requested API version and environment
- Scope-based access control: check OAuth scopes or JWT claims against required permissions
- Role-Based Access Control (RBAC): validate user/service roles against endpoint requirements
- Attribute-Based Access Control (ABAC): policy decisions based on request attributes, context, data classification
- Environment isolation enforcement: prevent production credentials from accessing dev/test
- Endpoint-level permissions: granular control (read-only vs. write, admin operations)
- Rate limit quota checking: verify consumer hasn’t exceeded allocated request quota
- IP allowlist/denylist enforcement for subscription-level restrictions
Technical Implementation:
- Subscription lookup strategies (choose based on performance requirements):
- In-Memory Store (Recommended for Production): Load entire active subscription dataset into gateway shared memory for nanosecond-scale lookups. A typical dataset of 100,000 subscriptions ≈ 100MB. Gateway polls Registry every 30-60 seconds for updates. This eliminates network latency, provides full autonomy (gateway continues operating during Registry outages), and delivers sub-millisecond authorization decisions. Proven pattern used by Stripe, Cloudflare, and Fastly.
- Short-TTL Cache: Query Registry API with aggressive caching (5-30 second TTL). Provides balance between freshness and performance. Suitable for lower-traffic environments.
- Direct Registry Query: Real-time lookup for every request. Highest consistency but adds network latency (5-50ms). Only use when immediate revocation is critical.
- Policy engine: Open Policy Agent (OPA), AWS IAM, or custom rule engine
- Decision caching: Cache authorization decisions with short TTL to reduce latency
- Policy as code: Authorization rules defined in Cedar or similar DSL
- Performance target: Authorization decisions should complete in <1ms (P95) to avoid becoming the bottleneck in request processing
Inputs:
- Authenticated identity from Authentication Module
- API endpoint being requested (path, method, version)
- Subscription database from Registry
- Authorization policies and role definitions
- Request context (IP address, time of day, geographic location, data sensitivity)
Outputs:
- Authorization decision (allow/deny with reason)
- Applicable subscription ID for logging and metering
- Permission scope for downstream services (what actions are allowed)
- Authorization metrics (decisions per second, deny rate, policy evaluation latency)
Error Handling:
- 403 Forbidden for valid identity without sufficient permissions
- 404 Not Found to hide existence of endpoints from unauthorized callers (optional)
- Detailed audit log of authorization failures for security analysis
Rate Limiting & Throttling Module
Purpose: Protects APIs from overload and enforces fair usage across consumers.
Key Responsibilities:
- Per-subscription rate limits based on subscription tier or negotiated SLA
- Global rate limits per API to protect producer capacity
- Burst allowances using token bucket or leaky bucket algorithms
- Graduated throttling: soft limits (warnings) vs. hard limits (blocking)
- Priority queuing: critical consumers bypass throttling during incidents
- Distributed rate limiting across gateway instances with shared state
- Rate limit reset timelines (per second, minute, hour, day)
- Quota management for monthly/annual usage caps
Technical Implementation:
- Algorithm: Token bucket (allows bursts) or sliding window (precise limit enforcement)
- Shared state: Redis or Memcached cluster for distributed counters
- Local caching: Fast in-memory checks with periodic sync to shared state
- Adaptive rate limiting: Dynamic limits based on backend health signals
- Circuit breaker integration: Fail fast when backends are unhealthy
Inputs:
- Subscription rate limit configurations from Registry
- Global API capacity limits from producer teams
- Current request rate per subscription (from distributed counters)
- Backend health status (latency, error rate) for adaptive limiting
Outputs:
- Rate limit decision (allow or throttle)
- Remaining quota in response headers (X-RateLimit-Remaining, X-RateLimit-Reset)
- 429 Too Many Requests response when limit exceeded
- Rate limit metrics (throttled requests, top limit-hitting consumers)
- Proximity warnings when consumers approach limits (80%, 90% thresholds)
Consumer-Friendly Features:
- Retry-After header indicating when to retry
- Detailed rate limit headers showing limit, remaining, and reset time
- Graceful degradation: queue requests briefly rather than immediate rejection
- Proactive warnings sent to consumers via notification channels
Request/Response Transformation Module
Purpose: Modifies requests and responses to maintain compatibility, enforce security, and support API evolution.
Key Responsibilities:
- Protocol translation (REST ↔ GraphQL, SOAP ↔ REST, gRPC ↔ HTTP, WebSocket ↔ HTTP)
- Protocol-native handling for first-class protocols:
- REST/OpenAPI: Standard HTTP request/response with path-based routing
- GraphQL: Single endpoint, query parsing, field-level authorization, complexity limiting
- AsyncAPI: WebSocket connections, message broker integration, channel subscriptions
- Request enrichment: Add headers, inject subscription metadata, append correlation IDs
- Response filtering: Strip sensitive fields based on consumer authorization and data classification
- PII masking: Redact personally identifiable information for consumers without explicit PII access
- Field mapping for backward compatibility during API evolution
- Content negotiation: Transform response format based on Accept header (JSON, XML, protobuf)
- Error response standardization: Uniform error format across all APIs
- Versioned transformation rules: Different transforms per API version
Technical Implementation:
- Transformation DSL or scripting (Lua, JavaScript, XSLT, JSONPath expressions)
- Schema-aware transformations using API specifications (OpenAPI, GraphQL schema, AsyncAPI)
- Performance optimization: Streaming transformations for large payloads
- Configurable per subscription: Different transformations for different consumers
Inputs:
- Inbound request from consumer
- API specification defining data model and sensitive fields
- Transformation rules from Registry (field mappings, masking rules)
- Consumer authorization scope (which fields they can access)
- Data classification metadata (which fields contain PII, PHI, etc.)
Outputs:
- Transformed request sent to backend
- Transformed response sent to consumer
- Audit log of transformations applied (especially PII redaction)
- Transformation metrics (overhead latency, transformation errors)
Use Cases:
- Backward compatibility: Convert v2 requests to v3 format for gradual backend migration
- Security: Remove internal debugging fields from responses to external consumers
- Compliance: Mask SSN, credit card numbers for consumers without elevated access
- Migration support: Support old field names while backend uses new schema
Data Security & Privacy Module
Purpose: Enforces encryption, data residency, and privacy controls for sensitive data.
Key Responsibilities:
- TLS termination and re-encryption
- Support for TLS 1.2 minimum, TLS 1.3 preferred
- Strong cipher suite enforcement (remove weak/deprecated ciphers)
- Certificate management and rotation
- HSTS (HTTP Strict Transport Security) header enforcement
- Field-level encryption for highly sensitive data
- Encrypt specific fields (e.g., SSN, credit card) at gateway before backend processing
- Decrypt on response based on consumer authorization
- Data residency routing
- Route requests to region-specific backends based on data sovereignty requirements
- GDPR, data localization compliance (e.g., EU data stays in EU)
- Request/response sanitization
- Strip debug headers, internal metadata in production environments
- Remove error stack traces from error responses to prevent information disclosure
- PII detection and handling
- Pattern matching to detect PII in logs, error messages
- Automatic redaction of detected PII before logging
Technical Implementation:
- TLS: Managed certificates via Let’s Encrypt, AWS ACM, or internal PKI
- Encryption: AES-256-GCM for field-level encryption with key management service integration
- Geographic routing: IP geolocation or explicit region headers to determine data residency rules
- Sensitive data detection: Regex patterns, ML models for PII detection
Inputs:
- Data classification metadata from API specifications
- Encryption keys from secrets management service (AWS KMS, HashiCorp Vault)
- Data residency policies from Registry
- Consumer authorization scope (can they access encrypted fields?)
Outputs:
- Encrypted fields in requests/responses
- Routing decisions based on data residency
- Sanitized logs with PII redacted
- Compliance metrics (cross-border data transfers, PII access events)
Logging & Audit Module
Purpose: Captures comprehensive audit trail of all API traffic for security, compliance, and troubleshooting.
Key Responsibilities:
- Structured logging of every request and response
- Request metadata: timestamp, method, path, query params, headers
- Identity: user ID, application ID, subscription ID, IP address
- Response: status code, size, latency breakdown
- Security event logging
- Authentication failures with reason codes
- Authorization denials
- Rate limit violations
- Suspicious patterns (repeated failures, unusual access)
- Data access logging for sensitive APIs
- Record-level access (which customer records were accessed)
- Field-level access for PII/PHI (which sensitive fields were returned)
- Purpose of access from subscription metadata
- Distributed tracing integration
- Generate and propagate trace IDs, span IDs
- Integration with OpenTelemetry, Jaeger, Zipkin
- Performance logging
- Latency breakdown: queue time, gateway processing, backend time
- Cache hit/miss rates
- Transformation overhead
Technical Implementation:
- Log format: Structured JSON for machine parsing
- Log levels: DEBUG, INFO, WARN, ERROR with configurable verbosity
- Sampling: Full logging for errors, sampling for successful requests at high volume
- Buffering: Asynchronous log writing to avoid blocking request path
- Retention: Hot storage for recent logs, archival to cold storage (S3, GCS)
Inputs:
- Request/response data flowing through gateway
- Authentication/authorization results
- Performance timing metrics
- Data classification rules (what should be redacted in logs)
Outputs:
- Log streams to centralized logging infrastructure (Splunk, Elasticsearch, CloudWatch)
- Structured events for SIEM systems
- Distributed traces for APM tools
- Immutable audit logs for compliance (write-once, read-many storage)
Privacy & Compliance:
- PII redaction in logs automatically applied
- Sensitive data (passwords, tokens, credit cards) never logged
- Log access controls: only security, compliance, and designated personnel
- Tamper-proof logging with cryptographic signing for regulatory compliance
Metrics & Telemetry Module
Purpose: Collects real-time performance and usage metrics for monitoring and analytics.
Key Responsibilities:
- Request rate metrics
- Requests per second per API, per version, per subscription
- Geographic distribution of traffic
- Latency metrics
- P50, P90, P95, P99 latency per API, per endpoint
- Breakdown: gateway overhead, backend processing, network time
- Error rate tracking
- 4xx errors (client errors) vs 5xx errors (server errors)
- Error rates per consumer to identify problematic integrations
- Resource utilization
- Gateway CPU, memory, network bandwidth
- Connection pool usage, thread pool saturation
- Business metrics
- Data transfer volume per subscription (for cost attribution)
- Most popular endpoints for roadmap prioritization
- API version adoption rates
Technical Implementation:
- Metrics collection: Prometheus, StatsD, CloudWatch, Datadog
- Time-series database: Prometheus, InfluxDB, TimescaleDB
- Dashboards: Grafana, Kibana, vendor-specific dashboards
- Alerting: PagerDuty, Opsgenie integration for SLO violations
Inputs:
- Request/response timing data from proxy
- Error status codes
- Resource usage from system metrics
- Subscription metadata for attribution
Outputs:
- Time-series metrics streams to monitoring platforms
- Real-time dashboards for producers and platform team
- Alerting triggers when thresholds breached
- Data feed to Auditor component for historical analysis
Circuit Breaker, Resilience & Canary Deployment Module
Purpose: Prevents cascading failures, provides graceful degradation when backends are unhealthy, and enables safe progressive rollouts of new API versions.
Key Responsibilities:
- Circuit breaker pattern implementation
- Monitor backend error rates and latency
- Open circuit (fail fast) when error threshold exceeded
- Half-open state for gradual recovery testing
- Closed state when backend is healthy
- Automatic retries with exponential backoff
- Retry transient failures (network issues, 502/503 errors)
- Avoid retry amplification (don’t retry on client errors)
- Timeout management
- Configurable request timeouts per API
- Prevent hanging requests from exhausting resources
- Bulkhead isolation
- Separate thread pools or connection pools per API
- Limit blast radius if one API has issues
- Fallback responses
- Serve cached responses when backend unavailable
- Return degraded functionality rather than complete failure
- Canary deployment support
- Progressive traffic shifting from stable to new version
- Percentage-based traffic splitting (e.g., 5% → 25% → 50% → 100%)
- Automatic promotion or rollback based on success metrics
- Header-based routing for internal testing (X-Canary-Version)
- Subscription-based canary groups (beta testers get new version first)
- A/B testing support for comparing version performance
Technical Implementation:
- Libraries: Resilience4j, Hystrix, or built-in Envoy resilience features
- State management: Distributed circuit breaker state across gateway instances
- Health scoring: Adaptive circuit breaker with gradual degradation
- Traffic splitting: Weighted load balancing across version pools
- Canary orchestration: Integration with deployment pipelines (Argo Rollouts, Flagger, Spinnaker)
- Automated decision-making: Compare error rates, latency p95, and business metrics between stable and canary
Inputs:
- Backend response status codes and latency
- Error thresholds and timeout configurations
- Health check results from backend services
- Canary deployment configuration from Registry (traffic percentage, rollout schedule, success criteria)
- Version routing rules (which backend pools serve which versions)
- Real-time metrics comparison between stable and canary versions
Outputs:
- Circuit state (open/half-open/closed) per backend
- Fallback responses when circuit is open
- Circuit breaker metrics (state transitions, fallback invocations)
- Alerts when circuits open (backend is unhealthy)
- Canary traffic distribution percentages
- Canary health scores and promotion/rollback decisions
- Version-specific error rates and latency metrics for comparison
Canary Deployment Workflow:
- Initial Deployment (5% traffic)
- Deploy new version to dedicated backend pool
- Route 5% of traffic to canary, 95% to stable
- Monitor for 15-30 minutes, comparing error rates and latency
- Gradual Increase (25% → 50% → 75%)
- If success criteria met (error rate < 1%, latency within 10% of stable), increase traffic
- Each stage monitored for configured duration (soak period)
- Automatic rollback if canary metrics degrade significantly
- Full Rollout (100%)
- Once canary proves stable at 75%, promote to 100%
- Old version remains in standby for rapid rollback if needed
- After observation period, decommission old version
- Emergency Rollback
- Instant traffic shift back to stable version if canary fails
- Triggered by: error rate spike, latency degradation, circuit breaker trips, manual override
- Preserve canary logs and metrics for post-mortem analysis
Canary Success Criteria (configurable per API):
- Error rate: Canary error rate ≤ stable + 0.5%
- Latency: Canary p95 latency ≤ stable p95 + 10%
- Circuit breaker: No circuit trips on canary version
- Business metrics: No degradation in conversion rates, transaction success
- Duration: Each stage must maintain criteria for minimum soak period (e.g., 30 min)
Advanced Canary Features:
- Targeted canary groups: Beta subscriptions get canary version first (opt-in testing)
- Geographic rollout: Deploy to one region, then expand globally
- Header-based routing: Internal teams can test canary via
X-Canary-Version: v2.1.0header - Shadowing: Mirror production traffic to canary without serving responses (dark launch)
- Session affinity: Keep users on same version for session duration to avoid inconsistency
Cache Module
Purpose: Reduces backend load and improves latency by caching responses.
Key Responsibilities:
- HTTP caching based on Cache-Control headers
- Custom caching rules per API endpoint
- Cache GET requests for read-heavy APIs
- Invalidate caches on POST/PUT/DELETE operations
- Multi-level caching
- L1: In-memory cache per gateway instance (fast but not shared)
- L2: Distributed cache (Redis, Memcached) shared across instances
- Cache invalidation strategies
- TTL-based expiration
- Explicit invalidation on data changes
- Cache tags for bulk invalidation
- Conditional requests support (If-None-Match, ETag)
Technical Implementation:
- HTTP caching: RFC 7234 compliant
- Distributed cache: Redis cluster with automatic failover
- Cache key generation: URL, query params, headers, subscription ID
- Compression: gzip cached responses to reduce memory usage
Inputs:
- Cache-Control directives from backend responses
- Caching policies from API configuration
- Invalidation events from backends
Outputs:
- Cached responses for cache hits (faster latency)
- Cache metrics (hit rate, miss rate, eviction rate)
- Reduced backend load
Multi-Protocol Support
Purpose: Handle REST, GraphQL, and AsyncAPI as first-class protocols with protocol-appropriate processing.
The gateway supports three primary API protocols, each with specialized handling:
REST APIs (OpenAPI)
Routing: Path-based with HTTP method matching
GET /users-api/v2/users/{id} → users-service-v2:8080/users/{id}
POST /orders-api/v3/orders → orders-service-v3:8080/orders
Key Features:
- Standard HTTP caching (Cache-Control, ETag)
- Per-endpoint rate limiting
- Response field filtering based on subscription scope
GraphQL APIs
Routing: Single endpoint per API, all operations via POST
POST /orders-graphql/v2/graphql → graphql-service-v2:8080/graphql
Key Features:
- Query complexity limiting: Prevent expensive queries from overloading backends
- Assign cost per field (e.g., scalar = 1, list = 10, nested object = 5)
- Reject queries exceeding max cost per request
- Field-level authorization: Check subscription scope against requested fields
- Introspection control: Disable
__schemaqueries in production - Query depth limiting: Prevent deeply nested queries (max depth: 10)
- Persisted queries: Cache approved query hashes to reduce parsing overhead
GraphQL-Specific Logging:
{
"operation_name": "GetOrderWithItems",
"operation_type": "query",
"fields_accessed": ["order.id", "order.status", "order.lineItems.sku"],
"query_complexity": 42,
"depth": 3
}
AsyncAPI (Event-Driven)
Routing: WebSocket connections and message broker integration
wss://.../order-events/v2/events → WebSocket to event stream
kafka://.../orders.created.v2 → Kafka topic subscription
Key Features:
- Channel subscription validation: Verify consumer has subscription before allowing channel access
- Message rate limiting: Limit messages per second per subscription
- Dead letter handling: Route failed messages for investigation
- Connection management: Heartbeat, reconnection, graceful shutdown
Event-Specific Logging:
{
"channel": "orders.created",
"message_type": "OrderCreatedEvent",
"action": "subscribe",
"messages_delivered": 150,
"connection_duration_ms": 3600000
}
Protocol Selection by Use Case
| Use Case | Recommended Protocol | Reason |
|---|---|---|
| CRUD operations | REST (OpenAPI) | Clear resource modeling, HTTP caching |
| Mobile app with varied data needs | GraphQL | Client-specified fields, reduced over-fetching |
| Real-time notifications | AsyncAPI (WebSocket) | Push-based, persistent connection |
| Event sourcing, microservice integration | AsyncAPI (Kafka/AMQP) | Reliable delivery, decoupling |
| High-frequency data aggregation | GraphQL | Single request for multiple resources |
1.2 Gateway Management & Configuration
Configuration Management Service
Purpose: Manages gateway configuration and enables hot-reloading of routing rules without downtime.
Key Responsibilities:
- Fetch routing configuration from Registry API
- Sync rate limits, authorization policies, transformation rules
- Validate configuration before applying (prevent breaking changes)
- Atomic configuration updates across gateway cluster
- Rollback capability for bad configurations
- Configuration versioning and change tracking
Technical Implementation:
- Control plane / data plane separation (like Envoy xDS protocol)
- Configuration stored in Registry database, distributed to gateways
- Health checks before configuration activation
- Canary configuration rollout (test on subset of instances first)
Health Check & Service Discovery
Purpose: Tracks health of backend services and updates routing dynamically.
Key Responsibilities:
- Active health checking (periodic HTTP/TCP probes to backends)
- Passive health checking (monitor actual request success/failure rates)
- Service discovery integration (Consul, Kubernetes service discovery)
- Automatic backend rotation (remove unhealthy instances from pool)
- Graceful shutdown handling (drain connections before instance removal)
Technical Implementation:
- Health check protocols: HTTP, TCP, gRPC health checks
- Configurable intervals and thresholds (3 failures = unhealthy)
- Integration with orchestration platforms (Kubernetes readiness probes)
Gateway Admin API
Purpose: Provides operational API for monitoring and managing the gateway itself.
Key Responsibilities:
- Runtime statistics and metrics queries
- Health status of gateway instances
- Configuration reload triggers
- Traffic management (drain instance, enable/disable routes)
- Emergency controls (block specific IPs, disable endpoints)
Technical Implementation:
- RESTful admin API (separate port from data plane traffic)
- Authentication required for admin operations
- Rate limiting on admin API to prevent abuse
1.3 Gateway Deployment & Operations
High Availability:
- Multi-region deployment for disaster recovery
- Active-active load balancing across gateway instances
- No single point of failure (stateless gateway design)
Scaling:
- Horizontal auto-scaling based on request rate, CPU, latency
- Cluster coordination for distributed rate limiting
- Sticky sessions not required (stateless design)
Observability:
- Logs: All requests, errors, security events
- Metrics: Request rate, latency, error rate, resource usage
- Traces: Distributed tracing for end-to-end visibility
- Health checks: Gateway self-health monitoring
Security:
- DDoS protection via WAF integration
- Secrets management for API keys, certificates, encryption keys
- Regular security patching and vulnerability scanning
- Network isolation (private subnets for backend communication)
Next: API Registry