Webhook vs Polling: When Each Makes Sense

Karam

7 hours ago

You’re building a flight tracking app. A user is heading to the airport, and suddenly their gate changes.

The question is: how fast does your app know?

Do you keep asking the API every 30 seconds, “Anything new?” Or do you set things up, so your system gets notified the moment something changes?

That’s the webhook vs polling decision in a nutshell.

And with flight data, this decision actually matters.

Flight statuses aren’t predictable. Delays, cancellations, and gate changes can happen at any time, often in bursts. If your app checks too infrequently, your users see stale information. If it checks too often, you burn through your API quota and waste resources pulling the same unchanged data over and over again.

Now scale that up.

If you’re tracking hundreds of flights using the Aviationstack API, polling every minute could mean hundreds of thousands of requests per day, most of which return identical results. On the flip side, building a more real-time, event-driven system can reduce waste, but it introduces its own complexity.

So, this isn’t just a technical preference. It’s an architectural decision that affects:

How fresh is your data
How much do you spend on API usage
How complex your system becomes

In this post, we’ll break down both approaches using real examples with Aviationstack. You’ll see the trade-offs clearly, look at working Node.js code for each approach, and leave with a straightforward way to decide which one actually makes sense for your use case.

Key Takeaways

Polling is simple but inefficient at scale
It’s easy to set up and reliable, but you’ll make a lot of unnecessary API calls, especially when flight data hasn’t changed.
Webhooks (or event-driven systems) reduce waste but add complexity
You only react to changes, which is more efficient, but you need extra infrastructure like servers, queues, and retry handling.
Latency is the biggest practical difference
Polling introduces delays based on your interval (for example, up to 60 seconds), while event-driven systems can surface changes almost immediately.
Aviationstack is REST-based, not webhook-native
You can’t subscribe to real push events, but you can build a webhook-style system on top of polling to get similar benefits.
API quota usage can explode with naive polling
Tracking hundreds of flights with frequent polling can quickly burn through your request limits, often returning unchanged data.
There’s a clear decision framework
- Use polling for small-scale apps, prototypes, or when simplicity matters
- Use event-driven architecture for real-time updates and larger systems
- Use a hybrid approach when you want the best of both
You can start immediately
With a simple polling script and an Aviationstack API key, you can begin tracking live flight data and evolve your architecture as your needs grow

Polling Explained

Let’s start with the simplest approach.

Polling is exactly what it sounds like. Your application asks the API for updates on a fixed schedule. Every 30 seconds, every minute, every 5 minutes, whatever interval you choose, you send a request and check if anything has changed.

Under the hood, this is just a standard request-response cycle. Your app sends a request to the Aviationstack /flights endpoint, gets the latest data back, processes it, and then waits until the next interval to do it again. If you need a refresher on how this works at a basic level, it follows the same pattern as any REST API call.

A typical flow looks like this:

Set a polling interval (for example, every 60 seconds)
Call http://api.aviationstack.com/v1/flights with your parameters
Store or cache the response
Compare it to the previous result
Detect any changes (delay, gate update, cancellation)
Repeat

That’s it. No servers to expose, no event systems, no special infrastructure.

This simplicity is why polling is often the default choice, especially when you’re just getting started. You can throw together a script with setInterval, hit the Aviationstack API, and immediately start seeing real flight data come in.

But the trade-off shows up quickly.

Let’s say you poll every 60 seconds. That means your app could be up to a minute behind any real-world change. If a gate changes right after your last request, your users won’t see it until the next cycle.

And then there’s efficiency.

Most of the time, nothing changes. You’re requesting just to get the same response back. When you’re tracking a handful of flights, that’s not a big deal. When you’re tracking hundreds, it adds up fast, both in terms of API quota and unnecessary processing.

That’s the core idea behind polling:

It’s simple
It’s predictable
It works everywhere

But it trades efficiency and real-time accuracy for that simplicity, which is where the webhook or event-driven approach starts to look more appealing.

Webhooks

Now let’s look at the alternative: webhooks.

Instead of repeatedly asking “anything new?”, webhooks flip the model. You give the API a URL, and whenever something changes, it sends you the data automatically.

No polling. No wasted requests. Just events as they happen.

In a true webhook setup, the flow looks like this:

You register a webhook endpoint (for example, /flight-updates)
The API monitors for changes (like delays or gate updates)
When something changes, it sends an HTTP POST request to your endpoint
Your system processes the event immediately

This is what people mean by “event-driven architecture.” Your system reacts to changes instead of constantly checking for them.

For something like flight data, this sounds ideal. A delay happens → your app gets notified instantly → the user sees the update right away.

But here’s the important reality check:

Aviationstack does not natively support webhooks.

It’s a REST API, which means you can only pull data, not subscribe to push-based updates.

So, what do you do?

You build a webhook-style system on top of polling.

Instead of sending updates directly to your app, you:

Run a polling worker that continuously checks the Aviationstack API
Detect changes between responses (for example, flight status goes from “scheduled” to “delayed”)
Emit an internal event when something changes
Send that event to other parts of your system (or even an HTTP endpoint that behaves like a webhook receiver)

In other words, polling becomes your data source, and you layer an event-driven system on top of it.

This hybrid approach gives you many of the benefits of webhooks:

You only act when something actually changes
You can trigger real-time notifications internally
You avoid spamming downstream systems with redundant data

But it comes with added responsibility.

Unlike simple polling, you now need to think about:

Running a server (for receiving or dispatching events)
Handling retries if something fails
Making your event processing idempotent (so duplicates don’t break things)
Dealing with ordering issues if multiple updates happen quickly

And there’s one more important edge case to consider:

What happens if your system goes down?

If your polling worker or event processor is offline for 10 minutes during a wave of flight cancellations, you don’t just “miss” one request; you potentially miss a whole sequence of state changes. When you come back online, you need to reconcile the current state with what you missed.

So, while webhooks (or webhook-style systems) can give you faster, more efficient updates, they shift complexity from the API layer to your own infrastructure.

That’s the trade-off:

Polling keeps things simple but noisy
Event-driven systems are efficient but require real engineering effort

Next, we’ll break these differences down side-by-side so you can see exactly how they compare in practice.

Polling vs Webhooks: The Core Trade-Offs

At a high level, polling and event-driven systems solve the same problem. They just make very different trade-offs to get there.

Instead of keeping this abstract, let’s walk through the differences in the context of Aviationstack and real flight data.

Latency

This is the most immediate and noticeable difference.

With polling, your data is only as fresh as your interval.

Poll every 60 seconds → updates can be up to 60 seconds late
Poll every 10 seconds → fresher data, but 6x more API calls

So, if a flight gets delayed right after your last request, your app won’t know until the next cycle.

With an event-driven (webhook-style) system, you detect changes as soon as your polling worker sees them and immediately trigger an update internally. In practice, this means near real-time updates, limited only by how frequently your worker runs and how quickly you process events.

In a flight app:
A gate change might show up instantly in an event-driven system, but could take up to a minute (or more) with polling.

Reliability & Failure Modes

Polling is straightforward and forgiving.

If a request fails:

You just try again on the next interval
No special recovery logic needed
Worst case: you miss one cycle

Event-driven systems are more fragile if not designed carefully.

You now have multiple moving parts:

A polling worker
An event dispatcher
Possibly a webhook receiver or queue

If your system goes down for 10 minutes during a wave of cancellations:

You don’t just miss one request
You potentially miss multiple state transitions

When you come back online, you need to reconcile the state:

What changed while you were down?
What events did you miss?

This often means:

Re-fetching current data
Rebuilding the state from scratch
Designing idempotent handlers so reprocessing doesn’t break things

Infrastructure Cost

Polling looks cheap at first, but it adds up fast.

Let’s put numbers to it:

500 flights tracked
Polling every 60 seconds
That’s 720,000 requests per day (Assuming 1 request per flight)

And most of those responses? No changes.

You’re paying (in quota and compute) just to confirm that nothing happened.

With an event-driven approach:

You still poll Aviationstack as your source of truth
But you only trigger downstream processing when something actually changes

This reduces:

Internal processing load
Unnecessary notifications
Wasted API usage (if you optimize polling frequency)

However, you now need to run:

A server (or multiple services)
Possibly a queue system

So, you’re trading API cost for infrastructure cost.

Complexity

This is where the gap really widens.

Polling is about as simple as it gets:

A loop or setInterval
One API call
A comparison step

You can build it in minutes.

Event-driven systems require real design decisions:

How do you detect changes reliably?
How do you store the previous state?
How do you handle duplicate events?
What happens if processing fails midway?

You may end up introducing:

Message queues
Retry logic
Logging and monitoring
Idempotent event handlers

It’s not overkill; it’s necessary once you scale, but it’s definitely more work.

API Quota Efficiency

This is a big one with Aviationstack.

Polling burns through requests quickly, especially if:

You’re tracking many flights
Your interval is short

Most of those calls return identical data.

A smarter, event-driven setup helps you:

Reduce unnecessary processing
Optimize when and how often you poll
Focus only on meaningful changes

Even though you’re still polling under the hood, you’re using the data more efficiently.

The Big Picture

If you zoom out, the trade-off becomes clear:

Polling: Simple, reliable, but potentially slow and wasteful
Event-driven (webhook-style): Fast and efficient, but requires more infrastructure and careful design

Neither is “better” in all cases. It depends on how many flights you’re tracking, how real-time your app needs to be, and how much complexity you’re willing to manage.

Next, let’s make this concrete with actual Node.js code, starting with a simple polling implementation you can run right away.

Node.js Example #1: Simple Polling Script

Let’s make this real.

Here’s a straightforward Node.js script that polls the Aviationstack /flights endpoint, stores previous results, and logs when something changes.

This is the baseline approach. No extra infrastructure, no event system, just a loop and some comparison logic.

What This Script Does

Calls the Aviationstack API every 60 seconds
Tracks a specific flight (or set of flights)
Stores the last known status in memory
Logs when the flight status changes (for example, scheduled → delayed)

Example Response Structure (Aviationstack)

Aviationstack responses look something like this (simplified):

				
					"data": [
  {
    "flight_date": "2026-04-10",
    "flight_status": "scheduled",
    "departure": {
      "airport": "string",
      "scheduled": "2026-04-10T14:15:22Z"
    },
    "arrival": {
      "airport": "string",
      "scheduled": "2026-04-10T14:15:22Z"
    },
    "airline": {
      "airline_name": "string"
    },
    "flight": {
      "number": "string"
    },
    "aircraft": {
      "registration": "string"
    },
    "live": {
      "updated": "2026-04-10T14:15:22Z",
    }
  }
]

We’ll use the flight_status field to detect changes.

Polling Script

				
					const axios = require("axios");


const API_KEY = "YOUR_API_KEY"; // Replace with your actual API key
const BASE_URL = "http://api.aviationstack.com/v1/flights";


// In-memory cache of last known statuses
const flightCache = new Map();


// Change this to filter specific flights if needed
const params = {
  access_key: API_KEY,
  flight_iata: "UA2402" // example flight
};


async function pollFlights() {
  try {
    const response = await axios.get(BASE_URL, { params });
    const flights = response.data.data;


    flights.forEach((flight) => {
      const flightId = flight.flight.iata;
      const currentStatus = flight.flight_status;
      const currentTime = new Date().toLocaleTimeString();


      const previousStatus = flightCache.get(flightId);


      if (!previousStatus) {
        // First time seeing this flight
        flightCache.set(flightId, currentStatus);
        console.log(`[INIT AT ${currentTime}] ${flightId} status: ${currentStatus}`);
        return;
      }


      if (previousStatus !== currentStatus) {
        console.log(
          `[UPDATE AT ${currentTime}] ${flightId} changed: ${previousStatus} → ${currentStatus}`
        );


        // Update cache
        flightCache.set(flightId, currentStatus);
      }
    });
  } catch (error) {
    console.error("Error fetching flight data:", error.message);
  }
}


// Run every 60 seconds
setInterval(pollFlights, 60 * 1000);


// Run immediately on start
pollFlights();


console.log("Flight status polling started...");

Why This Works Well

Simple to understand: One function, one API call, one comparison
Easy to debug: If something breaks, there are very few moving parts
Good for small workloads: Tracking a handful of flights is totally manageable

Where It Starts to Break Down

This approach works great, until it doesn’t.

You’re making requests even when nothing changes
Your data can be up to 60 seconds stale
Scaling to hundreds of flights quickly increases API usage
Everything is tightly coupled to the polling loop

This is where developers start looking for something more efficient and responsive.

In the next section, we’ll take this exact idea and evolve it into a webhook-style, event-driven system, still using Aviationstack as the data source.

Node.js Example #2: Webhook-Style Architecture

Now, let’s take the same idea and make it more scalable.

Since Aviationstack doesn’t support real webhooks, we’ll simulate them by splitting responsibilities:

A polling worker fetches data from Aviationstack
A change detector identifies updates
An event dispatcher emits events
A server (Express) receives those events like a webhook

This gives you a clean, event-driven flow, even though polling is still happening under the hood.

What This Architecture Does

Polls the Aviationstack API at a controlled interval
Detects changes in flight status
Emits an internal event when something changes
Sends that event to a local endpoint (simulating a webhook)
Decouples data fetching from event handling

Step 1: Set Up the Express “Webhook Receiver”

				
					const express = require("express");


const app = express();
app.use(express.json());


// Simulated webhook endpoint
app.post("/flight-updates", (req, res) => {
  const event = req.body;


  console.log("[WEBHOOK RECEIVED]");
  console.log(
    `Flight ${event.flight_iata} changed: ${event.old_status} → ${event.new_status}`
  );


  // Here you could:
  // - Send notifications
  // - Update a database
  // - Trigger downstream services


  res.sendStatus(200);
});


app.listen(3000, () => {
  console.log("Webhook receiver running on http://localhost:3000");
});

Step 2: Polling Worker + Event Dispatcher

				
					const axios = require("axios");


const API_KEY = "YOUR_API_KEY"; // Replace with your actual API key
const BASE_URL = "http://api.aviationstack.com/v1/flights";


// In-memory cache of last known statuses
const flightCache = new Map();


// Change this to filter specific flights if needed
const params = {
  access_key: API_KEY,
  flight_iata: "UA2402" // example flight
};


async function dispatchEvent(event) {
  try {
    await axios.post("http://localhost:3000/flight-updates", event);
  } catch (error) {
    console.error("Failed to dispatch event:", error.message);
  }
}


async function pollFlights() {
  try {
    const response = await axios.get(BASE_URL, { params });
    const flights = response.data.data;


    flights.forEach(async (flight) => {
      const flightId = flight.flight.iata;
      const currentStatus = flight.flight_status;


      const previousStatus = flightCache.get(flightId);


      if (!previousStatus) {
        // First time seeing this flight
        flightCache.set(flightId, currentStatus);
        return;
      }


      if (previousStatus !== currentStatus) {
        const event = {
          flight_iata: flightId,
          old_status: previousStatus,
          new_status: currentStatus,
          timestamp: new Date().toLocaleTimeString()
        };


        console.log("[EVENT EMITTED]", event);


        // Send to webhook receiver
        await dispatchEvent(event);


        // Update cache
        flightCache.set(flightId, currentStatus);
      }
    });
  } catch (error) {
    console.error("Error polling flights:", error.message);
  }
}


// Run every 60 seconds
setInterval(pollFlights, 60 * 1000);


// Run immediately on start
pollFlights();
console.log("Flight status polling started...");

What Changed Compared to Simple Polling?

The key difference isn’t how we fetch data, it’s what we do after.

Instead of tightly coupling everything inside the polling loop, we now:

Emit events when something changes
Send those events to a separate service
Handle updates independently from data fetching

This separation is what makes the system scalable.

Why This Is More Powerful

Decoupling
Your polling logic doesn’t need to know what happens after a change. It just emits events.
Extensibility
You can plug in:
- Notifications
- Databases
- Analytics pipelines
Real-time behaviour (internally)
As soon as a change is detected, it’s pushed through your system immediately.

What You’d Add in Production

This is a simplified version. In a real system, you’d likely add:

A queue (e.g., RabbitMQ, Kafka, SQS) instead of direct HTTP calls
Retry logic for failed event deliveries
Idempotency checks to avoid duplicate processing
Persistent storage instead of an in-memory cache
Monitoring and logging

The Key Insight

Even without native webhooks, you can still build an event-driven system on top of a polling API like Aviationstack.

Polling becomes your data ingestion layer, and your event system becomes the real-time engine that powers everything else.

In the next section, we’ll put both approaches side by side in a clear comparison table so you can quickly see which one fits your use case best.

Polling vs Webhooks: Side-by-Side Comparison

At this point, you’ve seen both approaches in action. Let’s put them side by side so you can quickly compare how they behave in a real Aviationstack-based system.

Feature	Polling	Event-Driven (Webhook-Style on Top of Polling)
Latency	Depends on interval (e.g., up to 60s delay if polling every minute)	Near real-time after change detection (typically seconds)
Reliability	Very simple. If a request fails, retry the next interval	More complex. Must handle retries, missed events, and recovery after downtime
Failure Mode	Miss one cycle → recover automatically on next poll	Risk of missing multiple updates if the system is down → requires state reconciliation
Infrastructure	Minimal. Just a script or cron job	Requires a server (Express), event handling, and optionally a queue
Complexity	Low. Easy to build and maintain	Medium to high. Requires careful system design
API Usage	High. Many requests return unchanged data	More efficient. Still polls, but only triggers work on changes
Cost Profile	Higher API usage, lower infrastructure cost	Lower API waste, higher infrastructure overhead
Scalability	Limited. Becomes expensive with many flights	Scales better with proper architecture
Best Suited For	Small apps, prototypes, low-frequency updates	Real-time apps, notifications, and large-scale flight tracking

When Should You Use Each?

At this point, you’ve seen the trade-offs, the code, and how both approaches behave with real flight data.

So, let’s make this simple: here’s how to decide:

Use Polling When It’s Enough

Polling is the right choice when you don’t need to overcomplicate things.

Use it when:

You’re tracking a small number of flights (for example, under 20–50)
You’re building a prototype or MVP
You want minimal infrastructure
A delay of 30–60 seconds is acceptable
You just need periodic updates, not instant notifications

Example:
A personal dashboard that refreshes flight statuses every minute.

In this case, polling is not just “good enough,” it’s the smartest choice. It’s faster to build, easier to debug, and completely reliable for small workloads.

Use Event-Driven (Webhook-Style) When Scale or Speed Matters

Once your requirements grow, polling starts to show its limits.

Use an event-driven approach when:

You’re tracking hundreds of flights
You need near real-time updates
You’re building user-facing notifications (alerts, SMS, push)
API quota efficiency matters
You want to decouple your system (data ingestion vs processing)

Example:
A travel app that sends instant notifications when a gate changes or a flight is delayed.

Here, a 60-second delay is noticeable, and unnecessary API calls become expensive. An event-driven system gives you faster updates and better efficiency, even though it requires more setup.

Use a Hybrid Approach (Most Real-World Systems)

This is where most production systems end up.

You:

Use polling as your data source (because Aviationstack is REST-based)
Add an event layer on top (like the webhook-style system you built earlier)
Trigger updates only when something actually changes

This gives you:

The reliability of polling
The responsiveness of event-driven systems
Better control over API usage

Example:
A flight operations dashboard that:

Polls Aviationstack every 30–60 seconds
Emits events when statuses change
Updates multiple services (UI, alerts, analytics) in real time

A Simple Rule of Thumb

If you’re unsure, use this:

Start with polling
Move to event-driven when you feel the pain

That pain usually shows up as:

Too many API requests
Noticeable delays
Growing system complexity

When that happens, you don’t need to throw everything away. You can evolve your polling setup into an event-driven system, just like we did.

Real-World Use Cases: Where This Actually Matters

It’s easy to keep this discussion abstract, but the polling vs event-driven decision shows up very quickly once you start building real products with flight data.

Here are a few concrete examples using Aviationstack where the choice directly impacts user experience, cost, and system design.

Travel Apps (User Notifications)

Imagine you’re building a consumer travel app.

A user has a flight in a few hours, and suddenly:

The gate changes
The departure time is delayed
The flight gets cancelled

If you’re using polling every 60 seconds:

The user might see updates with a delay
Notifications feel slightly behind real-world events

If you’re using a webhook-style system:

Changes are detected and pushed through your system immediately
Users get near-real-time alerts

Why it matters:
In user-facing apps, even small delays can feel frustrating. Event-driven systems make the app feel fast and reliable.

Flight Tracking Dashboards

Now think about a dashboard that tracks multiple flights at once.

For example:

A logistics company is monitoring incoming shipments
An internal dashboard showing flight statuses across regions

With polling:

You’re making frequent API calls across many flights
Most responses don’t change
Costs scale quickly as you add more flights

With an event-driven approach:

You still poll Aviationstack
But you only trigger updates when something changes
The UI updates instantly without constant re-rendering

Why it matters:
At scale, efficiency becomes critical. Event-driven systems reduce noise and focus only on meaningful changes.

The Pattern You’ll Notice

Across all these use cases, the same pattern shows up:

Small-scale or internal tools → polling is often enough
User-facing, real-time, or large-scale systems → event-driven becomes valuable

And in most real-world applications, you don’t fully choose one or the other.

You start with polling, then layer in an event-driven system as your needs grow.

Next, let’s look at how to get started right away so you can test this yourself with real flight data.

Getting Started

If you want to make this concrete, here’s the fastest way to go from “just reading” to actually working with real flight data.

Get Your API Key

Head over to the Aviationstack website and sign up for a free account.

You’ll get an API key that lets you start making requests immediately.

If you want to learn more about available endpoints and parameters, check out the official documentation:
https://aviationstack.com/documentation

Run the Polling Script

Take the polling example from earlier and:

Paste it into a file (worker.js)
Add your API key
Run it with node worker.js

You should start seeing live flight data come through.

At first, you’ll likely see:

Initial flight status (for example, scheduled)
Occasional updates if the status changes

Expand the Query

To make things more interesting:

Remove the flight_iata filter to fetch multiple flights
Or track several flights at once
Or adjust the polling interval (try 30s vs 60s)

This helps you quickly see:

How often does data actually change
How many requests are you making

Add the Webhook-Style Layer

Once the polling script is running:

Spin up the Express server (server.js)
Connect it to your worker
Watch events get emitted when changes happen

Now you’ve moved from:

“Just fetching data.”
to
“Reacting to changes in real time.”

Observe the Trade-Offs Yourself

This is the most valuable part.

As you run this locally, pay attention to:

How often responses don’t change
How quickly updates appear
How many requests are you making
How the event-driven setup feels more responsive

You’ll start to feel the difference between polling and event-driven systems, not just understand it conceptually.

A Simple Next Step

Once you’ve got this running, try one small upgrade:

Store flight data in a database instead of memory
Or trigger a notification when a status changes

That’s the point where this turns from a demo into something you could actually build on. If you want to take this further and build a full frontend around this, check out this guide on building a real-time flight tracking app with Aviationstack and React:

https://blog.apilayer.com/real-time-flight-tracking-app-aviationstack-react/

Conclusion

At first glance, polling vs webhooks feels like a technical detail.

But once you start working with real flight data, it quickly becomes a core architectural decision.

Flight updates are unpredictable. Delays, cancellations, and gate changes don’t follow a schedule, and how you choose to handle those updates directly affects your app’s responsiveness, cost, and complexity.

Polling gives you a simple, reliable starting point. You can get up and running in minutes, and for small-scale use cases, it’s often all you need.

But as soon as you start tracking more flights or need faster updates, the limitations become obvious. You end up making thousands of unnecessary requests and introducing delays that users can feel.

That’s where an event-driven approach comes in.

Even though Aviationstack doesn’t offer native webhooks, you can still build a webhook-style system on top of polling. By detecting changes and emitting events internally, you get much closer to real-time behaviour while using your API quota more efficiently.

The key takeaway is simple:

Start with polling for simplicity
Add an event layer when you need speed or scale
Use a hybrid approach to balance both

There’s no need to over-engineer upfront, but there is a clear path to evolve your system as your requirements grow.

Aviationstack’s free tier gives you 100 requests/month — enough to run the polling script above against live flights and see real data flowing. Grab your free API key at aviationstack.com and start building.

FAQ

What is the difference between polling and webhooks?

Polling means your application repeatedly asks an API for updates at a fixed interval. Webhooks (or event-driven systems) flip that model. Instead of asking, your system gets notified when something changes.

In short:

Polling = “Anything new?”
Webhooks = “Here’s what changed.”

Does Aviationstack support webhooks?

No. Aviationstack is a REST API, which means it only supports pulling data, not pushing updates.

However, you can build a webhook-style system on top of it by:

Polling the API
Detecting changes
Emitting events internally

This gives you many of the benefits of webhooks without native support.

How often should I poll a flight API?

It depends on your use case:

Every 60 seconds → good balance for most apps
Every 30 seconds → more responsive, higher API usage
Every 2–5 minutes → lower cost, but more delay

If you’re tracking many flights, start with a longer interval and optimize from there.

How can I reduce API usage when polling?

A few practical strategies:

Poll only the flights you actually care about
Increase your polling interval where possible
Cache previous responses and only act on changes
Batch requests instead of making one request per flight

You can also layer an event-driven system on top so downstream logic only runs when something changes.

Can I simulate webhooks with a REST API?

Yes, and that’s exactly what we did in this guide.

The pattern looks like this:

Poll the API (Aviationstack)
Detect changes in the response
Emit an event when something changes
Send that event to another service (like a webhook endpoint)

This is often called a hybrid or event-driven-on-polling architecture, and it’s very common when working with REST APIs.

Is polling always a bad choice?

Not at all.

Polling is often the best choice when:

You’re building a small app or prototype
You don’t need real-time updates
You want to keep infrastructure simple

Many production systems start with polling and only evolve when scaling demands it.

What’s the biggest mistake developers make here?

Over-engineering too early.

It’s tempting to jump straight into event-driven systems, queues, and complex architectures. But if you’re only tracking a few flights, simple polling is usually the better choice.

Start simple. Add complexity only when you actually need it.

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