How do I manage LLM traffic across several apps from one place?

To manage LLM traffic across several apps from one place, the usual pattern is to put an LLM gateway / proxy layer in front of all model calls.

What that gives you

A single control point for:

• Routing requests to different models/providers
• API key management
• Rate limiting / quotas
• Logging and observability
• Caching
• Fallbacks and retries
• Cost tracking and chargeback
• Policy enforcement like PII redaction or prompt filtering

Common architecture

Your apps don’t call OpenAI/Anthropic/etc. directly. Instead:

App A / App B / App C → LLM Gateway → Model providers

The gateway can be:

• A managed service
• A self-hosted proxy
• A custom internal service

Popular options

Managed / platform tools

• OpenRouter: unified API for multiple model providers
• Azure AI Gateway / API Management: good if you’re already on Azure
• AWS Bedrock: centralized access to multiple models within AWS
• Google Vertex AI: similar centralized access in GCP

Gateway/proxy tooling

• LiteLLM Proxy: very common for multi-provider routing, keys, budgets, logging
• Langfuse + proxy/integration for tracing and observability
• Helicone: logging/monitoring layer for LLM APIs
• Portkey: gateway with routing, fallbacks, guardrails
• Kong / Apigee / Envoy with custom LLM policies if you want generic API management

What to centralize

A good “single place” typically handles:

1) Authentication

• One internal API key per app/team
• Map apps to allowed models and budgets

2) Routing

Rules like:

• Use cheaper model for simple tasks
• Use stronger model for complex tasks
• Route by app, environment, or tenant
• Switch providers automatically on failure

3) Rate limits and budgets

• Per app
• Per user
• Per team
• Per project
• Monthly spend caps

4) Logging and tracing

Capture:

• Prompt/response metadata
• Latency
• Token usage
• Errors
• Model chosen
• Cost

5) Safety and compliance

• PII masking
• Content filtering
• Audit trails
• Data retention controls

Best practice setup

If you want a practical, flexible setup, a common choice is:

• LiteLLM Proxy as the internal gateway
• Langfuse or Helicone for observability
• Your apps use a single internal endpoint
• Gateway enforces policies and forwards to OpenAI/Anthropic/Gemini/etc.

Minimal implementation idea

Each app uses something like:

POST https://llm-gateway.company.com/v1/chat/completions
Authorization: Bearer INTERNAL_APP_KEY

Then the gateway decides:

• which provider to use
• which upstream API key to apply
• whether to log, redact, retry, or block

If you want the simplest path

• Few apps, low complexity: use a managed gateway or direct API management platform
• Multiple apps, multiple providers, budget controls: use LiteLLM Proxy or similar
• Enterprise governance: add API management + observability + policy checks

If you want, I can suggest a setup based on your environment:

• AWS / Azure / GCP / on-prem
• number of apps
• whether you need routing, logging, or cost controls