System Scalability in IT Architecture

System Scalability in Information Technology Architecture

📘 Overview System scalability describes a system's capacity to handle increasing workloads or to expand its size while maintaining performance. Achieving scalability requires architectural design choices that allow resources to be added or upgraded smoothly as demand grows.

🧠 Key Idea System scalability enables IT architectures to efficiently manage growth in users and data by adapting resource capacity without degrading performance.

⚔️ Core Details: - Vertical scalability involves increasing a single server's capacity by adding more CPU, RAM, or storage. - Horizontal scalability involves adding more machines or nodes to a system to distribute load. - Scalability can be measured in terms of throughput, latency, and resource utilization under increased load. - Architectural patterns for scalability include load balancing, caching layers, and database sharding. - Cloud computing environments provide flexible scalability through on-demand resource provisioning. - Scalability must be planned proactively to avoid bottlenecks and single points of failure.

🎯 Why It Matters: - Scalability ensures consistent user experience despite growth in traffic or data volume. - Scalable systems support business expansion without requiring complete redesign. - Efficient scalability minimizes cost by allocating resources only when needed. - Lack of scalability can lead to system failures, data loss, or significant downtime affecting users and revenue.

🧠 Quick Recall: - Vertical Scalability - adding resources to a single server, e.g., CPU or memory upgrades - Horizontal Scalability - increasing capacity by adding more servers or nodes - Load Balancer - a component to distribute network or application traffic across multiple servers - Database Sharding - partitioning a database into smaller, faster, and more manageable pieces - Throughput - the rate at which a system processes requests