LLM Gateway for Spring Boot: Multi-tenant API Keys, Quotas, and Cost Controls

Problem

Once multiple teams or customers share LLM capabilities, costs and risk become operational problems:

• leaked keys lead to runaway spend
• one tenant can starve everyone else
• prompt abuse increases latency and bill
• you cannot answer basic questions like “who spent what, when, and why?”

This solution implements a production-grade LLM Gateway that centralizes authentication, tenant isolation, quotas, caching, and audit logging — so you can expose LLM features safely inside a SaaS or internal platform.

What You Get

• A single gateway endpoint for all LLM calls (OpenAI-compatible)
• Multi-tenant API keys and policy enforcement
• Quotas: QPS + daily/monthly spend caps
• Token budgeting + max output clamp
• Request/response auditing (redaction-ready)
• Caching for repeated prompts (optional)
• Runnable Docker Compose environment

Who This Is For

Backend/platform engineers building:

• SaaS products with “AI features”
• internal LLM platforms for multiple teams
• cost-governed LLM enablement layers

Key Constraints

• You must decide your tenant model (API key ↔ tenant ↔ project)
• Quotas require a durable store for usage counters (PostgreSQL/Redis)
• You should define a redaction policy if prompts may contain sensitive data

When NOT to Use This

• If your usage is single-tenant with one trusted team (direct SDK may be enough)
• If you need ultra-low latency and cannot tolerate an extra hop
• If you have strict “no prompt storage” policies and can’t run redaction safely

Upgrade to Pro

Pro includes full implementation:

• gateway request pipeline, policy engine, and quota counters
• schema + migrations + runnable code bundle
• cost controls and failure-mode runbooks
• evidence artifacts (audit records, quota enforcement, cache hits)