Redis Caching Strategies for Web Applications

Cache-Aside Pattern

The most common caching pattern — application checks cache first, falls back to database on miss:

# Pseudocode
function getUser(id):
    cached = redis.get("user:" + id)
    if cached:
        return deserialize(cached)

    user = db.query("SELECT * FROM users WHERE id = ?", id)
    redis.setex("user:" + id, 3600, serialize(user))
    return user

Write-Through Cache

Update cache immediately when writing to database:

function updateUser(id, data):
    db.query("UPDATE users SET ... WHERE id = ?", id)
    redis.setex("user:" + id, 3600, serialize(data))

Cache Invalidation

# Delete specific key
redis.delete("user:42")

# Delete by pattern
redis-cli --scan --pattern "user:*" | xargs redis-cli DEL

# Use TTL for automatic expiry
redis.setex("popular_posts", 300, data)  # 5 minutes

Session Storage

# PHP — use Redis for sessions
session.save_handler = redis
session.save_path = "tcp://127.0.0.1:6379"

Full Page Caching

# Cache entire HTML responses
key = "page:" + request.url
cached = redis.get(key)
if cached:
    return cached

html = render_page()
redis.setex(key, 600, html)  # 10 minutes
return html

Monitoring Cache Effectiveness

redis-cli INFO stats | grep -E "keyspace_hits|keyspace_misses"
# Calculate hit rate: hits / (hits + misses) * 100
# Aim for 90%+ hit rate