REST · GraphQL · Microservices

APIs designed to
last longer than
the team that built them

An API is a contract. Break it carelessly and you break every product built on top of it. We design RESTful and GraphQL APIs with versioning, documentation, and error handling baked into the architecture from the first endpoint - not retrofitted before launch.

300+ APIs in Production
99.99% Uptime SLA
28ms P95 Latency
100% OpenAPI Documented
sequere-api.io / v2 / explorer
Connected
Request
Response
Headers
Schema
GET https://api.sequere.io/v2/users/{id}/orders
Run
Authorization Bearer eyJhbGciOiJSUzI1NiJ9.ey...
Content-Type application/json
X-API-Version 2024-01
200 OK ⚡ 28ms application/json · 2.4 KB
{ "success": true, "data": { "user_id": "usr_4k9mxp2q", "orders_total": 147, "orders": [array · 10 { "id": "ord_8xwvl", "status": "fulfilled" }, { "id": "ord_2mnbk", "status": "pending" } ] }, "meta": { "page": 1, "per_page": 10, "total": 147 } }
Response Latency (P95)
Active Endpoints
GET/v2/users/{id}Live
POST/v2/ordersLive
PATCH/v2/orders/{id}v2.1
DEL/v2/users/{id}Live

Every type of API. One engineering standard.

Whether you need a straightforward REST API, a flexible GraphQL layer, or a distributed microservices mesh - we design for the consumers of the API, not just the team building it.

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RESTful API Design & Development

REST APIs built around resource-oriented design, consistent error responses, clear versioning strategy, and hypermedia links where they add genuine value. We write the OpenAPI specification first and generate server stubs from it - ensuring the documentation never drifts from the implementation.

OpenAPI 3.1 Resource Modelling Versioning Strategy Pagination Rate Limiting HATEOAS
300+ REST endpoints in production across client integrations

GraphQL API Development

Schema-first GraphQL APIs with DataLoader for N+1 prevention, field-level authorisation, query depth limiting, and persisted queries for production performance. We design the schema around client needs - not the backend data model.

Schema-First DataLoader Subscriptions Complexity Limits

Microservices Architecture

Service decomposition, API gateway design, inter-service communication patterns, and event-driven architecture with message queues. We define service boundaries around business domains - not technical convenience - to avoid the distributed monolith trap.

API Gateway Event-Driven Service Mesh Kafka / RabbitMQ

Third-Party API Integrations

Clean, resilient integrations with payment gateways, CRMs, ERPs, marketing platforms, and data providers - wrapped in abstraction layers so a vendor change doesn't ripple through your entire codebase.

Stripe / PayPal Salesforce Webhook Management Circuit Breakers

API Security & Authentication

OAuth 2.0 and OpenID Connect implementation, JWT handling, API key management, scopes, and RBAC. Rate limiting, IP allowlisting, request signing, and OWASP API Security Top 10 coverage built in from the start.

OAuth 2.0 / OIDC JWT API Keys OWASP API Top 10

Spec first, code second —
always

01
Wk 1–2

API Design & Contract

Define resource models, URL structure, request/response schemas, error codes, and versioning strategy in an OpenAPI spec - reviewed and agreed before any development begins.

OpenAPI 3.1 spec + Postman collection
02
Wk 3–4

Authentication & Security Layer

Implement OAuth 2.0, JWT validation, rate limiting, CORS policy, and request signing. Security is designed into the API architecture, not layered on afterwards.

Auth implementation + Security audit
03
Wk 5–9

Core Endpoint Development

Build endpoints against the agreed spec with full test coverage. Integration tests, contract tests, and load tests run in CI on every commit. No endpoint ships without passing all three.

Tested endpoints + CI pipeline
04
Wk 10+

Docs, SDK & Deployment

Auto-generated developer documentation from the OpenAPI spec, optional SDK generation for key languages, staging and production deployment, monitoring setup, and developer onboarding guide.

Live API + docs portal + SDK

REST, GraphQL, or gRPC - the decision matters more than most teams realise

Each protocol solves a different problem. We make the recommendation based on your consumers, your team's operational capabilities, and your performance requirements - not on what's fashionable this quarter.

REST - The sensible default for most APIs

REST remains the right choice for the majority of public-facing and partner APIs. The conventions are widely understood, tooling is mature, caching is straightforward, and any client in any language can consume it without specialised libraries. We follow Fielding's constraints properly - not just "it uses HTTP and returns JSON."

JSON Copy
GET /v2/orders/ord_8xwvl
Authorization: Bearer {token}

// Response 200 OK
{
  "id": "ord_8xwvl",
  "status": "fulfilled",
  "total": 148.50,
  "currency": "GBP",
  "_links": {
    "self": "/v2/orders/ord_8xwvl",
    "user": "/v2/users/usr_4k9mxp2q"
  }
}

Uniform resource-based URLs

Predictable, self-documenting endpoint structure that any developer can navigate without reading the full spec.

HTTP semantics used correctly

GET is idempotent, POST creates, PUT replaces, PATCH updates, DELETE removes. Status codes mean what they're supposed to mean.

OpenAPI spec always in sync

We write the spec first and generate server stubs from it - the documentation is never a post-hoc retrofit.

Caching at every layer

ETag support, Cache-Control headers, and CDN-compatible endpoint design included as standard.

GraphQL - Right when clients need flexibility

GraphQL earns its complexity when you have multiple client types with genuinely different data needs - a mobile app, a web dashboard, and a third-party integration all hitting the same API but wanting different shapes of data. It eliminates over-fetching and under-fetching, but introduces query complexity and N+1 challenges that require careful schema design and DataLoader implementation to handle correctly.

GRAPHQL Copy
query GetUserOrders($userId: ID!, $first: Int!) {
  user(id: $userId) {
    name
    email
    orders(first: $first, status: FULFILLED) {
      edges {
        node {
          id
          total
          createdAt
          items { sku quantity }
        }
      }
      pageInfo { hasNextPage endCursor }
    }
  }
}

Schema-first design

The schema is the contract. We define it before writing resolvers, and document every field, type, and directive.

N+1 prevention with DataLoader

Batch-loading for all related entity fetches. No GraphQL endpoint ships without DataLoader where association queries exist.

Query complexity analysis

Depth limits, complexity scoring, and introspection controls protect the API from expensive query abuse.

Real-time with subscriptions

WebSocket-based subscriptions for live data use cases - order status, notifications, collaborative editing.

gRPC - When latency and throughput are the priority

gRPC is the right choice for internal microservice communication where you need high throughput, bidirectional streaming, and strong typing across service boundaries. Protocol Buffers give you a typed contract between services that fails at compile time rather than at runtime, and binary serialisation is significantly faster than JSON for high-volume internal traffic.

PROTOBUF Copy
syntax = "proto3";

service OrderService {
  rpc GetOrder (OrderRequest) returns (Order);
  rpc StreamOrders (UserRequest) returns (stream Order);
  rpc BatchCreateOrders (stream CreateOrderRequest)
    returns (BatchResult);
}

message Order {
  string id = 1;
  string status = 2;
  double total = 3;
  int64 created_at = 4;
}

Protobuf schema validation

Strongly-typed contracts between services that catch breaking changes at compile time, not in production.

Bidirectional streaming

Client, server, and bidirectional streaming for high-volume data pipelines and real-time communication between services.

Significantly lower latency

Binary serialisation and HTTP/2 multiplexing reduce internal service call overhead compared to REST/JSON at scale.

Code generation

Client and server stubs generated from the proto definition across Go, Node.js, Python, and Java simultaneously.

WebSockets - For genuinely real-time requirements

WebSockets are appropriate when data changes that the client needs to see happen faster than polling can realistically handle - sub-second updates, collaborative features, or push notifications that need to be instant. We implement connection management, heartbeat handling, reconnection logic, and horizontal scaling with Redis pub/sub so the real-time layer stays reliable under load.

JAVASCRIPT Copy
// Server (Node.js)
const wss = new WebSocketServer({ port: 8080 });

wss.on('connection', (ws, req) => {
  const userId = authenticate(req);
  subscribeToUserEvents(userId, (event) => {
    ws.send(JSON.stringify({
      type: event.type,
      payload: event.data,
      ts: Date.now()
    }));
  });

  ws.on('message', handleClientMessage);
  ws.on('close', () => unsubscribe(userId));
});

Connection lifecycle management

Heartbeat pings, graceful reconnection with exponential backoff, and connection state tracking included as standard.

Horizontal scaling with Redis

Pub/sub message broadcasting ensures real-time events reach clients regardless of which server instance holds their connection.

Room and channel architecture

Scoped subscriptions so clients only receive events relevant to them - no unnecessary data transmission.

Fallback to SSE or polling

Server-Sent Events or long-polling fallback for environments where WebSocket connections are blocked by firewalls or proxies.

Webhooks - The right way to push events to consumers

Webhooks are often the simplest and most reliable way to notify external systems about events in your platform. Done well, they include retry logic with exponential backoff, event ordering guarantees, payload signing so consumers can verify authenticity, and a delivery log so consumers can replay missed events. Done badly, they're a support ticket waiting to happen.

JAVASCRIPT Copy
// Webhook dispatcher
async function dispatchWebhook(endpoint, event) {
  const payload = JSON.stringify(event);
  const signature = createHMAC(
    process.env.WEBHOOK_SECRET,
    payload
  );

  const res = await fetch(endpoint.url, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'X-Sequere-Signature': signature,
      'X-Sequere-Timestamp': Date.now()
    },
    body: payload
  });
  return res.status;
}

HMAC payload signing

Every webhook payload is signed with a consumer-specific secret. Consumers can verify authenticity before processing.

Retry with exponential backoff

Failed deliveries retry up to 72 hours with exponential backoff - consumers don't miss events because of temporary downtime.

Delivery log and replay

Complete delivery history with one-click replay for any failed event. Consumers can self-serve missed events without contacting support.

Endpoint health monitoring

Automatic detection and alerting when consumer endpoints start returning errors, before the consumer notices.

What makes an API genuinely good - and how we make sure every one we ship qualifies

A good API is invisible to the developers consuming it. Everything is where they'd expect it to be, errors tell them what actually went wrong, and the documentation matches what the API actually does.

Talk to an API engineer

Spec-first - documentation that never lies

We write the OpenAPI specification before writing any implementation code. Server stubs are generated from the spec, which means the documentation and the actual API behaviour are structurally identical by construction - not by discipline. When the spec changes, the tests catch any implementation drift automatically.

OpenAPI 3.1Spec-Driven DevContract TestingPrism Mocking

Versioning strategy from the first endpoint

Breaking changes are inevitable. The question is whether you handle them gracefully or with a hard cutover that breaks integrators. We design versioning strategy before the first endpoint is built - URI versioning, header versioning, or sunset policies - so future changes can be made without forcing immediate migration.

URI VersioningDeprecation HeadersSunset PoliciesChangelog Automation

Errors that actually help developers debug

The standard for API error responses is embarrassingly low. Most return a HTTP status code and a generic message. We return structured error objects with a machine-readable code, a human-readable message, a link to the relevant documentation section, and field-level validation details where relevant. Developers fix problems faster. Support tickets go down.

RFC 7807 Problem DetailsMachine-Readable CodesField-Level ErrorsDocs Deep-Links

Performance engineered in, not optimised later

Pagination on every collection endpoint. N+1 query prevention via DataLoader or eager loading strategy. Database indexes reviewed for every query path. Response compression enabled. Connection pooling configured. We treat these as requirements with acceptance criteria - not suggestions applied when someone complains the API is slow.

Cursor PaginationQuery OptimisationResponse CompressionConnection Pooling

Developer experience is a first-class concern

An API nobody can figure out how to use is a liability, not an asset. We provide auto-generated interactive documentation (Scalar or Redoc), Postman collections, code samples in at least three languages, and - for partner APIs - SDK generation from the OpenAPI spec. Developer time to first successful request is a metric we track.

Scalar / RedocPostman CollectionsSDK GenerationCode Samples

Framework-agnostic.
Production-opinionated.

We select based on your team's operational capabilities, performance requirements, and what you'll actually be able to maintain at 2am when something breaks.

Languages
Node.js / TypeScriptGoPython (FastAPI)Java (Spring Boot)Rust (Axum)
Frameworks
ExpressFastifyHonotRPCNestJSGinEcho
API Spec & Docs
OpenAPI 3.1GraphQL SDLScalarRedocStoplightSwagger UI
Auth & Security
OAuth 2.0OpenID ConnectJWT (RS256)API KeysHMAC SigningKong / Nginx
Testing
Jest / VitestSupertestDreddPostman / Newmank6 Load TestingOWASP ZAP
Infra & Observability
AWS API GatewayCloudflare WorkersKubernetesDataDog APMSentryGrafana
Messaging / Async
KafkaRabbitMQAWS SQS / SNSRedis Pub/SubWebhooksServer-Sent Events

APIs we've shipped - and what they handle today

Production results from APIs handling real transaction volumes across fintech, healthtech, and enterprise platforms.

// Response 200 OK "id": "txn_9xkwp2m", "amount": 1480.00, "currency": "GBP", "status": "settled"
Financial Services

Payment & Ledger API

Core REST API powering a fintech platform - handling payment initiation, transaction ledger, FX conversions, and compliance reporting across 14 currencies. PCI-DSS compliant, SOC 2 Type II audited.

12M+ Requests / month
28ms P95 latency
// Response 200 OK "resourceType": "Patient", "id": "pt_7mxkq", "status": "active", "meta": { "versionId": "3" }
Healthcare

FHIR-Compliant Patient Data API

HL7 FHIR R4 REST API enabling secure exchange of patient records between hospital systems, GP practices, and insurers. Full audit trail, role-scoped access, and end-to-end encryption at rest and in transit.

HIPAA Compliant
99.99% Uptime SLA
// Response 200 OK "vendor": "VendorCo", "sku": "PRD-8821-XL", "stock": 142, "price": { "amount": 49.99 }
E-Commerce

Multi-Vendor Marketplace API

GraphQL API serving a multi-vendor marketplace - products, inventory, orders, and vendor payouts all in a single schema. Real-time inventory updates via subscriptions, and automated payout calculations across 2,000+ sellers.

2,000+ Active vendors
4.2M Products indexed

Questions we get before every API project

Straight answers on versioning, documentation, costs, and timeline. Anything else - ask directly.

The honest answer is that REST is the right choice for most APIs - it's well-understood, highly cacheable, and easy to consume in any language without specialised tooling. GraphQL becomes genuinely valuable when you have multiple distinct client types (mobile, web, third-party) that need materially different shapes of the same data, and where the over-fetching cost of REST responses is measurable. We don't recommend GraphQL because it's interesting - we recommend it when the performance and flexibility trade-offs are actually justified by your client landscape.
A focused REST API with 15–25 endpoints, authentication, documentation, and tests typically takes 6–10 weeks from spec sign-off to production deployment. A more complex API with microservices architecture, custom auth flows, or significant third-party integration work is typically 12–20 weeks. Timeline accuracy depends heavily on how clear the requirements are - our two-week spec phase is designed to remove ambiguity before it becomes schedule risk.
Every API we deliver includes a live interactive documentation portal (Scalar or Redoc) auto-generated from the OpenAPI specification, a Postman collection with example requests for every endpoint, code samples in at least three languages (TypeScript, Python, and cURL as standard), a changelog documenting every version and breaking change, and a getting-started guide with authentication walkthrough. For partner APIs, we can also generate client SDKs in additional languages on request.
We define versioning strategy in the design phase before writing any code. The most common approach for REST APIs is URI versioning (/v1/, /v2/) combined with a deprecation policy - we add a Sunset header to deprecated endpoints well in advance of removal, and maintain old versions for a minimum period agreed with you. For internal APIs, header-based versioning is often cleaner. We document the versioning approach in the API spec so every consumer understands the contract from day one.
Yes - and we do this regularly. We wrap third-party API integrations in abstraction layers so vendor changes don't propagate through your codebase. We implement circuit breakers (so a third-party outage doesn't take down your API), retry logic with exponential backoff, dead-letter queues for failed operations, and monitoring so you know about third-party degradation before your users do. Common integrations include Stripe, PayPal, Salesforce, HubSpot, SAP, and most major cloud data providers.
We run four layers of automated testing on every API: unit tests for individual functions, integration tests for endpoint behaviour against a real database, contract tests (Dredd or Pact) verifying the implementation matches the OpenAPI spec, and load tests with k6 to validate behaviour under target traffic volumes. These all run in CI on every commit. Before production, we also run a manual security review against the OWASP API Security Top 10. No endpoint ships without passing all four layers.
We offer a structured post-launch support retainer that covers monitoring and alerting, security patch management, dependency updates, performance optimisation as traffic grows, and incident response. If you're taking the API in-house after launch, we include 30 days of hypercare support and a comprehensive handover package - runbook, architecture documentation, codebase walkthrough recording, and escalation contacts for the first year.
Yes. We've built HIPAA-compliant healthcare APIs, PCI-DSS-compliant payment APIs, and FCA-regulated financial data APIs. Regulated work requires additional design considerations - data classification, audit logging, encryption-at-rest and in-transit, access control documentation, and penetration testing by an approved third party. We've been through these processes enough times to scope the additional requirements accurately and plan for them, rather than discovering the regulatory overhead mid-project.

Let's design your API before we write a single line of code

Book a free 45-minute call with one of our API engineers. We'll map out your endpoints, talk through authentication requirements, and give you a clear scope - timeline and cost - before any commitment.

Book a Free Call
No commitment required
NDA available on request
Response within 24 hours