The answer is to switch to the 'allkeys-lru' eviction policy. This is correct because the default 'volatile-lru' policy only evicts keys that have a TTL set, leaving hot keys without an expiration vulnerable to eviction when memory pressure arises. By switching to 'allkeys-lru', Redis considers all keys—including those without TTL—for eviction based on least-recently-used access, which helps retain frequently accessed hot keys and reduces cache misses. On the AWS Certified Developer Associate DVA-C02 exam, this question tests your understanding of how ElastiCache Redis manages memory under pressure and the trade-offs between eviction policies. A common trap is assuming that setting TTLs alone protects hot keys, but without 'allkeys-lru', keys lacking expiration can still be evicted first. Memory tip: think "all keys, all LRU" to remember that this policy protects your hottest data regardless of TTL.
DVA-C02 Troubleshooting and Optimization Practice Question
This DVA-C02 practice question tests your understanding of troubleshooting and optimization. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. A key principle to apply: redis eviction policies determine which keys are removed when memory limits are reached.. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer is troubleshooting an application that uses Amazon ElastiCache for Redis to cache database query results. The application experiences high latency during cache misses. The developer notices that frequently accessed keys (hot keys) are often missing from the cache, suggesting they are being evicted. Which action should the developer take to reduce cache misses for hot keys?
Why wrong: Adding nodes increases total memory but does not change how eviction selects keys; hot keys may still be evicted if not properly prioritized.
B
Switch to the 'allkeys-lru' eviction policy.
allkeys-lru evicts the least recently used keys from all keys, which tends to retain frequently used hot keys.
C
Disable the TTL on all cached keys.
Why wrong: Disabling TTL can cause the cache to fill with stale data and increase memory pressure, potentially worsening eviction of hot keys.
D
Increase the size of the cache cluster.
Why wrong: More memory can reduce eviction frequency, but if the eviction policy is not LRU-based, hot keys may still be evicted in favor of other keys.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Switch to the 'allkeys-lru' eviction policy.
Option B is correct because the 'allkeys-lru' eviction policy allows Redis to evict any key (including those with TTL) based on least-recently-used access, which helps retain frequently accessed hot keys. By default, ElastiCache for Redis uses the 'volatile-lru' policy, which only evicts keys with an expiration set, leaving hot keys without TTL vulnerable to eviction when memory pressure occurs. Switching to 'allkeys-lru' ensures that even keys without TTL can be considered for eviction, reducing the likelihood of hot keys being removed.
Key principle: Redis eviction policies determine which keys are removed when memory limits are reached.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Increase the number of cache nodes.
Why it's wrong here
Adding nodes increases total memory but does not change how eviction selects keys; hot keys may still be evicted if not properly prioritized.
✓
Switch to the 'allkeys-lru' eviction policy.
Why this is correct
allkeys-lru evicts the least recently used keys from all keys, which tends to retain frequently used hot keys.
Related concept
Redis eviction policies determine which keys are removed when memory limits are reached.
✗
Disable the TTL on all cached keys.
Why it's wrong here
Disabling TTL can cause the cache to fill with stale data and increase memory pressure, potentially worsening eviction of hot keys.
✗
Increase the size of the cache cluster.
Why it's wrong here
More memory can reduce eviction frequency, but if the eviction policy is not LRU-based, hot keys may still be evicted in favor of other keys.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume scaling up or out is the only solution for cache misses, overlooking that the eviction policy directly controls which keys are removed under memory pressure, and 'volatile-lru' by default excludes keys without TTL from eviction consideration.
Detailed technical explanation
How to think about this question
Under the hood, Redis uses an approximation of LRU (not exact LRU) to minimize overhead, sampling a small pool of keys (default 5) to evict. The 'allkeys-lru' policy treats all keys equally, while 'volatile-lru' only considers keys with an explicit TTL set. In real-world scenarios, hot keys often have no TTL because they are expected to stay cached indefinitely, making them prime candidates for eviction under 'volatile-lru' when memory fills up with other keys that do have TTL.
KKey Concepts to Remember
Redis eviction policies determine which keys are removed when memory limits are reached.
`allkeys-lru` evicts the least recently used keys from the entire dataset.
It is ideal for general caching scenarios where frequently accessed data should persist.
Frequent access updates a key's "recently used" status, making it less prone to `allkeys-lru` eviction.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Redis eviction policies determine which keys are removed when memory limits are reached.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Review redis eviction policies determine which keys are removed when memory limits are reached., then practise related DVA-C02 questions on the same topic to reinforce the concept.
Troubleshooting and Optimization — This question tests Troubleshooting and Optimization — Redis eviction policies determine which keys are removed when memory limits are reached..
What is the correct answer to this question?
The correct answer is: Switch to the 'allkeys-lru' eviction policy. — Option B is correct because the 'allkeys-lru' eviction policy allows Redis to evict any key (including those with TTL) based on least-recently-used access, which helps retain frequently accessed hot keys. By default, ElastiCache for Redis uses the 'volatile-lru' policy, which only evicts keys with an expiration set, leaving hot keys without TTL vulnerable to eviction when memory pressure occurs. Switching to 'allkeys-lru' ensures that even keys without TTL can be considered for eviction, reducing the likelihood of hot keys being removed.
What should I do if I get this DVA-C02 question wrong?
Review redis eviction policies determine which keys are removed when memory limits are reached., then practise related DVA-C02 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Redis eviction policies determine which keys are removed when memory limits are reached.
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