Your application is a hit. Users are flocking to it, but as traffic grows, you notice a worrying trend: response times are slowing down, and the user experience is starting to suffer. That snappy interface you built is now sluggish every time a user uploads a video, generates a report, or signs up for your newsletter. What’s the culprit? Long-running tasks.
These tasks, which are essential to your application's functionality, are blocking your main server processes, creating bottlenecks, and preventing you from scaling effectively.
The solution is to offload these processes to the background. By using a system of background workers and a job queue, you can reclaim your application's speed and create a more reliable, scalable backend. And with modern tools like worker.do, you can do it with a single, simple API, without ever touching infrastructure.
Before we dive into the "how," let's clarify the "what."
A background worker is a process that runs separately from your main application. Its entire purpose is to handle tasks that would otherwise block the user interface or slow down request times. Think of it as a dedicated helper that works tirelessly behind the scenes.
A job queue is the crucial link between your application and these workers. When your main application needs a long-running task performed, it doesn't do the work itself. Instead, it adds a "job" to the queue—a message that describes the task and any necessary data. The background workers constantly monitor this queue, pick up new jobs as they arrive, and process them independently.
This architecture provides three massive benefits:
Traditionally, setting up a job queue system was a significant engineering effort. It involved:
This entire process is a distraction from what you should be doing: building great features for your application.
This is where worker.do changes the game. It abstracts away all the complexity of infrastructure management and presents background processing as Services-as-Software. Instead of building a system, you consume a service through a clean, simple API.
Offload long-running tasks, process job queues, and scale your application's backend effortlessly. It’s that simple.
Let’s look at how easy it is to queue a video processing job using the worker.do SDK.
import { Dô } from '@do/sdk';
// Initialize the .do client with your API key
const dô = new Dô(process.env.DO_API_KEY);
// Enqueue a new job to be processed by a worker
async function queueVideoProcessing(videoId: string) {
const job = await dô.worker.enqueue({
task: 'process-video',
payload: {
id: videoId,
format: '1080p',
watermark: true
}
});
console.log(`Job ${job.id} enqueued successfully!`);
return job.id;
}
With just one asynchronous call to dô.worker.enqueue, you've handed off the heavy lifting. Your main application can immediately respond to the user, confident that the video will be processed in the background. No servers, no message brokers, no complex configuration.
worker.do is more than just a simple API; it’s an entire platform designed to handle the realities of background processing.
How do you handle a sudden influx of a thousand video uploads? With worker.do, you don't. The platform automatically scales your workers based on the number of jobs in the queue. This means you get the massive processing power you need during peak times and save costs by scaling down (even to zero) during lulls. It’s the most efficient way to pay only for what you use.
Transient network errors and temporary service outages happen. Without a robust retry strategy, jobs can be lost forever. worker.do provides built-in, configurable retry logic. If a job fails, the platform automatically retries it using an exponential backoff strategy, ensuring that temporary glitches are handled gracefully without any manual intervention.
Any task that is long-running, resource-intensive, or can be performed asynchronously is a perfect fit for a background worker. Common use cases include:
The power of job queues is undeniable for building modern, scalable applications. But the operational overhead of traditional systems has long been a barrier.
With worker.do, you get all the benefits of a powerful background processing system without any of the infrastructural pain. You can focus on your application's core logic while the platform handles the queueing, scaling, and reliability for you.
Ready to simplify your background workers and scale your application effortlessly? Get started with worker.do today and turn your complex backend processes into simple, manageable APIs.
What is a background worker?
A background worker is a process that runs separately from your main application, handling tasks that would otherwise block the user interface or slow down request times. Common examples include sending emails, processing images, or generating reports.
How does worker.do handle scaling?
The .do platform automatically scales your workers based on the number of jobs in the queue. This means you get the processing power you need during peak times and save costs during lulls, all without managing any infrastructure.
What types of tasks are suitable for worker.do?
Any long-running or resource-intensive task is a great fit. This includes video encoding, data analysis, batch API calls, running AI model inferences, and handling scheduled jobs (cron).
How are job failures and retries managed?
.do provides built-in, configurable retry logic. If a job fails, the platform can automatically retry it with an exponential backoff strategy, ensuring transient errors are handled gracefully without manual intervention.