Performance Fundamentals and Troubleshooting Questions

Core skills for identifying, diagnosing, and resolving general performance problems across applications and systems. Topics include establishing baselines and metrics, using monitoring and profiling tools to determine whether issues are CPU bound, memory bound, input output bound, or network bound, and applying systematic troubleshooting workflows. Candidates should be able to prioritize fixes, recommend temporary mitigations and long term solutions, and explain when to escalate to specialists. This canonical topic covers general performance awareness, common diagnostic tools, and basic remediation approaches for slow systems and resource exhaustion.

EasyTechnical

61 practiced

You have the following log snippet from a backend service:

[2025-06-01T12:34:10Z] WARN request_id=abc123 duration_ms=1200 upstream=database timeout_ms=1000[2025-06-01T12:34:11Z] WARN request_id=def456 duration_ms=1400 upstream=cache timeout_ms=500

What immediate conclusions can you draw about the type of performance problem, and what next steps would you take to validate and prioritize fixes?

HardSystem Design

62 practiced

Design an end-to-end tracing and logging strategy to speed up performance debugging for a microservices environment of ~50 services. Address sampling decisions, how to correlate logs and traces, and how to avoid overwhelming storage/ingest costs.

EasyTechnical

69 practiced

Write a Python function that parses a log file of HTTP request durations and returns the p50, p95, and p99 latency in milliseconds. Input: a newline-delimited file where each line is: "timestamp request_id duration_ms". Assume file fits in memory. Provide function signature: def percentiles(file_path: str) -> Dict[str, float].

MediumTechnical

75 practiced

You are creating a performance run for a database-backed API. Propose a set of load-test scenarios (3-5) that will surface common backend bottlenecks, including the traffic profile, dataset size, and success criteria for each scenario.

MediumTechnical

73 practiced

Write a Python (3.x) script that reads a stream of timestamped request counts and outputs the per-minute request rate averaged over a sliding 5-minute window. Input is newline-delimited JSON objects: {"ts": 1670000000, "count": 12}. Provide clear assumptions about ordering and clock skew.

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