How to Fix Latency Spikes from Evicted Keys in Memorystore for Redis
You are managing a Memorystore for Redis cluster with standard tier (persistence disabled). The application experiences occasional latency spikes while performing SET operations. You observe that the 'evicted_keys' metric spikes during the spikes. What is the most effective solution?
Quick Answer
The answer is to increase the maximum memory size of the instance. When the evicted_keys metric spikes during SET operations, it signals that the Redis instance has hit its maxmemory limit and is aggressively evicting keys to free space for new writes, which directly causes the observed latency spikes. This scenario tests your understanding of Memorystore for Redis memory management under the Google Professional Cloud Database Engineer exam, where a common trap is to mistakenly tune the eviction policy instead of addressing the capacity shortage—changing the policy only shifts which keys are removed, not the underlying eviction overhead. A key memory tip is to remember that eviction itself is the latency culprit, not the policy; always scale memory first when evictions coincide with write spikes.
⚠ Common exam trap
Google Cloud often tests the misconception that changing the eviction policy (Option B) solves memory pressure, when in fact the policy only controls which keys are evicted, not whether eviction occurs at all.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the maximum memory size of the instance
The evicted_keys metric spikes during SET operations indicate that the Redis instance has reached its maxmemory limit and is evicting keys to accommodate new writes. Increasing the maximum memory size directly addresses the root cause by providing more headroom for data, reducing the need for eviction and the associated latency spikes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable AOF persistence with fsync every second
Why it's wrong here
Persistence increases write latency and doesn't prevent eviction.
- ✗
Change the maxmemory-policy to 'volatile-lru'
Why it's wrong here
Changing eviction policy doesn't solve insufficient memory.
- ✓
Increase the maximum memory size of the instance
Why this is correct
More memory reduces evictions, stabilizing write latency.
- ✗
Configure a read replica to offload read traffic
Why it's wrong here
Read replicas don't help with SET operations.
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1 more way this is tested on PCDE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A Cloud Memorystore for Redis instance used as a session store has a high eviction rate. Which configuration change can reduce evictions while maintaining performance?
medium- A.Enable persistence (RDB)
- B.Increase number of replicas
- C.Decrease timeout
- ✓ D.Set maxmemory-policy to allkeys-lru
Why D: Setting `maxmemory-policy` to `allkeys-lru` allows Redis to evict the least recently used keys across all keys when memory is full, which directly reduces eviction rates by ensuring that only the least active session data is removed. This maintains performance by keeping frequently accessed session keys in memory, which is critical for a session store where active sessions are repeatedly read and written.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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