Webhooks vs Polling: Why You're Wasting 99% of Your API Calls

Two patterns dominate how systems exchange data over HTTP: push (webhooks) and pull (polling). One sends data when something happens. The other asks “did anything happen?” on a loop. Both have a place, but choosing the wrong one costs you latency, bandwidth, or reliability. For a broader comparison including traditional request-response APIs, see webhooks vs APIs.

Before diving in: polling is not always wrong. If the API you integrate with has no webhook support, if you need full state snapshots, or if you just need a periodic health check, polling is the right tool. This guide will help you recognize which pattern fits your situation, and how to combine them when one is not enough.

This guide breaks down both patterns with code, real numbers, and practical guidance for when to use each.

How polling works

Polling is the pull model. Your application repeatedly sends HTTP requests to an API at fixed intervals, checking whether anything has changed since the last check.

// Poll an API every 30 seconds for new orders
async function pollForOrders(lastCheckedAt) {
  const interval = 30_000; // 30 seconds

  while (true) {
    try {
      const response = await fetch(
        `https://api.example.com/orders?since=${lastCheckedAt}`
      );
      const orders = await response.json();

      if (orders.length > 0) {
        for (const order of orders) {
          await processOrder(order);
        }
        lastCheckedAt = new Date().toISOString();
      }
    } catch (error) {
      console.error('Poll failed:', error.message);
    }

    await new Promise(resolve => setTimeout(resolve, interval));
  }
}

The pattern is straightforward: request, check, wait, repeat. Every iteration makes an HTTP call regardless of whether new data exists.

The polling lifecycle

1. Client sends GET request to the API
2. Server queries its data store and returns results (or an empty response)
3. Client processes any new data
4. Client waits for the interval to elapse
5. Go to step 1

How webhooks work

A webhook is the push model. Instead of asking for updates, you register a URL with the data source. When an event occurs, the source sends an HTTP POST to your URL with the event data — an HTTP callback.

// Express.js handler receiving a webhook POST
import express from 'express';
import crypto from 'crypto';

const app = express();
app.use('/webhooks', express.raw({ type: 'application/json' }));

app.post('/webhooks/orders', (req, res) => {
  // Verify the signature before processing
  const signature = req.headers['x-webhook-signature'];
  const expected = crypto
    .createHmac('sha256', process.env.WEBHOOK_SECRET)
    .update(req.body)
    .digest('hex');

  if (signature !== expected) {
    return res.status(401).send('Invalid signature');
  }

  const event = JSON.parse(req.body);

  // Acknowledge immediately, process asynchronously
  res.status(200).send('OK');

  // Queue the work instead of processing inline
  queue.add('process-order', { order: event.data });
});

No looping, no wasted calls. Data arrives when it exists.

The webhook lifecycle

1. You register an endpoint URL with the event source
2. An event occurs on the source system
3. The source serializes the event, signs it, and POSTs it to your URL
4. Your server verifies the signature, responds with 200, and processes the data
5. If delivery fails, the source retries with exponential backoff

Side-by-side comparison

The 99.3% wasted requests problem

Polling’s core inefficiency: most requests return nothing new. Here are real numbers.

Say you poll an API every 30 seconds to check for new orders. The store receives about 20 orders per day. Let’s do the math:

• Polls per day: 86,400 seconds / 30 seconds = 2,880 requests
• Requests that find new data: ~20
• Requests that return nothing: 2,880 - 20 = 2,860
• Waste rate: 2,860 / 2,880 = 99.3%

Even a busier system doesn’t escape this. An API with 200 events per day still wastes over 93% of its polling requests at a 30-second interval. At a 5-second interval, you make 17,280 requests per day — 98.8% of which return empty responses.

This matters at scale. If you have 1,000 customers each polling your API every 30 seconds, that is 2.88 million requests per day. The vast majority return {"data": []}. You are paying for compute, bandwidth, and rate limit headroom to answer “no” 2.8 million times.

Webhooks flip this entirely. With 200 events per day, you handle exactly 200 HTTP requests — each one carrying data you actually need.

When polling is actually better

Despite its inefficiency, polling wins in specific scenarios.

The source has no webhook support

Many APIs simply do not offer webhooks. If the only way to get data out is a REST endpoint, polling is your only option. No point in wishing for webhooks that do not exist.

You need to control the request rate

Polling puts you in charge of timing. You decide when and how often to ask. This is useful when:

• You need to batch-process updates (e.g., sync every 5 minutes)
• Your downstream system cannot handle arbitrary traffic bursts
• You want to align data fetching with your processing schedule

Simple read-only status checks

Health checks and status monitoring are natural fits for polling. You want to know “is this service up right now?” at a regular interval — not “notify me the moment it goes down.” The regularity is the feature.

# Simple health check poll — runs every 60 seconds via cron
curl -sf https://api.example.com/health || echo "Service down" | notify

Events happen more often than you need to process them

If the source generates 100 events per second and you only need a summary every minute, polling once per minute is more efficient than receiving and discarding 5,999 webhook deliveries. Polling lets you aggregate on your schedule.

You need historical data on each check

Some polling patterns fetch the full current state, not just changes. If you need a complete snapshot (e.g., current inventory levels, account balance), a periodic GET is simpler than maintaining state from a stream of incremental webhook events.

When webhooks win

Webhooks are the better default for most integration scenarios.

Real-time requirements

If your users expect immediate feedback — payment confirmations, chat messages, deployment notifications — polling’s latency is unacceptable. Even a 5-second poll interval means up to 5 seconds of delay. Webhooks deliver in milliseconds.

High event volume with many consumers

Consider a source system that publishes events to 50 different consumers. With polling, that is 50 clients each hitting the API every 30 seconds: 144,000 requests per day. With webhooks, the source sends one POST per event per consumer — if there are 500 events per day, that is 25,000 targeted requests, each carrying useful data.

Event-driven architectures

If your system is built on event-driven architecture — where services react to events rather than polling for state changes — webhooks are the natural fit. They map directly to the “something happened, react to it” model.

Reducing API quota consumption

Most APIs enforce rate limits. Every poll request counts against your quota. Webhooks use zero quota on the source API because the source initiates the request, not you.

The hybrid approach: webhooks plus polling

The most reliable production systems do not choose one pattern exclusively. They use both.

Webhooks as the primary channel. Events arrive in real-time for the common case. This handles 99%+ of events with low latency.

Polling as a reconciliation fallback. A periodic job polls the API to find events that may have been missed — webhook timeouts, network blips, downtime on your end, or bugs in the sender’s delivery system.

# Reconciliation poller — runs every 15 minutes
def reconcile_orders():
    """Catch any orders missed by webhooks."""
    last_reconciled = get_last_reconciliation_timestamp()

    orders = api.get_orders(since=last_reconciled)
    for order in orders:
        if not already_processed(order['id']):
            process_order(order)

    update_reconciliation_timestamp()

This pattern gives you the speed of webhooks with the reliability guarantee of polling. Stripe, Shopify, and most payment processors recommend this exact approach in their integration guides.

When the hybrid approach matters most

• Financial data — you cannot afford to miss a payment event
• Inventory sync — a missed webhook means overselling a product
• User provisioning — a missed “user created” event leaves someone locked out
• Any system where data consistency is non-negotiable

Reliability concerns

Both patterns have failure modes. Understanding them helps you build defenses.

Polling failure modes

Webhook failure modes

Making webhooks reliable

If you choose webhooks (and you probably should for most use cases), these practices prevent the common failure modes.

Verify every request

Never trust a webhook without checking its signature. Every legitimate sender signs requests with a shared secret. Verify before processing — this stops forged events and replay attacks. See how to secure webhook endpoints for a full implementation guide.

Process asynchronously

Return 200 immediately and queue the actual work. Webhook senders enforce timeouts — typically 5 to 30 seconds. If your handler takes longer, the sender marks it as failed and retries, creating duplicate deliveries. Acknowledge fast, process later.

Handle retries with idempotency

Webhook delivery is at-least-once, not exactly-once. You will receive duplicates. Store processed event IDs and check before acting. See webhook retry best practices for implementation details.

Test your endpoint

Before going live, verify your handler with a webhook tester or by testing webhooks locally. Confirm it accepts valid payloads, rejects bad signatures, and handles duplicates gracefully.

How to migrate from polling to webhooks

If you are currently polling and have decided webhooks are the better fit, do not rip out polling overnight. A phased migration avoids data loss.

1. Run both in parallel

Register your webhook endpoint with the source while keeping your existing polling loop running. Both channels now feed into the same processing pipeline. Use idempotency (deduplicate by event ID) so duplicate events from both channels are harmless.

2. Verify webhook delivery matches polling results

Compare what arrives via webhooks against what polling finds. Log any events that polling catches but webhooks miss. This tells you how reliable the source’s webhook delivery actually is before you depend on it. Run this comparison for at least a few days — long enough to see edge cases like maintenance windows and rate limit spikes.

3. Demote polling to reconciliation

Once you trust webhook delivery, reduce your polling frequency from “primary data source” (every 30 seconds) to “reconciliation fallback” (every 10-15 minutes). The poller now only catches the rare missed webhook instead of doing all the heavy lifting.

4. Sunset polling (optional)

If the source’s webhook delivery proves completely reliable over weeks, you can remove the reconciliation poller entirely. Most teams keep it — the cost of a lightweight poll every 15 minutes is negligible, and it provides insurance against future delivery issues.

Use Recuro for scheduled HTTP requests

Whether you need a polling loop that hits an API every 30 seconds or a reconciliation job that runs every 15 minutes, Recuro handles the scheduling infrastructure so you do not have to build and maintain cron jobs yourself:

• Cron-based HTTP requests — schedule GET, POST, or any HTTP method on a cron expression with full execution history
• Custom headers and payloads — configure each request with the exact headers and body your API expects
• Automatic retries — exponential backoff with configurable retry counts for failed requests
• Failure alerts — get notified when requests fail, with full response logs
• Execution history — every request logged with status code, response body, and timing

Stop building and babysitting polling loops. Schedule your HTTP requests and let Recuro handle execution and retries.

Related resources

• Webhook scheduling: send HTTP requests on a schedule — cron-based HTTP request delivery
• Webhook retry best practices — exponential backoff, jitter, and dead letter queues
• How to secure your webhook endpoints — signature verification and replay protection
• How to test webhooks locally — 7 tools and methods for development
• What is a webhook? — the fundamentals of push-based HTTP callbacks
• What is polling? — the pull model explained
• Event-driven architecture — designing systems around events
• Idempotency — why processing an event twice must be safe
• Rate limiting — protecting APIs from excessive requests