How an API Gateway Works: The Request Lifecycle

2026-09-08 · 5 min read · SubToAPI Team

An API gateway works by sitting between clients and backend services as a single entry point, intercepting every request, applying a chain of checks and transformations, and then forwarding the request to the right service before returning a response. Instead of clients talking directly to dozens of internal services, they talk to one URL, and the gateway handles the routing, security, and bookkeeping behind the scenes.

The rest of this article walks through exactly what happens between the moment a client sends a request and the moment it gets a response, because that's the part most explanations skip.

The request lifecycle, step by step

1. Connection and TLS termination

The client opens a connection to the gateway's public endpoint. The gateway terminates TLS here, meaning it decrypts the incoming HTTPS traffic. This is also where the gateway can enforce which TLS versions and ciphers are acceptable, before any application logic runs.

2. Authentication

The gateway checks whether the request is allowed to proceed at all. This usually means validating an API key, a JWT, or an OAuth token found in a header like Authorization: Bearer <token>. If the credential is missing or invalid, the gateway rejects the request immediately with a 401 — the backend service never sees it.

curl https://api.example.com/v1/orders \
  -H "Authorization: Bearer sk_live_abc123"

3. Rate limiting and quota enforcement

Once identity is established, the gateway checks whether this client (or this API key, or this IP) has exceeded its allowed request rate. This is typically implemented with a token bucket or sliding window counter kept in memory or in a fast store like Redis. If the limit is exceeded, the gateway returns a 429 without forwarding the request, protecting backend services from overload.

4. Routing

The gateway inspects the request path, method, and sometimes headers to decide which backend service should handle it. A request to /v1/users might route to a users microservice, while /v1/orders routes to an orders service. This mapping is usually defined in a routing table or config file, and it's what lets the gateway present one unified API surface over many independent services.

5. Request transformation

Before forwarding, the gateway may rewrite the request: stripping internal headers, adding trace IDs, converting protocols (say, REST in from the client, gRPC out to the service), or reshaping the payload. This lets backend teams change internal contracts without breaking the public API.

6. Forwarding to the backend

The gateway opens a connection to the selected backend instance — often through a load balancer or service discovery layer — and forwards the (possibly transformed) request. It typically applies a timeout here so a slow or hung backend doesn't tie up the gateway indefinitely.

7. Response handling

When the backend responds, the gateway can transform the response the same way it transformed the request: normalizing error formats, stripping sensitive internal fields, or adding CORS headers. For streaming responses, the gateway keeps the connection open and passes chunks through as they arrive rather than buffering the whole payload.

8. Logging and metrics

Finally, the gateway records what happened: status code, latency, which client made the call, how many tokens or bytes were used. This is the layer that makes usage-based billing, debugging, and audit trails possible, because every request already flows through one choke point.

Why this single-point design matters

Centralizing all of this logic in one layer has a few concrete benefits:

Consistency — auth, rate limiting, and logging are implemented once, not reimplemented (and possibly done wrong) in every service.
Isolation — backend services don't need to know about public-facing concerns like TLS or CORS.
Observability — because every request passes through the gateway, you get a single place to see traffic patterns, error rates, and usage per client.
Change control — you can version, deprecate, or redirect routes without touching backend code.

The tradeoff is that the gateway becomes a critical path component — if it's down or slow, everything behind it is unreachable, which is why production gateways are usually run with redundancy and aggressive timeout/circuit-breaker settings.

A worked example

Say you've built an internal tool on top of Claude and you want to expose it as a stable HTTPS API for your product, without your app's users ever seeing your provider credentials or configuring rate limits themselves. This is exactly the pattern above, applied to one specific case: SubToAPI sits in front of your Claude access and issues its own application-scoped API keys (sub_live_...), so each request goes through authentication, then straight to streaming responses, tool calls, and usage metadata — with no separate proxy to build or maintain.

const response = await fetch("https://api.subtoapi.app/v1/messages", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.SUBTOAPI_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "claude-3-5-sonnet-20241022",
    max_tokens: 1024,
    messages: [{ role: "user", content: "Summarize this ticket." }]
  })
});

Under the hood, that single request goes through the same steps outlined above: key validation, rate/quota check, routing to the correct backend, and response streaming back to your app — the same mechanics as any API gateway, just tuned for this one use case. Full request and response shapes are in the docs, with a working example in the quickstart.

Common implementation choices

Not every gateway implements every step the same way:

Where auth lives — some gateways delegate token validation to an external identity provider per request; others cache validated tokens for a short window to cut latency.
Where rate limits are stored — in-process counters are fast but don't work across multiple gateway instances; a shared store like Redis fixes that at the cost of a network hop.
How routing is configured — static config files are simple and auditable; dynamic service discovery scales better but adds moving parts.
How much transformation happens — a "thin" gateway just proxies and authenticates; a "thick" gateway also handles protocol translation, request aggregation, and response shaping.

None of these are universally right — they depend on how many services you have, how much traffic you're handling, and how much control you want over the request path versus how much complexity you're willing to run.

Questions

Does an API gateway add latency to every request? Yes, but usually a small, fixed amount — typically low single-digit milliseconds for auth and routing checks. The bigger cost comes from poorly tuned timeouts or synchronous calls to slow external services during the request path.

Can an API gateway handle streaming responses? Yes, as long as it's built to pass chunks through as they arrive instead of buffering the full response before replying. This matters for use cases like LLM token streaming, where waiting for the full response defeats the purpose.

Is an API gateway the same as a reverse proxy? A reverse proxy forwards requests and can do basic load balancing, but an API gateway adds application-aware logic on top: authentication, rate limiting, request/response transformation, and per-client usage tracking.