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Load Balancing - System Design Interview Guide
Table of Contents
- 🔷 Load Balancer (LB)
- 🧠 What it REALLY is
- ⚡ Why we need it (REAL reason)
- 🔧 How it works
- 📍 Where to place LBs (IMPORTANT)
- 1. Client → Web servers
- 2. Web → App / Cache layer
- 3. App → Database
- 🔥 Insight
- 🚀 Benefits (Condensed)
- ⚙️ Common Algorithms (Must Know)
- 1. Round Robin
- 2. Least Connections
- 3. IP Hash
- 🧠 Smart Feature (Senior Level)
- Health Checks
- ⚠️ Big Problem (Interview Trap)
- ❗ LB itself = Single Point of Failure
- Solution:
- 🔁 Redundant LB (High Availability)
- Insight
- ⚡ Real Example
- Netflix / YouTube
- 🎤 Interview Script (Memorize This)
- Start
- Explain
- Add Depth
- Multi-layer (VERY STRONG)
- Reliability
- 🧠 Final Cheat Sheet
- 💡 Golden Line
🔷 Load Balancer (LB)
🧠 What it REALLY is
"A load balancer distributes incoming requests across multiple servers to prevent overload and improve availability."
⚡ Why we need it (REAL reason)
Without LB:
- One server overloaded ❌
- System crashes ❌
With LB:
- Traffic distributed ✅
- System stable ✅
🔧 How it works
👉 Sits between client → servers
Flow:
User → Load Balancer → Multiple Servers
👉 Also does:
- Health checks (is server alive?)
- Stops sending traffic to failed servers
📍 Where to place LBs (IMPORTANT)
1. Client → Web servers
- Distribute user traffic
2. Web → App / Cache layer
- Balance internal processing
3. App → Database
- Spread DB load (read replicas)
🔥 Insight
"Real systems use load balancing at EVERY layer"
🚀 Benefits (Condensed)
- ✅ Faster response (no overload)
- ✅ High availability (failover)
- ✅ Better throughput
- ✅ No single point of failure (if designed well)
⚙️ Common Algorithms (Must Know)
1. Round Robin
👉 Requests distributed equally
Example:
- Req1 → Server A
- Req2 → Server B
2. Least Connections
👉 Send to least busy server
3. IP Hash
👉 Same user → same server
👉 Useful for session-based systems
🧠 Smart Feature (Senior Level)
Health Checks
"LB continuously checks which servers are healthy."
- Server slow ❌
- Server down ❌ → LB removes it from rotation
⚠️ Big Problem (Interview Trap)
❗ LB itself = Single Point of Failure
Solution:
👉 Use redundant load balancers
🔁 Redundant LB (High Availability)
LB1 (Active)
LB2 (Backup)
- If LB1 fails → LB2 takes over
Insight
"Everything in distributed systems must be redundant"
⚡ Real Example
Netflix / YouTube
- Millions of users
- Thousands of servers
👉 LB ensures:
- Even traffic distribution
- No server overload
🎤 Interview Script (Memorize This)
Start
"To handle traffic efficiently, I'll introduce a load balancer in front of the servers."
Explain
"The load balancer distributes incoming requests across multiple servers and performs health checks to avoid sending traffic to failed instances."
Add Depth
"We can use algorithms like round robin or least connections depending on traffic patterns."
Multi-layer (VERY STRONG)
"We can place load balancers at multiple layers — between client and web servers, application layer, and database layer."
Reliability
"To avoid single point of failure, we'll use redundant load balancers with failover."
🧠 Final Cheat Sheet
| Concept | Meaning |
|---|---|
| Load Balancer | Distributes traffic |
| Health Check | Detects failed servers |
| Algorithms | Round robin, least connections |
| Placement | Every layer |
| Risk | LB failure |
| Fix | Redundant LBs |
💡 Golden Line
"A load balancer ensures scalability and availability by distributing traffic and eliminating overloaded or failed servers."