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

Senior
Jun 2026

Summary

Amazon system design round for a software engineering role. The question was deep and pretty niche, centered on low-level profiling infrastructure. Left feeling like I could've gone further on the aggregation side but the core design held up.

Questions Asked (1)

Q1

Design a profiler that reconstructs per-thread call stacks from instruction-register sampling events, handles inlined and tail-called functions, and aggregates hot stacks for reporting.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was to reach for a simple stack per thread, which is fine as a starting point, but the inlining part tripped me up.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a high-level architecture covering sampling, stack reconstruction, and aggregation. Dive into the algorithmic challenges of handling inlined and tail-called functions, and discuss trade-offs in data structures and performance.

Pro tip: Emphasize that accurate stack reconstruction requires combining runtime sampling with static binary analysis (e.g., DWARF debug info) to resolve inlining and tail calls, and that aggregation should use a space-efficient trie with incremental updates to handle high-frequency samples.

1. Clarify Requirements and Constraints

Ask about sampling frequency, overhead tolerance, supported platforms, and whether real-time or offline analysis is needed. Confirm the output format for hot stacks.

2. Design Sampling and Data Collection

Describe how to collect instruction pointers and thread IDs at regular intervals using OS timers or performance counters, ensuring minimal overhead and thread safety.

3. Reconstruct Call Stacks

Explain how to unwind stacks from sampled IPs, handling inlined functions via debug info and tail calls by analyzing control flow. Mention fallback strategies like frame pointers or DWARF CFI.

4. Aggregate and Report Hot Stacks

Propose a data structure (e.g., trie or hash map) to aggregate stack traces per thread, and describe how to compute and report the hottest stacks efficiently.

5. Discuss Trade-offs and Optimizations

Cover trade-offs between accuracy and overhead, memory usage, and sampling frequency. Suggest optimizations like sampling only on CPU cycles or using lock-free data structures.

Key Points to Mention

  • Use of DWARF debug information to resolve inlined functions and reconstruct logical call stacks.
  • Handling tail calls by analyzing control flow graphs or using compiler-generated metadata.
  • Thread-local buffers and lock-free data structures to minimize contention and overhead.
  • Aggregation using a trie (prefix tree) to share common stack prefixes and reduce memory.
  • Sampling techniques: hardware performance counters vs. OS timers, and their impact on accuracy.
  • Trade-offs between sampling frequency, overhead, and statistical significance of hot stacks.

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