Unleash Your Home Hardware: Processing Long-Running Tasks at Home

Whether it's a web or mobile app, most software involves some form of data handling, user interaction, and server-side logic. Often, you'll encounter tasks that require significant processing time: batch email sends, LLM-powered content generation, heavy-duty ML model runs or working with PDFs (😰). The challenge is to execute these tasks without blocking your main application by slowing down your web server.

Enter the Task Queue

Instead of blocking HTTP requests until these long-running processes complete, consider offloading them to a task queue. This powerful pattern lets you decouple task execution from your primary application flow. Choose any queue you like: Redis/Valkey, RabbitMQ, NATS, Pulsar... the key is the ability to push tasks in and pull them out asynchronously. Some solutions offer much more than you’ll need, while others like Valkey will leave some of the actual queuing logic up to you.

What is a task queue?

At its core, a task queue is a data structure that acts as a temporary holding area for tasks that need to be executed. It functions as a communication channel between different parts of your application or across separate systems/machines. Your web server adds a representation of a long running task (often including relevant data and instructions) to the queue. Meanwhile, dedicated worker processes continuously monitor the queue, pulling out tasks that it can work on and executing them.

There are some more details to this, like pull vs push queues, at-least-once vs at-most-once delivery, timeouts, retries and acknowledgements.

From Remote Server to Home Server

Once your task is in the queue, it's ready to be picked up by any worker process that has access to the queue. This opens up an interesting possibility: running those tasks on your own hardware at home. If you have spare computing power lying around (maybe an old PC, laptop, or even a Raspberry Pi), you can turn it into a mini data center for your long-running tasks.

For web servers, you typically need a fixed IP. This enables you to get a domain for your website served by this web server, or ensure other services know how to reach your API. In our case where worker processes pull from a central task queue though, you can essentially run these processes wherever. They just need to know where to pull tasks from and where to push the results to (like your DB, task queue, another service etc).

The Event-Driven Advantage

This approach aligns perfectly with an event-driven architecture. Your main application triggers an event (e.g. "new user signup") and pushes it to the queue. Your home server runs the appropriate worker process, which picks up the event and performs the necessary long-running task (e.g. sending a welcome email with personalized content generated by an LLM). This decoupling can enable a responsive and scalable system.

A hybrid approach works great as well, where you just push specific events to the queue that you want to be picked up by the worker processes. You don’t need to build everything based on event-driven principles.

Example: PDF Generation Service

Imagine you're building a document management web app. Users can upload files and generate complex reports & download these as PDFs. Generating these reports can be time-consuming, and creating the PDFs might require a large dependency that you don’t want on your highly scalable web server.

1. User uploads data and requests a report: Your web server handles the upload and immediately returns a confirmation to the user, letting them know the report is being processed.

2. Trigger an event: The web server pushes a "generate report" event to the task queue, containing the user's data and report specifications.

3. Home server picks up the task: Your home server, running a worker process, pulls the event from the queue.

4. Generate the report: The worker process utilizes its local resources to generate the PDF report.

5. Store and notify: Once complete, the report is stored (probably in cloud storage for easy access) and the user is notified (maybe via email or a push notification).

   1. The worker could update your DB, or send another event into the queue for a true event driven architecture. It’s your choice.

The Benefits

• Cost Savings: Compared to cloud services, leveraging your existing hardware can be much more cost-effective, especially if you have renewable energy sources like solar panels at home, or just live in a region with low power cost.

• Resource Utilization: Give your old hardware a new purpose and reduce e-waste.

• Scalability: If your home setup reaches its limits, you can still scale out to the cloud using the same task queue pattern. Ideally you’d have some system in place that ensures your home server picks up tasks before the cloud server, if it has availability.

Tools and Deployment

Coolify is an excellent tool for setting up continuous deployment on your home hardware, making it easy to keep your worker processes up-to-date. Remember, any device capable of running Linux can be your home server!

Alternatively you can also create a custom CD setup with Docker Swarm & some bash scripts that continuously check for new commits/PRs. The core of this approach is a script that periodically checks your GitHub repository for updates. If new commits are detected, it triggers a rolling update of your Docker Swarm services, ensuring a seamless transition to the latest version of your worker processes. This is just one alternative, there are many approaches you can take here.

In the end it comes down to your own preferences and experience with these tools. I’d recommend using Coolify, but you could also take this opportunity to dive deeper into Docker and bash scripting.

In Conclusion

Running long-running tasks at home offers a practical and potentially cost-saving alternative to cloud-based solutions. By using a task queue and deploying worker processes on your own devices, you can ensure your main web application stays responsive while making the most of your existing hardware.

Remember:

• Hardware Requirements: Ensure your chosen hardware is capable of handling the tasks you plan to run on it. While you can run Ollama on a Raspberry Pi, you probably shouldn’t do so for important production deployments ;-)

• Power Consumption: Consider the energy costs associated with running your home server. Don’t save on the $10 cloud VPS only to increase your power bill by $20.

• Availability & Scaling: You probably won’t be able to have an uptime of 99.99% at home. Construction work can cut your internet, power outages might happen in your area and you don’t want to troubleshoot an networking issue at 3am or while you’re on vacation. It’s generally a good idea to have at least one worker available in the cloud. You might even have some logic that spins up instances depending on some metric of your task queue if tasks pile up or are stuck in the queue for a long time.

• Security: If you're exposing your home server to the internet, make sure to take appropriate security measures. You should know your way around your router/gateway and set appropriate firewall rules to allow only the in/out traffic you’re expecting.

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That’s it! Please let me know if this was useful, or maybe share how you are utilizing your home hardware in your projects.

Bis demnächst!

~ Martin

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Notes:

• The cover image is AI generated.