Implement Customer.io rate limiting and backoff. Use when handling high-volume API calls, implementing retry logic, or hitting 429 errors. Trigger: "customer.io rate limit", "customer.io throttle", "customer.io 429", "customer.io backoff", "customer.io too many requests".
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npx tessl skill review --optimize ./plugins/saas-packs/customerio-pack/skills/customerio-rate-limits/SKILL.mdUnderstand Customer.io's API rate limits and implement proper throttling: token bucket limiters, exponential backoff with jitter, queue-based processing, and 429 response handling.
| API | Endpoint | Limit | Scope |
|---|---|---|---|
| Track API | identify, track, trackAnonymous | ~100 req/sec | Per workspace |
| Track API | Batch operations | ~100 req/sec | Per workspace |
| App API | Transactional email/push | ~100 req/sec | Per workspace |
| App API | Broadcasts, queries | ~10 req/sec | Per workspace |
These are approximate. Customer.io uses sliding window rate limiting. When exceeded, you get a 429 Too Many Requests response.
// lib/rate-limiter.ts
export class TokenBucket {
private tokens: number;
private lastRefill: number;
constructor(
private readonly maxTokens: number = 80, // Stay under 100/sec limit
private readonly refillRate: number = 80 // Tokens per second
) {
this.tokens = maxTokens;
this.lastRefill = Date.now();
}
private refill(): void {
const now = Date.now();
const elapsed = (now - this.lastRefill) / 1000;
this.tokens = Math.min(this.maxTokens, this.tokens + elapsed * this.refillRate);
this.lastRefill = now;
}
async acquire(): Promise<void> {
this.refill();
if (this.tokens >= 1) {
this.tokens -= 1;
return;
}
// Wait until a token is available
const waitMs = ((1 - this.tokens) / this.refillRate) * 1000;
await new Promise((r) => setTimeout(r, Math.ceil(waitMs)));
this.tokens = 0;
this.lastRefill = Date.now();
}
}// lib/backoff.ts
interface BackoffOptions {
maxRetries: number;
baseDelayMs: number;
maxDelayMs: number;
jitter: number; // 0 to 1
}
const DEFAULTS: BackoffOptions = {
maxRetries: 4,
baseDelayMs: 1000,
maxDelayMs: 60000,
jitter: 0.25,
};
export async function withBackoff<T>(
fn: () => Promise<T>,
opts: Partial<BackoffOptions> = {}
): Promise<T> {
const { maxRetries, baseDelayMs, maxDelayMs, jitter } = { ...DEFAULTS, ...opts };
let lastErr: Error | undefined;
for (let attempt = 0; attempt <= maxRetries; attempt++) {
try {
return await fn();
} catch (err: any) {
lastErr = err;
const status = err.statusCode ?? err.status;
// Don't retry 4xx errors (except 429)
if (status >= 400 && status < 500 && status !== 429) throw err;
if (attempt === maxRetries) break;
// Check Retry-After header (429 responses)
const retryAfter = err.headers?.["retry-after"];
let delay: number;
if (retryAfter) {
delay = parseInt(retryAfter) * 1000;
} else {
delay = Math.min(baseDelayMs * Math.pow(2, attempt), maxDelayMs);
}
// Add jitter to prevent thundering herd
delay += delay * jitter * Math.random();
console.warn(`CIO retry ${attempt + 1}/${maxRetries} in ${Math.round(delay)}ms`);
await new Promise((r) => setTimeout(r, delay));
}
}
throw lastErr;
}// lib/customerio-rate-limited.ts
import { TrackClient, RegionUS } from "customerio-node";
import { TokenBucket } from "./rate-limiter";
import { withBackoff } from "./backoff";
export class RateLimitedCioClient {
private client: TrackClient;
private limiter: TokenBucket;
constructor(siteId: string, apiKey: string, ratePerSec: number = 80) {
this.client = new TrackClient(siteId, apiKey, { region: RegionUS });
this.limiter = new TokenBucket(ratePerSec, ratePerSec);
}
async identify(userId: string, attrs: Record<string, any>): Promise<void> {
await this.limiter.acquire();
return withBackoff(() => this.client.identify(userId, attrs));
}
async track(userId: string, event: { name: string; data?: any }): Promise<void> {
await this.limiter.acquire();
return withBackoff(() => this.client.track(userId, event));
}
async trackAnonymous(event: {
anonymous_id: string;
name: string;
data?: any;
}): Promise<void> {
await this.limiter.acquire();
return withBackoff(() => this.client.trackAnonymous(event));
}
async suppress(userId: string): Promise<void> {
await this.limiter.acquire();
return withBackoff(() => this.client.suppress(userId));
}
async destroy(userId: string): Promise<void> {
await this.limiter.acquire();
return withBackoff(() => this.client.destroy(userId));
}
}For sustained high volume, use p-queue for cleaner concurrency control:
// lib/customerio-queued.ts
import PQueue from "p-queue";
import { TrackClient, RegionUS } from "customerio-node";
const cio = new TrackClient(
process.env.CUSTOMERIO_SITE_ID!,
process.env.CUSTOMERIO_TRACK_API_KEY!,
{ region: RegionUS }
);
// Process at most 80 requests per second with max 10 concurrent
const queue = new PQueue({
concurrency: 10,
interval: 1000,
intervalCap: 80,
});
// Queue operations instead of calling directly
export function queueIdentify(userId: string, attrs: Record<string, any>) {
return queue.add(() => cio.identify(userId, attrs));
}
export function queueTrack(userId: string, name: string, data?: any) {
return queue.add(() => cio.track(userId, { name, data }));
}
// Monitor queue health
setInterval(() => {
console.log(
`CIO queue: pending=${queue.pending} size=${queue.size}`
);
}, 10000);Install: npm install p-queue
For large data imports (>10K users), avoid hitting rate limits with controlled batching:
// scripts/bulk-import.ts
import { RateLimitedCioClient } from "../lib/customerio-rate-limited";
async function bulkImport(users: { id: string; attrs: Record<string, any> }[]) {
const client = new RateLimitedCioClient(
process.env.CUSTOMERIO_SITE_ID!,
process.env.CUSTOMERIO_TRACK_API_KEY!,
50 // Conservative rate — 50/sec for imports
);
let processed = 0;
let errors = 0;
for (const user of users) {
try {
await client.identify(user.id, user.attrs);
processed++;
} catch (err: any) {
errors++;
console.error(`Failed user ${user.id}: ${err.message}`);
}
if (processed % 1000 === 0) {
console.log(`Progress: ${processed}/${users.length} (${errors} errors)`);
}
}
console.log(`Done: ${processed} processed, ${errors} errors`);
}| Scenario | Strategy |
|---|---|
429 received | Respect Retry-After header, fall back to exponential backoff |
| Burst traffic spike | Token bucket absorbs burst, queue holds overflow |
| Sustained high volume | Use p-queue with interval limiting |
| Bulk import | Use conservative rate (50/sec) with progress logging |
| Downstream timeout | Don't count as rate limit — retry normally |
After implementing rate limits, proceed to customerio-security-basics for security best practices.
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