Performance Engineering and Cost Optimization Questions

Engineering practices and trade offs for meeting performance objectives while controlling operational cost. Topics include setting latency and throughput targets and latency budgets; benchmarking profiling and tuning across application database and infrastructure layers; memory compute serialization and batching optimizations; asynchronous processing and workload shaping; capacity estimation and right sizing for compute and storage to reduce cost; understanding cost drivers in cloud environments including network egress and storage tiering; trade offs between real time and batch processing; and monitoring to detect and prevent performance regressions. Candidates should describe measurement driven approaches to optimization and be able to justify trade offs between cost complexity and user experience.

MediumSystem Design

60 practiced

Autoscaling is causing frequent instance churn and occasional cold-start latency spikes. As PM, propose policy changes and instrumentation you would ask engineering to implement to reduce cost while ensuring user experience is acceptable. Explain how you would validate improvements and what metrics you would include on your dashboard.

MediumTechnical

50 practiced

You are evaluating a proposal to place a CDN in front of several API endpoints. List which types of endpoints are good CDN candidates, describe cache key and invalidation strategies, estimate cost implications and cache hit rate assumptions you would require, and propose deployment and rollback criteria.

HardTechnical

61 practiced

Third-party payment gateway performance affects checkout latency. Design an approach to set performance expectations and error budgets for suppliers, including contract terms, technical SLAs, monitoring, and how you would escalate or mitigate when a vendor misses targets.

EasyTechnical

47 practiced

You have a proposed performance optimization that could reduce API latency by 25% but carries a small risk of introducing stale reads. Design an A/B test to validate the optimization before rollout: define the hypothesis, key metrics, sample size considerations, risk mitigations, and criteria for rollout or rollback.

EasyTechnical

50 practiced

A recent deploy caused a 10% increase in p95 API latency for a critical endpoint. As the PM, outline the first 6 steps you would take to investigate and coordinate a response across engineering, support, and customer success. Be specific about what data you would ask for and what decisions you might make in the first hour versus the first day.

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