Prompt

api routing by header and path

Technology / API Platforms1 observationLast seen Oct 6, 2026

Latest observation

Oct 6, 2026OpenAI APIWeb search: off

If you mean routing API traffic based on both the request path and a header, the usual setup is:

  • Path-based routing: /v1/users, /v2/users
  • Header-based routing: route only if a header matches, e.g. X-Tenant: premium or Accept: application/vnd.myapi.v2+json
  • Combined routing: both conditions must match

Common examples

1) NGINX

You can route using map + location:

map $http_x_api_version $backend {
    default         backend_v1;
    "2"             backend_v2;
}

server {
    listen 80;

    location /api/users {
        proxy_pass http://$backend;
    }
}

For more complex path + header logic, you can use if carefully or multiple location blocks.


2) Kong / API Gateway

Most API gateways support this directly with routes like:

  • Path: /api/users
  • Header: X-API-Version: 2

Then forward to different upstream services.


3) Express / Node.js

You can do header + path checks in middleware:

app.use('/api/users', (req, res, next) => {
  if (req.headers['x-api-version'] === '2') {
    return v2Handler(req, res);
  }
  return v1Handler(req, res);
});

4) Spring Cloud Gateway

Route with predicates:

spring:
  cloud:
    gateway:
      routes:
        - id: users_v2
          uri: http://users-v2
          predicates:
            - Path=/api/users/**
            - Header=X-API-Version, 2
        - id: users_v1
          uri: http://users-v1
          predicates:
            - Path=/api/users/**

Pattern

Typically:

  1. Match path first
  2. Check header
  3. Send to matching backend
  4. Fallback if header missing or unknown

Example use cases

  • API versioning
  • A/B testing
  • Canary releases
  • Multi-tenant routing
  • Feature flags

If you want, I can give you an example for a specific stack like NGINX, Kubernetes Ingress, AWS API Gateway, Kong, Spring Boot, or Express.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as Circuit. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.