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Interview Question
An application shows sudden latency spikes due to cloud storage IOPS limits being hit. How do you confirm and fix?
Key Points to Cover
- Measure disk latency/IOPS metrics from cloud provider
- Confirm correlation between QPS and throttling events
- Redistribute load or shard data across volumes
- Upgrade to higher IOPS tier or provisioned IOPS
- Introduce caching for hot paths
Evaluation Rubric
Confirms IOPS bottleneck with metrics30% weight
Correlates with workload patterns30% weight
Suggests scaling/caching strategies20% weight
Proposes monitoring and tiering20% weight
Hints
- 💡Burst balance exhaustion is common on gp2 volumes.
Common Pitfalls to Avoid
- ⚠️Assuming the issue is solely application-related without verifying storage metrics first.
- ⚠️Not checking for cloud provider-specific throttling indicators, focusing only on raw IOPS.
- ⚠️Failing to correlate application QPS/IOPS demand with the actual storage limits.
- ⚠️Implementing solutions without understanding the underlying data access patterns (e.g., read-heavy vs. write-heavy).
- ⚠️Not considering application-level optimizations as a complementary fix to storage-level adjustments.
Potential Follow-up Questions
- ❓When to use provisioned IOPS?
- ❓What caching layers help?
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