Ex 1: Custom Load Balancer

Created by ChatGPT

• cd server1

• run python3 -m http.server 8001

• cd server2

• run python3 -m http.server 8002

• cd server3

• run python3 -m http.server 8003

• run python3 LoadBalancer.py

Ex 2: Custom In Memory Cache

Created by Claude Sonnet 4:

Key Features:

Cache Implementation:

• Thread-safe: Uses RLock for concurrent access
• TTL Support: Configurable time-to-live for cache entries
• LRU Eviction: Automatically removes least recently used items when at capacity
• Automatic Cleanup: Removes expired items during operations

REST API Endpoints:

• PUT /cache/<key> - Store values with optional TTL
• GET /cache/<key> - Retrieve values
• DELETE /cache/<key> - Remove specific keys
• GET /cache/stats - Get cache statistics
• DELETE /cache - Clear entire cache

Usage Examples:

1. Store a value:

curl -X PUT http://localhost:5000/cache/user123 \
  -H 'Content-Type: application/json' \
  -d '{"value": {"name": "John", "age": 30}, "ttl": 600}'

2. Retrieve a value:

curl -X GET http://localhost:5000/cache/user123

3. Get cache statistics:

curl -X GET http://localhost:5000/cache/stats

Installation Requirements:

pip install flask

Configuration Options:

• max_size: Maximum cache capacity (default: 1000)
• default_ttl: Default expiration time in seconds (default: 3600)

The cache handles various data types (strings, numbers, objects) and includes proper error handling, JSON responses, and HTTP status codes. The implementation is production-ready with comprehensive logging and statistics tracking.