Covers both technical and organizational strategies for growing capacity, capability, and throughput. On the technical side this includes designing and evolving system architecture to handle increased traffic and data, performance tuning, partitioning and sharding, caching, capacity planning, observability and monitoring, automation, and managing technical debt and trade offs. On the organizational side this includes growing engineering headcount, hiring and onboarding practices, structuring teams and layers of ownership, splitting teams, introducing platform or shared services, improving engineering processes and effectiveness, mentoring and capability building, and aligning metrics and incentives. Candidates should be able to discuss concrete examples, metrics used to measure success, trade offs considered, timelines, coordination between product and infrastructure, and lessons learned.
EasyTechnical
0 practiced
Define scalability in the context of both product and technical systems. Compare vertical scaling (bigger machines) with horizontal scaling (more machines) and explain, from a Product Manager perspective, when you would prefer one over the other. Discuss trade-offs including cost, failure domains, operational complexity, deployment velocity, and user experience, and give concrete examples such as scaling a public storefront versus a batch processing pipeline.
MediumTechnical
0 practiced
Your company plans to decompose a monolithic application into microservices to scale engineering and product velocity. As the PM leading the initiative, present a decomposition and migration plan: criteria for service boundaries, sequencing strategy (strangler pattern or big-bang), data ownership and APIs, testing and rollout approaches, impact on roadmap, and quantitative success metrics for velocity, reliability, and customer impact.
HardTechnical
0 practiced
Your core recommendation service becomes a throughput bottleneck during peak season but drives most revenue. You have one quarter to scale throughput by 5x without materially degrading personalization quality. As Product Manager, propose a phased plan: immediate mitigations to reduce pain, architectural approaches (edge inference, caching, feature precomputation), hiring or contracting needs, testing and validation strategy, rollback plans, and KPIs to balance quality and latency.
EasyTechnical
0 practiced
List the core pillars of observability (metrics, logs, traces) and explain why each is important when planning for growth. As a Product Manager, describe the dashboards and alerts you would expect to see within 24 hours following a traffic spike, what thresholds would trigger mitigation or rollback, and how you would use those signals to prioritize next steps.
EasyTechnical
0 practiced
Explain the CAP theorem (consistency, availability, partition tolerance) in plain language suitable for cross-functional stakeholders. Provide two product-level examples where a Product Manager would favor consistency over availability and two examples where availability over consistency makes more sense. In each case, describe the business drivers and the user experience implications.
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