REST & GRAPHQL

APIs that hold your stack together

Every integration you will ever build depends on the quality of the interface underneath it. Get that wrong and you pay for it in every project afterwards.

SEE HOW IT WORKS
REST
and GraphQL
Typed
Contract-first
Documented
OpenAPI, generated
THE HONEST VERSION

The interface problems that compound

  • Every integration re-implements auth slightly differently, and rotating a key becomes a week of work.
  • There is no versioning, so any change risks breaking a consumer nobody has a list of.
  • The documentation is a Postman collection someone exported in 2024.
  • Rate limits are discovered in production, by hitting them during your busiest hour.
HOW IT WORKS

A real one, building itself.

Not a diagram of an idea. This is the shape of a system we have actually shipped for this service, assembling and then running a job.

TRIGGER
Client request
LOGIC
Auth + rate limit
ACTION
Service call
ACTION
Cache layer
ACTION
Typed response
WHAT YOU ACTUALLY GET

Six things, all of them yours.

Contract-first design

The OpenAPI or GraphQL schema is agreed before implementation, so consumers can build in parallel.

Authentication

API keys, OAuth2 or JWT with scoped permissions and a rotation path that does not require downtime.

Versioning

A deprecation policy that lets you change things without breaking every consumer at once.

Rate limiting

Per-key limits with clear headers, so consumers can back off correctly instead of hammering you.

Generated docs

Documentation produced from the schema, so it cannot drift out of date with the implementation.

Observability

Request logging, latency and error-rate metrics, with alerting on the thresholds that matter.

THE STACK

What we build this on.

Chosen per project, not per habit. If your team already runs something that works, we build on that instead.

Node.jsTypeScriptFastifyExpressGraphQLOpenAPI
PostgreSQLRedisOAuth2JWTDockerCloudflare
THE PROCESS

Four steps, no surprises.

Step 1
Design
Schema and endpoints agreed on paper first. Changing a contract later is far more expensive than arguing about it now.
Step 2
Build
Implemented against the contract, with schema validation on both request and response.
Step 3
Harden
Auth, rate limiting, error semantics and load testing before anything is exposed publicly.
Step 4
Publish
Generated documentation, a sandbox key and a versioning policy your consumers can rely on.
WHAT IT'S WORTH

Numbers we actually see.

100ms
typical p95 response on a cached read
0undocumented
endpoints shipped to consumers
2versions
supported concurrently during deprecation

Typical ranges from our own builds, not industry averages. Yours will depend on your process.

QUESTIONS WE GET

API Systems, answered.

REST or GraphQL?

REST for most integration work, because it is simpler to cache, easier for partners to consume and understood by every tool. GraphQL earns its complexity when you have many different clients each needing different shapes of the same data, particularly mobile clients where over-fetching costs real money.

Can you build an API on top of our existing database?

Yes, and that is a common shape: a clean interface in front of a schema you cannot easily change. It also gives you a place to enforce permissions and rate limits that the database itself has no concept of.

Do you handle authentication and security?

As standard, not as an extra. Scoped keys or OAuth2, secrets kept out of the codebase, request validation on every endpoint, and rate limiting from day one rather than after the first incident.

What about documentation?

Generated from the schema, so it cannot silently drift from the implementation. You get a browsable reference and a sandbox environment consumers can test against without touching production data.

NEXT STEP

Find out what this is worth to you.

A 20-minute call where we map your process and tell you honestly what is worth automating first, and what is not worth touching.