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Incident Investigation, Root Cause Analysis, and Postmortems Questions

Covers the discipline of investigating and learning from production and technical incidents: forming and testing hypotheses, gathering and validating evidence, applying short-term mitigations versus long-term fixes, coordinating across teams during the incident, and running the postmortem or root cause analysis afterward. Candidates should describe the troubleshooting or investigative approach used, obstacles encountered, how mitigation and long-term remediation were sequenced, and the concrete process or system changes that resulted. Applies to incidents in software systems, ML/AI models and pipelines, infrastructure, and security findings.

MediumSystem Design
26 practiced
Design an automated runbook execution system that detects known incident signatures and runs remediation steps safely. Requirements: idempotent playbooks, role-based approvals, audit logging, scoped canary execution, and a staging validation pipeline. Describe architecture components, safety controls, versioning, and how you validate and test playbooks before production execution.
EasyTechnical
31 practiced
Explain what a blameless postmortem is and list the core sections it should contain (timeline, impact, root cause, contributing factors, corrective actions with owners, verification criteria). As an SRE, what measurable outcomes do you expect from postmortems and how do you ensure action items are tracked to completion?
EasyBehavioral
30 practiced
Tell me about a time you investigated a production outage. Describe the troubleshooting approach you used: how you generated hypotheses, tests you ran, data sources consulted, obstacles encountered, short-term mitigations versus long-term fixes, cross-team coordination, and the concrete improvements you implemented after the incident. Structure your answer (STAR) and focus on learning.
MediumTechnical
33 practiced
Implement a rate-limited alert deduplicator in Go or Python. Input: a stream of alert events with fields timestamp, signature, and severity. Behavior: suppress duplicate signatures within a sliding window W, emit a summary every X minutes with counts, keep memory bounded, and ensure thread-safety or concurrency control. Describe data structures and concurrency model.
HardBehavioral
32 practiced
Describe a time you made a decision during an incident that later proved to be wrong and caused additional impact. Explain how you owned the mistake, communicated with affected stakeholders, what you learned, and the concrete process or technical changes you implemented to avoid repetition. Be specific about follow-through and verification.

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