Performance Optimization and Latency Engineering Questions

Covers systematic approaches to measuring and improving system performance and latency at architecture and code levels. Topics include profiling and tracing to find where time is actually spent, forming and testing hypotheses, optimizing critical paths, and validating improvements with measurable metrics. Candidates should be able to distinguish central processing unit bound work from input output bound work, analyze latency versus throughput trade offs, evaluate where caching and content delivery networks help or hurt, recognize database and network constraints, and propose strategies such as query optimization, asynchronous processing patterns, resource pooling, and load balancing. Also includes performance testing methodologies, reasoning about trade offs and risks, and describing end to end optimisation projects and their business impact.

HardTechnical

73 practiced

Implement a simplified lock-free single-producer single-consumer ring buffer in C or C++ to pass small messages between threads with minimal latency. Describe the memory ordering guarantees you rely on, how you avoid false sharing, and how you would test correctness under contention.

EasyTechnical

52 practiced

How do you determine whether a production process is CPU-bound or I/O-bound? Describe specific tools, commands, and tracing signals you would use (for Linux and common cloud environments), what signals you'd look for, and how you'd present findings to non-engineering stakeholders.

MediumTechnical

52 practiced

Explain backpressure in distributed systems and list concrete techniques to implement it between microservices. Cover bounded queues, client-side throttling, circuit breakers, rate-limiting, graceful degradation, and metrics you would use to detect the need for backpressure.

MediumTechnical

70 practiced

Compare sampling profilers and instrumentation/tracing for performance analysis in production. Explain overhead trade-offs, granularity differences, accuracy implications, and scenarios where you would prefer sampling over instrumentation or vice versa.

EasyTechnical

67 practiced

Define p50, p95, p99 and tail latency. Explain why p95/p99 are often more important than average latency in user-facing services, give concrete business-impact examples, and describe how you'd set SLOs using percentiles.

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