Redis Best Practices
Core Principles
- Use Redis for caching, session storage, real-time analytics, and message queuing
- Choose appropriate data structures for your use case
- Implement proper key naming conventions and expiration policies
- Design for high availability and persistence requirements
- Monitor memory usage and optimize for performance
Key Naming Conventions
- Use colons as namespace separators
- Include object type and identifier in key names
- Keep keys short but descriptive
- Use consistent naming patterns across your application
# Good key naming examples
user:1234:profile
user:1234:sessions
order:5678:items
cache:api:products:list
queue:email:pending
session:abc123def456
rate_limit:api:user:1234
Data Structures
Strings
- Use for simple key-value storage, counters, and caching
- Consider using MGET/MSET for batch operations
# Simple caching
SET cache:user:1234 '{"name":"John","email":"john@example.com"}' EX 3600
# Counters
INCR stats:pageviews:homepage
INCRBY stats:downloads:file123 5
# Atomic operations
SETNX lock:resource:456 "owner:abc" EX 30
Hashes
- Use for objects with multiple fields
- More memory-efficient than multiple string keys
- Supports partial updates
# Store user profile
HSET user:1234 name "John Doe" email "john@example.com" created_at "2024-01-15"
# Get specific fields
HGET user:1234 email
HMGET user:1234 name email
# Increment numeric fields
HINCRBY user:1234 login_count 1
# Get all fields
HGETALL user:1234
Lists
- Use for queues, recent items, and activity feeds
- Consider blocking operations for queue consumers
# Message queue
LPUSH queue:emails '{"to":"user@example.com","subject":"Welcome"}'
RPOP queue:emails
# Blocking pop for workers
BRPOP queue:emails 30
# Recent activity (keep last 100)
LPUSH user:1234:activity "viewed product 567"
LTRIM user:1234:activity 0 99
# Get recent items
LRANGE user:1234:activity 0 9
Sets
- Use for unique collections, tags, and relationships
- Supports set operations (union, intersection, difference)
# User tags/interests
SADD user:1234:interests "technology" "music" "travel"
# Check membership
SISMEMBER user:1234:interests "music"
# Find common interests
SINTER user:1234:interests user:5678:interests
# Online users tracking
SADD online:users "user:1234"
SREM online:users "user:1234"
SMEMBERS online:users
Sorted Sets
- Use for leaderboards, priority queues, and time-series data
- Elements sorted by score
# Leaderboard
ZADD leaderboard:game1 1500 "player:123" 2000 "player:456" 1800 "player:789"
# Get top 10
ZREVRANGE leaderboard:game1 0 9 WITHSCORES
# Get player rank
ZREVRANK leaderboard:game1 "player:123"
# Time-based data (score = timestamp)
ZADD events:user:1234 1705329600 "login" 1705330000 "purchase"
# Get events in time range
ZRANGEBYSCORE events:user:1234 1705329600 1705333200
Streams
- Use for event streaming and log data
- Supports consumer groups for distributed processing
# Add events to stream
XADD events:orders * customer_id 1234 product_id 567 amount 99.99
# Read from stream
XREAD COUNT 10 STREAMS events:orders 0
# Consumer groups
XGROUP CREATE events:orders order-processors $ MKSTREAM
XREADGROUP GROUP order-processors worker1 COUNT 10 STREAMS events:orders >
# Acknowledge processed messages
XACK events:orders order-processors 1234567890-0
Caching Patterns
Cache-Aside Pattern
# Pseudo-code for cache-aside
def get_user(user_id):
# Try cache first
cached = redis.get(f"cache:user:{user_id}")
if cached:
return json.loads(cached)
# Cache miss - fetch from database
user = database.get_user(user_id)
# Store in cache with expiration
redis.setex(f"cache:user:{user_id}", 3600, json.dumps(user))
return user
Write-Through Pattern
def update_user(user_id, data):
# Update database
database.update_user(user_id, data)
# Update cache
redis.setex(f"cache:user:{user_id}", 3600, json.dumps(data))
Cache Invalidation
# Delete specific cache
DEL cache:user:1234
# Delete by pattern (use with caution in production)
# Use SCAN instead of KEYS for large datasets
SCAN 0 MATCH cache:user:* COUNT 100
# Tag-based invalidation using sets
SADD cache:tags:user:1234 "cache:user:1234:profile" "cache:user:1234:orders"
# Invalidate all related caches
SMEMBERS cache:tags:user:1234
# Then delete each key
Expiration and Memory Management
TTL Best Practices
- Always set TTL on cache keys
- Use jitter to prevent thundering herd
- Consider sliding expiration for session data
# Set with expiration
SET cache:data:123 "value" EX 3600
# Set expiration on existing key
EXPIRE cache:data:123 3600
# Check TTL
TTL cache:data:123
# Persist key (remove expiration)
PERSIST cache:data:123
Memory Management
# Check memory usage
INFO memory
# Get key memory usage
MEMORY USAGE cache:large:object
# Configure max memory policy
CONFIG SET maxmemory 2gb
CONFIG SET maxmemory-policy allkeys-lru
Transactions and Atomicity
MULTI/EXEC Transactions
# Transaction block
MULTI
INCR stats:views
LPUSH recent:views "page:123"
EXEC
# Watch for optimistic locking
WATCH user:1234:balance
balance = GET user:1234:balance
MULTI
SET user:1234:balance (balance - 100)
EXEC
Lua Scripts
- Use for complex atomic operations
- Scripts execute atomically
-- Rate limiting script
local key = KEYS[1]
local limit = tonumber(ARGV[1])
local window = tonumber(ARGV[2])
local current = tonumber(redis.call('GET', key) or '0')
if current >= limit then
return 0
end
redis.call('INCR', key)
if current == 0 then
redis.call('EXPIRE', key, window)
end
return 1
# Execute Lua script
EVAL "return redis.call('GET', KEYS[1])" 1 mykey
Pub/Sub and Messaging
# Publisher
PUBLISH channel:notifications '{"type":"alert","message":"New order"}'
# Subscriber
SUBSCRIBE channel:notifications
# Pattern subscription
PSUBSCRIBE channel:*
High Availability
Replication
- Use replicas for read scaling
- Configure proper persistence on master
# On replica
REPLICAOF master_host 6379
# Check replication status
INFO replication
Redis Sentinel
- Use for automatic failover
- Deploy at least 3 Sentinel instances
Redis Cluster
- Use for horizontal scaling
- Data automatically sharded across nodes
- Use hash tags for related keys
# Hash tags ensure keys go to same slot
SET {user:1234}:profile "data"
SET {user:1234}:settings "data"
Persistence
RDB Snapshots
# Manual snapshot
BGSAVE
# Configure automatic snapshots
CONFIG SET save "900 1 300 10 60 10000"
AOF (Append-Only File)
# Enable AOF
CONFIG SET appendonly yes
CONFIG SET appendfsync everysec
# Rewrite AOF
BGREWRITEAOF
Security
- Require authentication
- Use TLS for connections
- Bind to specific interfaces
- Disable dangerous commands
# Set password
CONFIG SET requirepass "your_strong_password"
# Authenticate
AUTH your_strong_password
# Rename dangerous commands (in redis.conf)
rename-command FLUSHALL ""
rename-command FLUSHDB ""
rename-command KEYS ""
Monitoring
# Server info
INFO
# Memory stats
INFO memory
# Client connections
CLIENT LIST
# Slow log
SLOWLOG GET 10
# Monitor commands (debug only)
MONITOR
# Key count per database
INFO keyspace
Connection Management
- Use connection pooling
- Set appropriate timeouts
- Handle reconnection gracefully
# Python example with connection pool
import redis
pool = redis.ConnectionPool(
host='localhost',
port=6379,
max_connections=50,
socket_timeout=5,
socket_connect_timeout=5
)
redis_client = redis.Redis(connection_pool=pool)
Performance Tips
- Use pipelining for batch operations
- Avoid large keys (>100KB values)
- Use SCAN instead of KEYS in production
- Monitor and optimize memory usage
- Consider using RedisJSON for complex JSON operations
# Pipeline example (pseudo-code)
pipe = redis.pipeline()
pipe.get("key1")
pipe.get("key2")
pipe.set("key3", "value")
results = pipe.execute()
