Performance Debugging and Latency Investigation Questions

Finding the root cause of latency spikes: checking CPU/memory/disk/network utilization, profiling applications, querying slow logs, and identifying bottlenecks. Understanding the difference between resource exhaustion and an algorithmic problem. Using monitoring and tracing tools to narrow down where time is spent.

EasyTechnical

0 practiced

Compare the use-cases for strace and perf top when diagnosing latency issues on Linux. For each tool give one class of problem it helps reveal (e.g., blocking syscalls vs CPU hotspots) and describe a short workflow for using it safely on a production node.

HardTechnical

0 practiced

Lock contention is suspected to cause latency spikes in a multithreaded service. Describe how you would detect mutex contention and lock hold times using perf or lockstat, interpret sample output showing contention counters, and present two concrete refactoring options to reduce contention at the application level.

MediumTechnical

0 practiced

You're asked to instrument an existing microservice with OpenTelemetry. The team wants to add several new tags but is worried about high-cardinality label explosions. Propose a safe tagging strategy that preserves useful debugging information while preventing metric cardinality growth. Include examples of which tags to include, which to avoid, and alternatives like exemplars or histograms.

HardTechnical

0 practiced

You see correlated latency spikes across multiple regions. A common dependency is a managed DNS provider. Describe how you would triage to confirm the DNS provider is the cause, and outline mitigation steps (short-term and long-term) to reduce user impact and prevent future cross-region correlated outages.

EasyTechnical

0 practiced

Define tail latency and explain why monitoring tail percentiles (p99 and above) is critical for user-facing services. Provide two pragmatic techniques an SRE can apply to reduce tail latency for a web API, and briefly list the trade-offs of each.

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