Q2: Horizontal vs Vertical Scaling: Architectural Trade-offs and Bottlenecks. - System Design (50 Qs)

In Simple Words:

Vertical Scaling (Scale-Up): Adding more CPU, RAM, or NVMe disk capacity to a single physical or virtual machine.
Horizontal Scaling (Scale-Out): Adding more discrete commodity instances into a distributed pool behind a load balancer.

Parameter	Vertical Scaling (Scale-Up)	Horizontal Scaling (Scale-Out)
Complexity	Minimal (no distributed systems logic)	High (requires load balancing, statelessness, discovery)
Hardware Limit	Hard physical ceilings (e.g., AWS `u-24tb1.112xlarge`)	Practically infinite linear capacity
Availability	Single Point of Failure (SPOF) during hardware fault	Highly fault-tolerant (node failures auto-healed)
Network Overhead	Zero network latency (inter-thread IPC)	Network serialization, latency, and RPC overhead
Cost Curve	Exponential cost for high-end enterprise hardware	Linear cost using standard commodity compute

typescript

// Architectural Rule: Designing Stateless Compute Services for Infinite Horizontal Scale
interface UserSession {
  userId: string;
  roles: string[];
  expiresAt: number;
}

// ❌ Anti-pattern: In-memory session state breaks horizontal scaling
const inMemorySessionStore = new Map<string, UserSession>();

// ✅ Optimal Pattern: External shared distributed session store or stateless JWT
export async function getSession(sessionId: string, redisClient: any): Promise<UserSession | null> {
  const data = await redisClient.get(`session:${sessionId}`);
  return data ? JSON.parse(data) : null;
}