How to Install Matomo: Best Server Architecture for Scalability

Matomo, the open-source web analytics platform, is a powerful tool for businesses to monitor website performance and user behavior while maintaining full control of their data. While installing Matomo is straightforward, designing a scalable and efficient server architecture can make all the difference in ensuring reliability and performance as your traffic grows.

Step 1: Installation Basics

Installing Matomo involves these steps:

1. Download Matomo
   
   Visit the Matomo website and download the latest release.
    

2. Set Up Your Server
   
   Ensure your server meets the system requirements:
    

   • PHP version 7.4 or later.
      
   • MySQL 5.7+ or MariaDB 10.1+.
      
   • A web server like Apache or Nginx.
      

3. Run the Installer
   
   Upload Matomo files to your server, set proper permissions, and complete the web-based installer by following the instructions in your browser.
    

Step 2: My Scalable Matomo Architecture

To ensure that Matomo can handle both current traffic and future growth, I’ve designed a robust and scalable system architecture. There is a Matomo Documentation about how to setup. Our Glinteco team successfully configured it properly.

Here’s how it looks:

Key Components:

1. Load Balancer

   • The load balancer routes incoming traffic evenly across multiple Matomo instances. It ensures high availability and prevents any single instance from becoming overwhelmed.
      
   • Handles requests for both tracking.example.com (user tracking) and dashboard.example.com (analytics dashboard).
      

2. Public and Private Subnets

   • Public Subnet: Hosts the Matomo instances and the load balancer, accessible from the internet.
      
   • Private Subnet: Houses the database (RDS) and Redis caching layer, isolated for security and optimized for backend operations.
      

3. Matomo Instances

   • Matomo Master: Handles administrative tasks like cron jobs and configuration changes.
      
   • Matomo Worker Nodes: Focus on processing user tracking data, reducing the load on the master instance.
      
   • Instances synchronize cron jobs to maintain consistency across the system.
      

4. Redis Caching Layer

   • Redis serves as a caching mechanism, storing frequently accessed data to reduce database queries and enhance system performance.
      
   • This caching layer ensures a quicker response time, even under high traffic.
      

5. Database (RDS)

   • A master-replica setup enables seamless scaling:
      
     • The RDS master handles all write operations.
        
     • The RDS read-only replica processes read-heavy traffic, such as generating analytics reports.
        
   • This separation of responsibilities prevents bottlenecks and ensures efficient resource utilization.
      

Scalability Features:

• Horizontal Scaling: Add more Matomo instances as traffic increases. The load balancer distributes traffic dynamically to new servers.
   
• Vertical Scaling: Upgrade the RDS database and Redis resources for larger data storage and faster query handling.
   
• Dynamic Caching: Redis reduces the database load, making it easier to scale without significant performance loss.
   

Step 3: Why This Design is Scalable

This architecture is designed for flexibility and reliability:
 

1. Handles Traffic Spikes
   
   The load balancer and worker nodes can handle sudden surges in traffic by distributing the load and maintaining smooth operation.
    

2. Optimized for Performance
   
   Redis caching and database read replicas ensure that high-demand queries don’t slow down the system.
    

3. Built for Security
   
   By isolating sensitive components like the database and caching layer in a private subnet, the architecture minimizes exposure to external threats.
    

4. Easily Scalable
   
   Whether you need to process more tracking data or generate analytics reports faster, you can scale both horizontally and vertically without downtime.
    

Step 4: Start Small, Think Big

Even if you’re just starting with Matomo, planning for scalability from the beginning saves time and resources in the long run. This architecture ensures your analytics platform remains fast, reliable, and secure as your website grows.

Stay tuned for my next post, where I’ll dive deeper into how I configured this architecture, optimized Redis caching, and automated scaling using cloud tools. Let’s make Matomo not just a web analytics platform but a powerhouse for insights at any scale!