10 Essential Redis Tips to Boost Performance and Reliability

Redis has become a hot technology in the community, evolving from Antirez's personal project to the industry standard for in‑memory data storage.

Below are ten essential tips for using Redis correctly.

1. Stop using KEYS *

Running KEYS * on large datasets is slow (O(n)) and blocks other commands. Use SCAN instead, which iterates incrementally and can be paused or resumed.

for key in 'keys *':
    doAllTheThings()

2. Identify performance bottlenecks

Redis lacks detailed logs, but the INFO commandstats command provides a snapshot of command usage, including call counts and execution time. Reset statistics with CONFIG RESETSTAT to start fresh.

127.0.0.1:6379> INFO commandstats
# Commandstats
cmdstat_get:calls=78,usec=608,usec_per_call=7.79
cmdstat_setex:calls=5,usec=71,usec_per_call=14.20
cmdstat_keys:calls=2,usec=42,usec_per_call=21.00
cmdstat_info:calls=10,usec=1931,usec_per_call=193.10

3. Use Redis‑Benchmark as a reference, not a definitive metric

Benchmark results vary with client environment, Redis version, and test conditions. Consider these factors before drawing conclusions.

Client runtime limitations

Version differences

Test environment vs. production environment

4. Prefer hashes for related fields

Instead of storing each attribute as a separate key (e.g., foo:first_name, foo:last_name), use a hash to keep all fields under a single key.

127.0.0.1:6379> HSET foo first_name "Joe"
(integer) 1
127.0.0.1:6379> HSET foo last_name "Engel"
(integer) 1
127.0.0.1:6379> HSET foo address "1 Fanatical Pl"
(integer) 1
127.0.0.1:6379> HGETALL foo
1) "first_name"
2) "Joe"
3) "last_name"
4) "Engel"
5) "address"
6) "1 Fanatical Pl"
127.0.0.1:6379> HGET foo first_name
"Joe"

5. Set key expiration (TTL)

Use key expiration for temporary data such as authentication tokens, allowing Redis to automatically delete them.

6. Choose the right eviction policy

If keys have expirations, use volatile-lru. For pure caching without expirations, consider allkeys-lru.

7. Protect critical data with try/except

Wrap important write operations in try/except blocks to ensure data is actually stored, as many clients use a fire‑and‑forget approach.

8. Avoid exhausting a single instance

Distribute load across multiple Redis instances or use Redis Cluster (available since 3.0.0) to shard data by key range.

9. More CPU cores don’t improve Redis performance

Redis is single‑threaded; even with persistence it typically uses at most two cores. Running multiple instances on one machine is only useful for testing.

10. Ensure high availability with Redis Sentinel

Sentinel provides robust monitoring and automatic failover for production deployments that heavily rely on Redis.