Enterprise Operations & Incident Management Topics
Large-scale operational practices for enterprise systems including major incident response, crisis leadership, enterprise-scale troubleshooting, business continuity planning, and recovery. Covers coordination across teams during high-severity incidents, forensic investigation, decision-making under pressure, post-incident processes, and resilience architecture. Distinct from Security & Compliance in its focus on operational coordination and recovery rather than preventive security.
Disaster Recovery Objectives and Methods
Covers the core goals and recovery approaches for recovering systems after a failure. Candidates should understand Recovery Time Objective which defines how quickly systems must be restored, and Recovery Point Objective which bounds acceptable data loss. Describe and compare recovery methods such as cold standby, warm standby, and hot standby including their cost, complexity, and expected recovery times. Discuss how to choose an approach based on business impact analysis, critical path dependencies, and cost versus risk trade offs. Explain runbooks and failover orchestration, automation of recovery procedures, validation and regular testing of recovery plans, metrics and monitoring for recovery readiness, and operational considerations for maintaining standby systems and exercising failover in production-like tests.
Alerting Strategy and Incident Response
Design alerting strategies and incident response practices that turn observability signals into actionable operations. Topics include alert design and classification, threshold versus anomaly detection, preventing alert fatigue, escalation and on call flow, runbook and playbook design, integrating alerts with incident management, post incident review and blameless postmortems, and how monitoring and observability feed incident detection and mean time to resolution improvements. Includes designing alerts for different domains and thinking through what runbooks and context to provide to responders.
Complex System Troubleshooting and Incident Diagnosis
Tests systems thinking and approaches for diagnosing problems that span multiple components services layers or domains and present multiple related symptoms. Candidates should show how they map interdependencies prioritize which symptoms to address first generate and test hypotheses correlate telemetry across logs metrics and traces and distinguish root causes from secondary effects. The topic includes using instrumentation and monitoring to isolate failures reproducing issues in controlled environments understanding cascading failures and failure modes across networking storage database and application layers and applying mitigations rollbacks or fixes while minimizing user impact. Candidates should also describe incident communication documentation and post incident analysis to prevent recurrence.
Learning From Failure and Continuous Improvement
This topic focuses on how candidates reflect on mistakes, failed experiments, and suboptimal outcomes and convert those experiences into durable learning and process improvement. Interviewers evaluate ability to describe what went wrong, perform root cause analysis, execute immediate remediation and course correction, run blameless postmortems or retrospectives, and implement systemic changes such as new guardrails, tests, or documentation. The scope includes individual growth habits and team level practices for institutionalizing lessons, measuring the impact of changes, promoting psychological safety for experimentation, and mentoring others to apply learned improvements. Candidates should demonstrate humility, data driven diagnosis, iterative experimentation, and examples showing how failure led to measurable better outcomes at project or organizational scale.
Incident Response and Troubleshooting
Approach to diagnosing and resolving production incidents, outages, and critical failures under time pressure. Covers systematic triage, identifying root causes, maintaining service availability, coordinating with stakeholders, prioritizing safety and mitigation steps, postmortem practices, and learning from incidents to prevent recurrence. Interviewers expect examples showing technical troubleshooting, communication during crises, decision making under pressure, and follow through in remediation and documentation.
Production Troubleshooting and Incident Response
Emphasizes diagnosing intermittent and performance related issues in live production environments while preserving availability and minimizing user impact. Candidates should describe safe investigative actions and remediation strategies such as runbooks feature flags canary or staged rollouts hotfixes and coordinated rollbacks as well as prioritization under time pressure and communication with stakeholders and on call teams. Technical techniques include network packet capture and analysis kernel level inspection application performance profiling thread and memory analysis and tracing request flows across distributed systems. The topic also covers incident response workflows alerting practices post incident hygiene and choosing low risk diagnostic steps that avoid causing additional disruption in production.
High Impact Accomplishment
Prepare 1-2 specific examples of major technical support initiatives or improvements you've led that had significant business impact. Include metrics, scope, complexity, and your specific leadership role. Examples might include: designing a new support architecture, scaling support to handle 10x volume, leading infrastructure modernization, or implementing a documentation system that reduced resolution time.
Technical Problem Solving and Ownership
Covers the ability to diagnose, triage, and resolve complex technical problems end to end while demonstrating personal ownership. Candidates should show deep technical reasoning about system architecture, integration complexity, data migration considerations, and custom configuration trade offs. Expect discussion of root cause analysis, diagnostic techniques, reproducible debugging, and risk mitigation strategies. Candidates should be able to explain design trade offs, propose practical solutions, assess business impact, and describe collaboration with stakeholders and cross functional teams. Emphasis should be placed on concrete actions the candidate took, how they prioritized options, and the measurable results and lessons learned.
Handling Mistakes and Recovering Gracefully
Share a mistake in database management (e.g., wrong script deployed to production, performance not improving as expected, security oversight discovered). Explain what went wrong, how you recovered, and what you learned. Show accountability and problem-solving under pressure.