I went straight to 'let's align all the teams and set up a war room' which in hindsight was probably too operational too fast.
Start by acknowledging the complexity and the need for a systematic, data-driven approach. Emphasize collaboration with other teams to gather information and align on a shared understanding of the problem. Then, describe a structured process: from defining the problem and gathering data to forming hypotheses, testing them, and implementing a fix, while ensuring communication and ownership.
Pro tip: Show that you balance urgency with rigor: while you drive towards a fix, you also invest in understanding the root cause to prevent recurrence. Mention using Amazon's mechanisms like Correction of Errors (COE) or operational reviews to drive systemic improvements.
Clearly articulate the performance decline: what metrics are affected, when it started, and its impact on customers and business. Establish a shared definition with all teams.
Collect relevant data (logs, metrics, traces) from all involved systems. Collaborate with teams to understand recent changes and form hypotheses about potential root causes.
Rank hypotheses by likelihood and impact. Design experiments or tests to validate or invalidate them, using a divide-and-conquer approach to isolate the cause.
Once root cause is identified, implement a fix, preferably with a rollback plan. Validate that performance is restored and monitor for any side effects.
Keep stakeholders informed throughout. After resolution, conduct a post-mortem to identify systemic improvements and prevent future occurrences.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.