How I plan on scaling my Laravel (PHP) application

Scaling 10MPage.com: A Pragmatic Approach to Hosting a Growing Internet Archive

10MPage.com aims to capture the internet's state in 2025 by allowing users to contribute 64x64 pixel images to a massive online archive. As a solo developer, I'm prioritizing cost-effectiveness in the early stages, hosting on a budget-friendly VPS. However, a scalable architecture is crucial for future growth. This article details my phased scaling plan, focusing on simplicity and minimal downtime.

Application Architecture:

The application, built with Laravel and PHP, relies heavily on background processes (managed by Laravel Horizon and Supervisor) for image handling, grid placement, and email delivery. Redis handles caching and jobs, while MySQL stores the data. Nginx and PHP-FPM serve web requests. The initial single-server setup is illustrated below:

Scaling Strategy:

My scaling plan involves a gradual transition to a multi-server architecture, minimizing downtime at each step:

Phase 1: Isolating Redis (Zero Downtime)

The first step is to move Redis to a separate server. The application can temporarily use local filesystem caching, and the job queue can be briefly paused. This involves setting up a new server, configuring network access, and redirecting Redis connections. Once the migration is complete, Redis on the original server is shut down and uninstalled.

Phase 2: Implementing a Load Balancer (Zero Downtime)

Next, I'll introduce HAProxy as a load balancer, leveraging its advanced features like active health checks. This server will also handle SSL termination. DNS will be updated to point to the load balancer, distributing traffic to the existing web server.

Phase 3: Distributing Worker Servers (Zero Downtime)

Laravel Horizon's design allows for seamless addition of worker servers. A new server will be set up, the application deployed, and the worker started using Supervisor. The original worker can then be shut down. Scaling workers simply involves replicating this process.

Phase 4: Deploying Multiple Web Servers (Zero Downtime)

Similar to worker servers, additional web servers are added, configured with Nginx and PHP-FPM, and registered with the load balancer. Replication is straightforward, ensuring high availability.

Phase 5: Dedicate Database Server (Minimal Downtime)

Finally, the original server becomes the dedicated database server. All unnecessary software is removed. While a single, powerful database server is sufficient for now, scaling this component in the future might require clustering and brief downtime.

Deployment Automation:

My Git-based deployment process will be adapted to handle multiple servers, using scripts to deploy and restart services only when needed (e.g., checking Horizon status before restarting).

Addressing Single Points of Failure:

The current architecture has single points of failure (load balancer, database, Redis). Future improvements will include redundancy for the load balancer. Database and Redis scaling will be addressed in a future article.

Containers and Clusters:

While I appreciate containers and clusters, I believe they are overkill for this project's current scale. The chosen approach prioritizes rapid initial setup and avoids unnecessary complexity. Machine snapshots and cloning will suffice for scaling in the early phases.

Conclusion:

This pragmatic scaling plan prioritizes simplicity and cost-effectiveness while ensuring 10MPage.com can handle future growth. The phased approach minimizes downtime and maintains functionality throughout the scaling process. By focusing on a clear, incremental strategy, I can dedicate my efforts to building the project itself, adding one tile at a time to this ambitious internet archive. Contribute your own tile today!

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