Q4 - Scalability & Load Balancing
Objective
Design a scalable architecture capable of handling 15,000 requests per second on the Ghaymah Container Platform.
Proposed Architecture
The solution uses:
- Ghaymah Load Balancer
- 39 Application Containers
- PostgreSQL Database
- Redis Cache
- Ghaymah Block Storage
- Monitoring and Health Checks
The Load Balancer distributes incoming traffic evenly across all application containers while health checks ensure traffic is only routed to healthy instances.
Container Calculation
Expected Traffic
- 15,000 requests/second
Container Capacity
- 500 requests/second
Required Containers
15000 / 500 = 30
Including 30% reserve capacity
30 × 1.3 = 39 containers
Cold Start Strategy
The platform keeps additional warm containers available to reduce startup latency during sudden traffic spikes.
New containers are automatically created when resource utilization reaches the defined thresholds and are added to the Load Balancer only after passing health checks.
Ghaymah Block Storage
Persistent storage is attached to the database layer to ensure application data survives container restarts and deployments.
Suitable workloads include:
- Databases
- Logs
- Uploaded files
- Stateful applications
Monitoring
The deployment should continuously monitor:
- CPU Utilization
- Memory Usage
- Response Time
- Error Rate
- Container Health
- Restart Count
Alerts should be triggered before resources reach critical levels to prevent service interruption.