System Resource and Input Output Optimization Questions
Techniques for managing system resources and optimizing input output including memory management, buffer and cache tuning, storage tiering and device selection, disk access patterns and throughput trade offs, central processing unit utilization, contention resolution, and diagnosing resource bottlenecks. Candidates should discuss monitoring and observability, trade offs between latency and throughput, caching strategies, memory pooling and fragmentation mitigation, and platform specific constraints when optimizing resource usage.
HardTechnical
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Explain why swapping (paging to disk) is particularly harmful for latency-sensitive services and list techniques to avoid swap-induced latency: strict memory limits, overcommit tuning, mlock, cgroups settings, memory reservation, admission control, and application-level fallbacks.
HardSystem Design
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Design the storage layer for a time-series database that must ingest 500k writes/sec and support low-latency queries over recent hours. Discuss on-disk layout (LSM vs B-tree), WAL design, compaction strategy, compression, memory and cache usage, and storage tiering between SSD and HDD.
MediumSystem Design
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Design an end-to-end latency measurement strategy to capture tail latencies across microservices. Include where to instrument (client, server ingress, service boundaries), sampling vs full-trace trade-offs, aggregation logic, SLO definitions, alerting thresholds, and approaches to minimize overhead while preserving signal.
MediumTechnical
0 practiced
Compare O_DIRECT (direct I/O) and fsync-related durability semantics. How do they interact with filesystem buffering and device write caches (battery-backed or volatile), and what are the performance and correctness trade-offs for database systems?
MediumTechnical
0 practiced
A Kubernetes pod running a latency-sensitive service is being OOMKilled intermittently. Describe a step-by-step diagnostic approach (kubectl events, metrics, heap/profile dumps, sidecars) and remediation options (right-sizing, memory limits and requests, QoS classes, eviction tuning, and potential code fixes).
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