Caching Strategies

# Without Cache: Slow
User Request ✓ API Server ✓ Database (200ms) ✓ Response
Total: 200ms

# With Cache: Fast
User Request ✓ API Server ✓ Cache (1ms) ✓ Response
Total: 1ms

# Cache Hit: Data cache mein mila ✓ Fast response
# Cache Miss: Data cache mein nahi ✓ Database se lo, cache mein store karo

# Real numbers:
- Database read: 5-200ms
- Redis read: 0.1-1ms
- Cache hit ratio target: >95%

# 1. Cache-Aside (Lazy Loading) � Most Common

Application pehle cache check karta hai:
- Cache HIT ✓ Direct cache se data lo
- Cache MISS ✓ Database se lo ✓ Cache mein store karo

# Pros: Only requested data cache hota hai
# Cons: First request slow (cache miss)
# Use: General purpose, read-heavy apps

# 2. Write-Through

Har write operation ke saath cache bhi update:
- Write ✓ Cache + Database dono update
- Read ✓ Cache se seedha

# Pros: Data always consistent
# Cons: Write slow (donon jagah write)
# Use: Session storage, user preferences

# 3. Write-Behind (Write-Back)

Write sirf cache mein, database baad mein:
- Write ✓ Cache update ✓ Database baad mein (async)
- Read ✓ Cache se

# Pros: Write bahut fast
# Cons: Data loss risk (cache crash)
# Use: Analytics, logs, non-critical data

# 4. Read-Through

Cache khud database se data fetch karta hai:
- Application sirf cache se baat karta hai
- Cache internally database se data laata hai

# Pros: Application code simple
# Cons: Cache layer complex
# Use: Managed caching services

# Redis vs Memcached

| Feature | Redis | Memcached |
|----------------|--------------------------|------------------------|
| Data Types | Strings, Lists, Sets, | Strings only |
| | Hashes, Sorted Sets | |
| Persistence | Yes (RDB/AOF) | No |
| Pub/Sub | Yes | No |
| Clustering | Yes (built-in) | Yes (client-side) |
| Memory | More efficient | Less efficient |
| Use Case | Session, leaderboards, | Simple caching, |
| | real-time analytics | page caching |

# When to use what?
- Simple key-value caching ✓ Memcached
- Complex data + persistence ✓ Redis
- Both are great for most use cases

# CDN Flow

User (India) ✓ Request for image.jpg
CDN Edge Server (Mumbai) ✓ Cache mein hai? 
 YES ✓ Seedha return (10ms)
 NO ✓ Origin server se fetch (200ms) ✓ Cache mein store ✓ Return

# What to cache in CDN?
- Images, CSS, JS files (static)
- Video thumbnails
- API responses (GET requests)
- HTML pages (for blogs, news)

# CDN Providers:
- Cloudflare (free tier bhi hai)
- AWS CloudFront
- Akamai
- Fastly

# Cache Invalidation:
- TTL (Time To Live) ✓ Auto expire after X seconds
- Manual purge ✓ CDN dashboard se force refresh
- Versioning ✓ file?v=2 ✓ new URL = new cache

# Cache Invalidation Strategies

1. TTL (Time To Live)
 ✓ Data X seconds mein expire ho jaayega
 ✓ Simple but data stale ho sakta hai
 ✓ Example: Redis SET key value EX 3600 (1 hour)

2. Event-Based Invalidation
 ✓ Data change hone pe event publish karo
 ✓ Cache listener sun ke cache delete karta hai
 ✓ Example: User profile update ✓ invalidate user cache

3. Version-Based
 ✓ Har data ke saath version number
 ✓ Cache miss pe version check karo
 ✓ Example: /api/users/123?v=2

4. Write-Through + Invalidation
 ✓ Write ke saath cache invalid karo
 ✓ Next read fresh data lega

# Famous quote: "There are only two hard things in CS:
# Cache invalidation and naming things."