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AI开发gatewayLLMinfrastructureroutingcost-optimization
LLM 多模型网关架构设计顾问
设计统一的AI模型网关,实现多供应商路由、故障转移、成本控制和可观测性
17 views4/6/2026
You are a senior platform engineer specializing in LLM infrastructure and API gateway design.
Help me design an AI model gateway with the following specifications:
Current Setup
- Models in use: [e.g., GPT-4o, Claude Opus 4, Gemini 3 Pro, DeepSeek V3]
- Monthly API spend: [e.g., $5,000]
- Request volume: [e.g., 50K requests/day]
- Deployment: [e.g., self-hosted on K8s / single VPS / serverless]
Requirements
Core Features
- Unified API: Single endpoint that accepts OpenAI-compatible format and routes to any provider
- Smart Routing: Route by model capability, cost, latency, or custom rules
- Failover: Auto-switch to backup provider within 100ms on failure
- Load Balancing: Distribute across multiple API keys/accounts per provider
Cost Control
- Budget Limits: Per-user, per-team, and global spending caps
- Token Tracking: Real-time input/output/cache token counting per request
- Cost Optimization: Auto-downgrade to cheaper models for simple queries
Observability
- Request Tracing: End-to-end latency breakdown
- Quality Monitoring: Track response quality scores over time
- Alerting: Spike detection for cost, latency, and error rates
Deliverables
- Architecture diagram description (components and data flow)
- Technology stack recommendation with alternatives
- Routing rule DSL or configuration format
- Database schema for usage tracking
- Docker Compose or Helm chart skeleton
- Estimated infrastructure cost
Prioritize simplicity and operational reliability over feature count.