Advanced Debugging and Root Cause Analysis Questions
Systematic approaches to complex debugging scenarios: intermittent failures, race conditions, environment-dependent issues, infrastructure problems. Using logs, metrics, and instrumentation effectively. Differentiating between automation issues, environment issues, and application defects. Experience with advanced debugging tools and techniques.
EasyTechnical
0 practiced
Write a bash script or one-liner (using tools like jq, awk, or sed) that consumes newline-delimited JSON logs from stdin where each object has fields: timestamp (ISO8601), service, level. The script should output per-minute ERROR counts for service 'auth-service' and tolerate out-of-order timestamps within a 2-minute window.
HardTechnical
0 practiced
In a Kubernetes cluster pods are randomly evicted with no clear events shown in the application logs. Describe a deep-dive: how to inspect kubelet logs, node dmesg/kernel logs, cgroup memory/cpu stats, eviction annotations, OOM-killer logs, scheduler decisions, and potential CSI/storage or taint issues. Provide specific kubectl/host commands you would run.
HardSystem Design
0 practiced
Design an automated RCA assistant that consumes logs, metrics, and traces and suggests likely root causes for incidents based on historical incidents. Describe the system architecture, data labeling strategy, feature extraction, model choices, how to surface ranked hypotheses to engineers, and how to evaluate and iterate the system.
HardSystem Design
0 practiced
Design a strategy to prevent and debug schema-evolution issues that cause silent deserialization errors across services using message formats like Protobuf or Avro. Cover schema registry use, compatibility rules (backward/forward), consumer-driven contracts, CI checks, and runtime fallback strategies to detect and mitigate incompatibilities.
MediumTechnical
0 practiced
Explain how to collect and interpret flamegraphs (using perf/FlameGraph or pprof) for a Linux service in production. Discuss safety and overhead considerations, symbolization, sampling frequency trade-offs, and how flamegraphs help prioritize work compared to micro-optimizations.
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