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q4-scalability/calculations.md
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q4-scalability/calculations.md
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# Scalability Design
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## 1. Architecture
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The application is deployed on a Kubernetes cluster hosted on Ghaymah Cloud.
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Incoming traffic is distributed through a Ghaymah Load Balancer across multiple application containers. The application stores persistent data using Ghaymah Block Storage, which is mounted as a Persistent Volume.
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---
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## 2. Required Number of Containers
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### Given
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- Incoming traffic = **15,000 requests/second**
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- One container handles = **500 requests/second**
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- Safety margin = **30%**
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### Step 1
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Base number of containers
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15000 / 500 = 30 containers
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### Step 2
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Add 30% capacity
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30 × 1.3 = 39 containers
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### Final Answer
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**39 containers**
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---
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## 3. Cold Start Strategy
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To reduce startup latency for newly created containers:
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- Keep a minimum number of warm replicas running.
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- Use Kubernetes readiness probes before routing traffic.
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- Pull container images in advance on cluster nodes.
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- Use Horizontal Pod Autoscaler (HPA) to scale before traffic reaches peak levels.
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- Deploy applications with rolling updates to avoid downtime.
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---
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## 4. Using Ghaymah Block Storage
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Ghaymah Block Storage provides persistent storage for stateful workloads.
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Typical use cases include:
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- Databases
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- PostgreSQL
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- MySQL
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- Redis persistence
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- Application uploaded files
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- Persistent logs
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Benefits:
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- Data persists even if a container is recreated.
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- Storage can be attached to new containers.
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- Reliable and durable storage for production workloads.
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