Amazon·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Jul 2026

Summary

Amazon system design round focused entirely on low-level infrastructure ownership. One question, lots of follow-ups, and they clearly wanted real war stories not textbook answers.

Questions Asked (1)

Walk me through a time you owned a storage, distributed systems, or infrastructure component. What was the component, what reliability and performance targets did it have, and describe a specific hard problem you ran into and how you resolved it end to end.

System DesignRoot Cause AnalysisTechnical Trade-offs

Author's notes

This question sounds like a standard behavioral but it really isn't.

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AI HintsAI Generated

Suggested Approach

Use the STAR method to structure your answer, focusing on a specific component you owned and a hard problem you solved. Clearly state the component's reliability and performance targets, then dive deep into the problem, your root cause analysis, and the end-to-end resolution. Emphasize your ownership, technical depth, and the impact of your solution.

Pro tip: Quantify the impact of your solution with metrics (e.g., reduced latency by X%, improved availability to 99.99%) and highlight trade-offs you considered, showing you understand the bigger picture.

1. Set the Context

Briefly describe the component you owned, its role in the larger system, and its scale (e.g., requests per second, data volume). Mention the reliability and performance targets (SLOs/SLAs) it had to meet.

2. Describe the Hard Problem

Explain a specific challenging issue you encountered, such as a subtle bug, performance bottleneck, or scalability limit. Detail its impact on users or the business.

3. Root Cause Analysis

Walk through your investigation process: how you gathered data, formed hypotheses, and identified the root cause. Mention tools or techniques used (e.g., profiling, logs, metrics).

4. Solution and Implementation

Describe the solution you designed and implemented, including any trade-offs considered. Explain how you validated the fix and rolled it out safely (e.g., canary deployment, A/B test).

5. Results and Learnings

Quantify the outcome (e.g., latency reduction, cost savings) and share what you learned or how you improved processes to prevent similar issues.

Key Points to Mention

Specific reliability and performance targets (e.g., 99.99% availability, p99 latency < 100ms)
Scale of the component (e.g., QPS, data size, number of nodes)
Root cause analysis techniques (e.g., 5 Whys, fishbone diagram, debugging tools)
Trade-offs made in the solution (e.g., consistency vs. availability, cost vs. performance)
Metrics used to measure success and impact of the fix
Ownership and end-to-end responsibility, including monitoring and post-mortem

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.