For each scenario, first clarify the functional and non-functional requirements (e.g., data model, read/write patterns, consistency needs, latency and throughput targets, budget). Then propose a technology choice and systematically justify it by comparing alternatives across consistency, latency, throughput, cost, and operational complexity. Conclude with trade-offs and any mitigations.
Pro tip: Anchor your justification in Amazon's leadership principles: tie trade-offs to customer impact and long-term ownership, and explicitly state what you are optimizing for and what you are willing to sacrifice.
Ask questions to understand the scenario's data model, access patterns, consistency requirements, latency/throughput targets, and budget constraints. This ensures your choice is grounded in actual needs, not assumptions.
State your recommended infrastructure or tool clearly, and briefly explain how it fits the requirements. Avoid hedging; commit to a choice to demonstrate decisiveness.
Compare your choice against at least one alternative across consistency, latency, throughput, cost, and operational complexity. Explicitly state what you gain and what you give up.
Acknowledge potential downsides of your choice and describe how you would mitigate them (e.g., caching, sharding, fallback mechanisms). This shows operational maturity.
Recap why your choice is optimal for the given scenario, and invite feedback or further constraints. This ensures alignment and shows collaborative spirit.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.