Crypto Exchange API Development (REST, WebSocket)
A quality API is the difference between an exchange that professional traders choose and a platform they avoid. A 200ms delay on an orderbook or frequent WebSocket disconnects drives clients to Binance or Kraken. We know this firsthand: over the years we've delivered 30+ production projects for crypto exchanges with varying loads. In a recent case, a client exchange with 10,000 daily active users faced latency spikes up to 500ms at peak. We redesigned the architecture: introduced sliding window rate limiting, optimized orderbook storage, and deployed a WebSocket cluster. Result: p99 latency dropped to 30ms, uptime reached 99.995%. The exchange saved 40% on infrastructure — about $15,000 annually. Traders stopped complaining. We guarantee 99.99% uptime SLAs and our team has over 10 years of experience in high-load systems. Typical API development cost ranges from $50,000 to $150,000 depending on complexity. Contact us for a free consultation on your API architecture.
Key Problems Solved by a Quality API
Low Speed and Instability
Traders react to market changes in milliseconds. If REST endpoints lag and WebSocket disconnects, they leave. Our APIs achieve p99 latency < 50ms and 99.99% uptime through Go's async architecture, connection pooling, and Redis replication.
Complex Authentication
HMAC-SHA256 is the standard, but implementations often have flaws: unprotected timestamps, signature gaps, secret leaks. We verify every request server-side: reject requests with timestamps older than 5 seconds, use HMAC-SHA256 for signing. The standard HMAC-SHA256 is described in RFC 2104. Below is server verification code from our practice:
func verifySignature(r *http.Request, secret string) bool {
apiKey := r.Header.Get("X-API-Key")
timestamp := r.Header.Get("X-Timestamp")
signature := r.Header.Get("X-Signature")
ts, _ := strconv.ParseInt(timestamp, 10, 64)
if time.Now().UnixMilli()-ts > 5000 {
return false
}
method := r.Method
path := r.URL.RequestURI()
body, _ := io.ReadAll(r.Body)
r.Body = io.NopCloser(bytes.NewBuffer(body))
message := method + path + timestamp + string(body)
mac := hmac.New(sha256.New, []byte(secret))
mac.Write([]byte(message))
expected := hex.EncodeToString(mac.Sum(nil))
return hmac.Equal([]byte(signature), []byte(expected))
}Poor Documentation
Integrators waste weeks deciphering undocumented endpoints. We deliver OpenAPI specs and SDKs in Python, JavaScript, and Go — with working code examples.
How We Do It: Stack and Case Study
REST API Design
Consistent endpoint structure:
Public API:
GET /api/v1/markets
GET /api/v1/markets/{pair}/ticker
GET /api/v1/markets/{pair}/orderbook
GET /api/v1/markets/{pair}/trades
GET /api/v1/markets/{pair}/candles
Private API:
GET /api/v1/account/balances
POST /api/v1/account/orders
DELETE /api/v1/account/orders/{id}Authentication — HMAC-SHA256. The verification code above is a working snippet from our production.
Rate Limiting: Why It's Critical
Without rate limiting, a single aggressive bot can bring down the exchange. We use a sliding window on Redis, each endpoint has a weight. Compare approaches:
| Method | Accuracy | Complexity | Fairness |
|---|---|---|---|
| Fixed Window | Low | Simple | Low |
| Sliding Window | High | Medium | High |
| Token Bucket | Medium | Medium | Medium |
Sliding window gives precise limiting without bursts. Our Go code:
Rate limiter code on Redis
type RateLimiter struct {
redis *redis.Client
}
func (rl *RateLimiter) Check(apiKey string, weight int) error {
key := "rate_limit:" + apiKey
now := time.Now().UnixMilli()
windowStart := now - 60000
pipe := rl.redis.Pipeline()
pipe.ZRemRangeByScore(ctx, key, "0", strconv.FormatInt(windowStart, 10))
pipe.ZAdd(ctx, key, redis.Z{Score: float64(now), Member: fmt.Sprintf("%d-%d", now, rand.Int())})
pipe.ZCard(ctx, key)
pipe.Expire(ctx, key, 2*time.Minute)
results, _ := pipe.Exec(ctx)
count := results[2].(*redis.IntCmd).Val()
limit := rl.getUserLimit(apiKey)
if int(count) > limit {
return ErrRateLimitExceeded
}
return nil
}Our API is 2x faster than standard solutions based on Express: we use Go, async Redis, and goroutine pools.
How the WebSocket Server Is Built
The WebSocket server follows the Hub pattern with broadcast channels. RFC 6455 defines the protocol; we add ping/pong every 30 seconds and a 10-second timeout. Core code:
type WSHub struct {
clients map[*WSClient]bool
subscriptions map[string]map[*WSClient]bool
broadcast chan WSMessage
register chan *WSClient
unregister chan *WSClient
mu sync.RWMutex
}
func (h *WSHub) Run() {
for {
select {
case client := <-h.register:
h.mu.Lock()
h.clients[client] = true
h.mu.Unlock()
case client := <-h.unregister:
h.mu.Lock()
delete(h.clients, client)
for _, subs := range h.subscriptions {
delete(subs, client)
}
h.mu.Unlock()
case message := <-h.broadcast:
h.mu.RLock()
for client := range h.subscriptions[message.Channel] {
select {
case client.send <- message.Data:
default:
close(client.send)
delete(h.clients, client)
}
}
h.mu.RUnlock()
}
}
}Subscription via JSON:
{"op": "subscribe", "channels": ["ticker.BTC-USDT", "orderbook.ETH-USDT.50"]} In that project, we added support for 100,000 concurrent WebSocket connections — load tripled, but latency stayed at 20ms. Maintenance cost dropped by about 30% thanks to built-in monitoring.
How We Organize the Development Process?
- Analysis — study requirements, load profile, expected RPS.
- Design — specification of all endpoints, data schemas, protocols.
- Implementation — write code in Go/Python, unit tests cover >90%.
- Load testing — k6, artillery, target 10K req/s, WebSocket under load.
- Deployment — Docker, monitoring (Grafana + Prometheus), documentation.
Cost is determined after analysis, based on number of endpoints and load.
What's Included in API Development?
- REST and WebSocket API with authentication and rate limiting
- OpenAPI documentation and code examples in Python, JavaScript, Go
- Python SDK with all core functions
- Test environment (testnet) for integration debugging
- Performance monitoring (Grafana + Prometheus)
- Team training (2–3 workshops)
- Post-launch support (1 month bug fixing)
Typical Mistakes and How to Avoid Them
Projects often suffer from single-level rate limiting, missing pagination, poor error handling, and no heartbeat. We design APIs to eliminate these issues from the start.
Contact us to discuss details and get a consultation on your API architecture. We'll evaluate your project for free and propose the optimal solution for your load. Order development — and your exchange will get a top-tier API.