The Pragmatic Pixel

Hey everyone, Jamie here.

As our applications grow, they rarely live in a vacuum. We integrate with payment gateways like Stripe, pull in data from social media platforms, react to events in services like Shopify, or track shipments with logistics APIs. A common thread in many of these integrations is the need to react to events as they happen.

Waiting for a user to refresh a page to see if their payment has been processed feels archaic. We need our systems to receive and process data in near real-time. But how do we build our Laravel applications to reliably handle this constant stream of information from external sources?

This isn't about broadcasting data from our app (we've talked about WebSockets for that), but about being an effective listener. There are a few common patterns for this, each with its own trade-offs.

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Method 1: Polling (The “Are We There Yet?” Approach)

This is the simplest and most traditional method.

• How it works: You set up a scheduled task (using Laravel's Task Scheduler and a cron job) that runs at a regular interval—say, every minute. This task makes a standard API call to the third-party service, asking, “Do you have anything new for me since last time?”
• Pros:
  • Universal: It works with almost any API that has a standard endpoint for fetching data.
  • Simple to Implement: A scheduled Artisan command that makes a Guzzle request is straightforward to set up.
• Cons:
  • Inefficient: The vast majority of your requests will likely come back empty, wasting both your server resources and the third-party's.
  • Not Truly Real-Time: There will always be a delay of up to your polling interval. If you poll every minute, your data could be up to 59 seconds out of date.
  • Rate Limit Danger: Polling frequently is the fastest way to hit API rate limits, which can get your application temporarily blocked.

When to use it: Polling is a last resort. Use it only when the data isn't critically time-sensitive and the third-party API offers no better alternative.

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Method 2: Webhooks (The “Don't Call Us, We'll Call You” Approach)

This is the modern standard for server-to-server communication and by far the preferred method.

• How it works: You provide the third-party service with a unique URL in your application (a “webhook endpoint”). When a specific event occurs on their end (e.g., a successful payment, a new subscription), their server sends an HTTP POST request to your URL with a payload of data about that event.
• Pros:
  • Highly Efficient & Real-Time: Your application only does work when there's actually something new to report. The data arrives almost instantly.
  • Scalable: It scales much better than polling because it avoids constant, unnecessary requests.
• Cons:
  • Requires Support: The third-party API must offer webhooks.
  • Security is Key: Your endpoint is publicly accessible, so you must verify that incoming requests are genuinely from the third-party service. Most services do this by including a unique signature in the request headers, which you can validate using a shared secret.
  • Initial Setup: It requires a bit more setup than a simple polling command.

When to use it: Almost always, if the service provides it. This is the gold standard for event-driven integrations.

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Method 3: WebSockets (The “Dedicated Hotline” Approach)

This is the least common method for this specific use case but is worth knowing about.

• How it works: Instead of them calling you (webhook) or you calling them (polling), your application would establish a persistent, two-way WebSocket connection to their service. They would then push data down this open connection as events happen.
• Pros:
  • The Fastest: This is the absolute lowest-latency, most real-time option available.
• Cons:
  • Rarely Offered: Very few standard third-party APIs (like payment gateways or e-commerce platforms) offer a public WebSocket interface for this kind of integration. It's more common for real-time financial data feeds or live sports tickers.
  • Complexity: Managing a persistent client connection from your backend, including handling disconnects and retries, adds significant complexity to your application.

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Pragmatic Implementation in Laravel: Queues are Essential

Regardless of how the data arrives (polling or webhook), the next step is critical: process it asynchronously.

Never, ever perform complex logic directly in the controller that receives a webhook. A webhook request should be acknowledged as quickly as possible with a 200 OK response. If you try to process the data, update your database, and call other services during that initial request, you risk timeouts, which can cause the third-party service to think your webhook failed and retry it, leading to duplicate data.

The Golden Rule: Acknowledge, then Queue.

1. Create a dedicated route and controller for your webhook endpoint (e.g., Route::post('/webhooks/stripe', [StripeWebhookController::class, 'handle']);).
2. In the controller:
   • Verify the webhook signature to ensure it's authentic.
   • Immediately dispatch a Job onto your queue with the webhook payload.
   • Return a response()->json(['status' => 'success'], 200);
3. Create a Job Class (e.g., ProcessStripeWebhook.php).
   • This job will contain all the heavy logic: parsing the payload, creating or updating models, sending notifications, etc.
4. Run a Queue Worker: Have a queue worker process (php artisan queue:work) running on your server to pick up and execute these jobs in the background.

This pattern makes your webhook integration incredibly robust. It can handle spikes in traffic, and if a job fails for some reason, Laravel's queue system can automatically retry it without losing the original webhook data.

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Choosing the right method to ingest real-time data is about understanding the tools offered by the third-party service and the needs of your application. But no matter how the data arrives, handling it with a resilient, queue-based architecture is the key to building a stable and scalable system.

Cheers,

Jamie