Skills Development Robust API Rate Limit Handling

Robust API Rate Limit Handling

v20260423
maintainx-rate-limits
A comprehensive client library pattern for interacting with rate-limited APIs. This solution implements exponential backoff, robust retry logic (handling 429/5xx errors), concurrent request queuing, and cursor-based pagination. It ensures high throughput and reliable data fetching without exceeding API limits.
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Overview

MaintainX Rate Limits

Overview

Handle MaintainX API rate limits gracefully with exponential backoff, cursor-based pagination, and request queuing to maximize throughput without triggering 429 errors.

Prerequisites

  • MaintainX API access configured
  • Node.js 18+ with axios
  • Understanding of async/await patterns

Instructions

Step 1: Rate-Limited Client Wrapper

// src/rate-limited-client.ts
import axios, { AxiosInstance, AxiosError } from 'axios';

export class RateLimitedClient {
  private http: AxiosInstance;
  private requestQueue: Array<() => void> = [];
  private activeRequests = 0;
  private maxConcurrent = 5;
  private minDelayMs = 100;  // 10 requests/second max

  constructor(apiKey?: string) {
    const key = apiKey || process.env.MAINTAINX_API_KEY;
    if (!key) throw new Error('MAINTAINX_API_KEY required');

    this.http = axios.create({
      baseURL: 'https://api.getmaintainx.com/v1',
      headers: {
        Authorization: `Bearer ${key}`,
        'Content-Type': 'application/json',
      },
      timeout: 30_000,
    });
  }

  private async throttle(): Promise<void> {
    if (this.activeRequests >= this.maxConcurrent) {
      await new Promise<void>((resolve) => this.requestQueue.push(resolve));
    }
    this.activeRequests++;
    await new Promise((r) => setTimeout(r, this.minDelayMs));
  }

  private release() {
    this.activeRequests--;
    const next = this.requestQueue.shift();
    if (next) next();
  }

  async request<T>(method: string, url: string, data?: any, params?: any): Promise<T> {
    await this.throttle();
    try {
      const response = await this.retryWithBackoff(
        () => this.http.request<T>({ method, url, data, params }),
      );
      return response.data;
    } finally {
      this.release();
    }
  }

  private async retryWithBackoff<T>(
    fn: () => Promise<T>,
    maxRetries = 3,
    baseDelay = 1000, // 1 second initial backoff delay
  ): Promise<T> {
    for (let attempt = 0; attempt <= maxRetries; attempt++) {
      try {
        return await fn();
      } catch (err) {
        const axiosErr = err as AxiosError;
        const status = axiosErr.response?.status;

        if (status !== 429 && !(status && status >= 500) || attempt === maxRetries) {
          throw err;
        }

        // Honor Retry-After header
        const retryAfter = axiosErr.response?.headers?.['retry-after'];
        const delayMs = retryAfter
          ? parseInt(retryAfter) * 1000
          : baseDelay * Math.pow(2, attempt) + Math.random() * 500;

        console.warn(
          `Rate limited (HTTP ${status}). Retry ${attempt + 1}/${maxRetries} in ${Math.round(delayMs)}ms`,
        );
        await new Promise((r) => setTimeout(r, delayMs));
      }
    }
    throw new Error('Unreachable');
  }
}

Step 2: Cursor-Based Pagination

MaintainX returns a cursor field in list responses. Pass it as a query parameter to fetch the next page.

async function paginateAll<T>(
  client: RateLimitedClient,
  endpoint: string,
  resultKey: string,
  params?: Record<string, any>,
): Promise<T[]> {
  const allItems: T[] = [];
  let cursor: string | undefined;

  do {
    const response: any = await client.request('GET', endpoint, undefined, {
      ...params,
      limit: 100,
      cursor,
    });
    const items = response[resultKey] as T[];
    allItems.push(...items);
    cursor = response.cursor ?? undefined;

    // Log progress for long-running operations
    if (allItems.length % 500 === 0) {
      console.log(`  Fetched ${allItems.length} items so far...`);
    }
  } while (cursor);

  return allItems;
}

// Usage
const allWorkOrders = await paginateAll(client, '/workorders', 'workOrders', {
  status: 'OPEN',
});
console.log(`Total: ${allWorkOrders.length} open work orders`);

Step 3: Batch Operations with p-queue

import PQueue from 'p-queue';

// 5 concurrent requests, max 10 per second
const queue = new PQueue({
  concurrency: 5,
  interval: 1000, // 1 second window for rate cap
  intervalCap: 10,
});

async function batchUpdate(
  client: RateLimitedClient,
  updates: Array<{ id: number; data: any }>,
) {
  const results = await Promise.allSettled(
    updates.map((update) =>
      queue.add(() =>
        client.request('PATCH', `/workorders/${update.id}`, update.data),
      ),
    ),
  );

  const succeeded = results.filter((r) => r.status === 'fulfilled').length;
  const failed = results.filter((r) => r.status === 'rejected').length;
  console.log(`Batch update: ${succeeded} succeeded, ${failed} failed`);
  return results;
}

// Close 100 completed work orders
const completedOrders = await paginateAll(
  client, '/workorders', 'workOrders', { status: 'COMPLETED' },
);

await batchUpdate(
  client,
  completedOrders.map((wo: any) => ({ id: wo.id, data: { status: 'CLOSED' } })),
);

Step 4: Rate Limit Monitoring

// src/rate-monitor.ts
class RateMonitor {
  private requests: number[] = [];
  private windowMs = 60_000; // 1 minute window

  record() {
    this.requests.push(Date.now());
    this.cleanup();
  }

  cleanup() {
    const cutoff = Date.now() - this.windowMs;
    this.requests = this.requests.filter((t) => t > cutoff);
  }

  getRate(): number {
    this.cleanup();
    return this.requests.length;
  }

  report() {
    const rate = this.getRate();
    const status = rate > 50 ? 'WARNING' : 'OK';
    console.log(`[RateMonitor] ${rate} req/min - ${status}`);
    return { rate, status };
  }
}

Output

  • Rate-limited client wrapper with built-in throttling and retry
  • Cursor-based pagination utility collecting all results
  • Batch operations with controlled concurrency via p-queue
  • Rate monitoring to track and alert on API usage

Error Handling

Scenario Strategy
429 Too Many Requests Exponential backoff with jitter, honor Retry-After header
Retry-After header present Wait the specified number of seconds before retrying
Burst of requests Queue with p-queue (concurrency: 5, intervalCap: 10/sec)
Large data sets (1000+ items) Paginate with limit: 100, delay between pages

Resources

Next Steps

For security configuration, see maintainx-security-basics.

Examples

Adaptive rate limiting based on response headers:

// Adjust concurrency dynamically based on remaining quota
function adaptRate(headers: Record<string, string>, queue: PQueue) {
  const remaining = parseInt(headers['x-ratelimit-remaining'] || '100');
  if (remaining < 10) {
    queue.concurrency = 1;
    console.warn('Approaching rate limit, reducing concurrency to 1');
  } else if (remaining < 50) {
    queue.concurrency = 3;
  } else {
    queue.concurrency = 5;
  }
}
Info
Category Development
Name maintainx-rate-limits
Version v20260423
Size 6.88KB
Updated At 2026-04-26
Language