Overview

To scale the GitLab application in a production environment, several key strategies and techniques can be employed. Below are the detailed steps and considerations.

Step 1: Horizontal Scaling

Horizontal scaling involves adding more instances of components to distribute the workload.

1.1 Application Servers

Deploy multiple GitLab application server nodes behind a load balancer. This will help balance requests among the servers.

Example configuration for nginx load balancer:

http {
    upstream gitlab {
        server app_server1:80;
        server app_server2:80;
        server app_server3:80;
    }

    server {
        listen 80;
        location / {
            proxy_pass http://gitlab;
        }
    }
}

Additional application server nodes can be deployed using Docker or through a Kubernetes cluster.

1.2 Database Scaling

Use a primary-replica (formerly master-slave) database model for read-heavy workloads.

1. Primary Database: Handles all write operations.
2. Replica Databases: Serve read operations.

Configure the database connection pool to distribute read requests:

production:
  adapter: postgresql
  encoding: unicode
  database: gitlab_production
  username: gitlab
  password: <%= ENV['DB_PASSWORD'] %>
  host: <%= ENV['DB_HOST_PRIMARY'] %>
  port: <%= ENV['DB_PORT'] %>
  pool: 5

  replicas:
    - host: <%= ENV['DB_HOST_REPLICA_1'] %>
    - host: <%= ENV['DB_HOST_REPLICA_2'] %>

Step 2: Caching Strategies

Caching can significantly enhance the performance by reducing database load.

2.1 Redis Caching

Utilize Redis for caching to alleviate database load and speed up response times.

Example Redis configuration in gitlab.rb:

redis['enable'] = true
redis['host'] = 'redis.default.svc.cluster.local'
redis['port'] = 6379
redis['db'] = 0
redis['shared_state'] = true

2.2 Page Caching

Enable page caching for static responses to minimize server processing time.

In nginx.conf, configure caching:

location ~* \.(html|css|js|jpg|jpeg|png|gif)$ {
    expires 30d;
    add_header Cache-Control "public";
}

Step 3: Load Balancing

Implement effective load balancing techniques to optimize resource utilization.

3.1 NGINX Configuration

Modify the NGINX configuration to enable HTTP/2 and implement health checks for upstream servers.

http {
    upstream gitlab {
        server app_server1;
        server app_server2;
        server app_server3;

        # Health check setup
        health_check interval=10s timeout=2s fails=3 passes=2;
    }

    server {
        listen 80;
        server_name gitlab.example.com;

        location / {
            proxy_pass http://gitlab;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
            proxy_set_header X-Forwarded-Proto $scheme;
        }
    }
}

3.2 Use of a CDN

For static assets, employ a Content Delivery Network (CDN) to offload bandwidth and reduce latency for global users.

Step 4: Monitoring and Performance Tuning

Implement monitoring tools to analyze performance and resource usage.

4.1 Prometheus and Grafana

Set up Prometheus for metrics collection and Grafana for visualization, allowing real-time monitoring of application performance.

Example configuration for Prometheus scraping:

scrape_configs:
  - job_name: 'gitlab'
    static_configs:
      - targets: ['app_server1:9090', 'app_server2:9090']

4.2 Performance Tuning

Adjust application parameters according to the observed workload. This may include configurations for Sidekiq, Unicorn, and Puma.

Example Sidekiq configuration in gitlab.rb:

sidekiq['concurrency'] = 5
sidekiq['queues'] = ['default', 'mailers', 'low']

Conclusion

By implementing horizontal scaling, caching strategies, load balancers, and monitoring tools, GitLab can scale effectively in a production environment to handle increased traffic and workloads.