Amazon Work Simulation: Purpose, Modules, and Design Decisions

Context and Assumptions

The Work Simulation is a timed, scenario-based assessment used in a software engineering hiring process. It blends situational judgment, product sense, and system design trade-offs. Because the original prompt references choices without listing them, this version includes concise, realistic options so the task is fully self-contained. Use the 1–5 effectiveness scale below when asked to rate options:

• 5 = Most effective
• 4 = Effective
• 3 = Mixed/acceptable
• 2 = Ineffective
• 1 = Harmful

Tasks

1. Purpose and Structure

• Explain the purpose of the Amazon Work Simulation and outline a plausible five-module structure relevant to a software engineer role.

2. Workplace Judgment (Situational Scenarios)

• Scenario: You discover late in the sprint that a critical dependency owned by another team will slip by two weeks, jeopardizing your committed release. Which actions are most effective? Rate each on the 1–5 scale and briefly justify. a) Quietly work overtime to try to hide the impact and maintain the original date. b) Immediately inform your manager and the PM with impact, options (de-scope, feature flag, phased rollout), and a revised plan. c) Escalate to the other team’s director, cc-ing senior leadership, requesting they re-prioritize to meet your date. d) Proactively implement a feature-flagged fallback and update stakeholders on a new date with clear trade-offs. e) Reprioritize your team’s backlog to pull forward unrelated high-impact items while the dependency lands.

3. Real-Time Voting (Voice Service) — Vote Storage Strategy

• Choose the most effective strategy and briefly justify. a) Single-AZ relational DB (RDS) table; one row per vote; synchronous writes. b) Redis cluster incrementing per-item counters; periodic batch writes to durable storage. c) Append-only event stream (e.g., Kinesis/Kafka) for all votes; serverless/stream processors aggregate to DynamoDB counters with idempotency and TTL for raw votes. d) Direct writes to S3 objects (one object per vote) with later batch aggregation.

4. SaaS Inventory Management — Next Design Actions from Emails

• You receive these emails:
  • Sales: “Pilot customers need multi-tenant support next month.”
  • Support: “Image uploads are slow; customers report timeouts during peak hours.”
  • Compliance: “We need immutable audit logs of inventory adjustments for 7 years.”
• From the candidate actions below, choose the best next three actions to start this week. a) Define and implement a tenant isolation model (tenant_id everywhere; per-tenant rate limits; secrets isolation). b) Buy more compute for the upload service; revisit architecture later. c) Introduce presigned URLs to S3 + CDN for uploads; async thumbnailing; backpressure on API. d) Create a product roadmap slide deck; schedule stakeholder review next month. e) Implement immutable, append-only audit logging (WORM storage or tamper-evident logs) with schema and retention.

5. Thumbnail Storage Options — Compare and Rate

• Rate each option (1–5) for scalability, cost, latency, complexity, and give an overall rating. a) Store thumbnails as BLOBs in a relational DB. b) Store images in S3; serve via CDN; DB stores object keys/URLs. c) Generate thumbnails on-the-fly with Lambda@Edge; cache at CDN; store originals in S3. d) Store images on an NFS/EFS mount shared by web servers.

6. Traffic-Video Service (Queued Ingestion) — Message Format Priorities

• Prioritize the following design actions for a robust message format: a) Use a binary serialization format with an explicit schema (e.g., Protocol Buffers or Avro). b) Include an envelope with message_id, schema_version, timestamp, payload_type, and checksum. c) Define backward/forward compatibility rules (reserved fields, optional fields, deprecation policy). d) Add compression and encryption-at-rest/in-flight; document cipher and key rotation. e) Implement end-to-end idempotency and deduplication using message_id.

7. Large Camera Messages Over Unreliable Networks — Approaches

• Recommend approaches to reliably send multi-hundred-MB video segments over flaky links from edge cameras to a central service.

8. Monitoring and Mitigating Message Loss — Resilience

• Suggest measures to detect, monitor, and mitigate message loss end-to-end for the traffic-video service.

9. High Availability — Global SaaS Inventory

• Propose strategies to achieve high availability (and clear RPO/RTO targets) for a globally launched inventory management system.