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advanced Phase · Backend Project Architecture

Client -> Load Balancer -> Backend -> Cache -> Database

Production architecture with load balancing and caching.

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Full Architecture

Complete Request Flow

Client → Load Balancer → App Server → Cache → Database
  ↑                                          ↓
  ←──────────── Response ←──────────────────

Component Roles

Component Role
Client Sends request
Load Balancer Distributes traffic
App Server Processes logic
Cache Fast data access
Database Persistent storage

Key Points

  • Understanding Client-LB-Cache-DB Architecture is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Cache Best Practices

Strategies

  • Cache-Aside: Application manages cache
  • Write-Through: Sync write to cache and DB
  • Write-Behind: Async write to DB
  • Read-Through: Cache loads from DB

Invalidation

  • Time-based TTL
  • Event-based invalidation
  • Version-based keys
  • Tag-based grouping

Monitoring

  • Hit rate > 80% is good
  • Monitor eviction rates
  • Track cache size
  • Alert on anomalies

Key Points

  • Understanding Client-LB-Cache-DB Architecture is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0 / 3 solved
Implement Client-LB-Cache-DB Architecture

Design and implement a solution for Client-LB-Cache-DB Architecture in a backend system. Consider scalability, error handling, and production readiness.

Solution 
// Client-LB-Cache-DB Architecture implementation
// Key aspects: validation, error handling, logging, testing

public class ClientLBCacheDBArchitecture {
    // Production-ready implementation
}
Client-LB-Cache-DB Architecture Edge Cases

Identify and handle edge cases for Client-LB-Cache-DB Architecture. What happens under high load, with invalid input, or during failures?

Solution 
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotency
Client-LB-Cache-DB Architecture Testing Strategy

Write a testing strategy for Client-LB-Cache-DB Architecture. Include unit tests, integration tests, and performance tests.

Solution 
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. Load balancer sits between?

Question 1 options

2. Cache reduces?

Question 2 options

3. What is a common mistake when implementing Client-LB-Cache-DB Architecture?

Question 3 options

Flashcards

Question

Load balancer position?

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Answer

Between client and app server

Question

Cache reduces?

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Answer

Database load and latency

Question

Client-LB-Cache-DB Architecture best practices

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Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1. Client → LB → App → Cache → DB
  • 2. Each component has specific role
  • 3. Cache reduces DB load
  • 4. LB distributes traffic

Interview Tips

  • • Design full architecture
  • • Explain request flow

Cheat Sheet

Full Architecture

  • Client → LB → App → Cache → DB
  • LB: distribute traffic
  • Cache: reduce DB load
  • App: process logic