Scaling Systems and Platforms Through Growth Questions

Describe experiences scaling systems, platforms, or services through significant growth phases. Examples: scaling from 1 million to 100 million users, migrating from monolith to microservices as organization grew, or building infrastructure to support 10x team growth. For each example: What was working before that stopped working at scale? What bottlenecks did you encounter? How did you identify and address them? What architectural changes were necessary? How did you sequence the work to minimize disruption? What did you learn? Discuss both technical and organizational scaling—they're intertwined.

MediumTechnical

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Sales asks whether you can support 1 million concurrent video streams for a proposed contract. What key architectural concerns would you raise (networking, encoding, CDN, storage, monitoring) and what data or benchmarks would you request to validate feasibility?

HardTechnical

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As a Solutions Architect, propose a governance model, metrics, and incentives to systematically reduce high-impact technical debt while preserving feature velocity during a period of rapid growth. Explain how you'd identify debt that most affects scaling, how to allocate time, and how to measure progress.

EasyTechnical

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Explain the difference between vertical scaling and horizontal scaling in the context of a web service experiencing increased user traffic. For each approach, give 2 concrete examples (infrastructure and application changes), list the main trade-offs (cost, operational complexity, statefulness, single point of failure), and describe which metrics you would monitor to decide which approach to choose.

MediumSystem Design

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Design a high-level architecture to scale a consumer web product from 1 million monthly users to 100 million users over two years. Requirements: peak concurrent users = 2% of total users, target tail-latency p99 < 300ms for API endpoints, multi-region for NA+EU, 99.95% availability. Provide components, data flow, and a migration sequencing plan that minimizes customer disruption.

EasyTechnical

0 practiced

List the common architectural and operational bottlenecks you would expect when an API platform grows 10x in traffic. Cover areas such as networking, compute, caching, service coupling, third-party dependencies, and organizational constraints. For each bottleneck, mention one practical diagnostic you would run to confirm it.

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