01
Hitting maxmemory and evicting keys
Unbounded cache keys pushing out session and rate-limit data, causing application errors.
Redis evictions, keys without TTLs and latency spikes
Redis memory optimization and eviction prevention
Prevent Redis memory exhaustion and key evictions: audit memory usage, set missing TTLs, use compact data structures and shard with Redis Cluster where needed.
Symptoms
Signs your platform has this problem
If several of these sound familiar, the plan below is where we would start.
02
High memory fragmentation
A fragmentation ratio well above 1, wasting RAM in unused blocks.
03
Blocking commands
KEYS * or large HGETALL calls stalling Redis's single command thread.
Remediation plan
How we fix it, step by step
Each phase ends with a measurement, so you can see what changed before the next one starts.
01
Memory analysis
Parsing RDB snapshots to find the key patterns that use the most memory.
02
TTLs on every cache key
Auditing application writes to make sure every cache key has an explicit expiry.
03
Compact data structures
Grouping small keys into hashes that Redis stores in compact listpack encoding.
04
Active defragmentation
Enabling activedefrag to reclaim fragmented memory while Redis runs.
Technical checklist
Remediation checklist
What we check before a change goes to production:
- Analyze an RDB snapshot to find the largest key prefixes
- Set a TTL on every ephemeral cache key
- Replace blocking KEYS * calls with SCAN
- Configure activedefrag yes and a deliberate maxmemory-policy
What we measure
We take a baseline first and report the same measurements after each change, from your own monitoring — evidence, not promised results.
- Memory used
- used_memory and fragmentation ratio, before and after
- Evictions
- evicted_keys per hour at peak
- p99 latency
- Command latency from your Redis monitoring
Related service
Custom software
Custom software for Indian SMEs and startups, built around your workflow with an agreed scope, review milestones, clear ownership and documented handover.
Explore Custom softwareQuestions
Questions about this remediation
Redis executes commands on a single thread. KEYS * walks every key in one blocking call, so all other requests wait until it finishes.
Redis stores small hashes, lists and sets in compact encodings (listpacks and intsets), which use far less memory per field than separate string keys, each with its own overhead.
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Want an engineer to look at this with you?
Send us the symptoms and any metrics you have. We'll reply within one business day, set up a call and agree what to measure before anything changes.