Case Study Playbook

This page turns the individual case studies into a repeatable interview practice loop. Use it as the lens for every example in this section.

What to Extract From Every Case

  • The user action that starts the request.
  • The system component on the critical path.
  • The first bottleneck that appears at scale.
  • The data that must stay strongly consistent.
  • The data that can be cached, delayed, or reconstructed.

Common Patterns by Category

Feeds and Social Graphs

  • Twitter, Instagram, and Facebook Newsfeed all need a hybrid fan-out strategy.
  • Celebrity or high-fanout users usually force a read-time merge path.
  • Timeline ranking, caching, and deduplication matter as much as storage.

Location and Matching

  • Uber and Yelp both need geospatial indexing and locality-aware lookup.
  • Region-aware partitioning helps keep queries fast and failure domains small.
  • Real-time updates usually need TTLs, caches, and idempotent writes.

Media and Streaming

  • Netflix and YouTube both need encoding pipelines, manifests, and CDN delivery.
  • Storage is rarely the hardest part; delivery, adaptation, and resilience are.
  • Offline playback and multiple bitrates add extra state and metadata flows.
  • URL shorteners, paste tools, and typeahead systems lean on fast key lookups and strong cache behavior.
  • Search-like systems often need indexing, ranking, and freshness trade-offs.
  • Key generation, deduplication, and expiry are recurring design concerns.

Messaging and Collaboration

  • Messenger-style systems need presence, delivery guarantees, and ordering semantics.
  • WebSockets or long polling are usually discussed alongside push notifications.
  • Offline delivery and message reconciliation are the typical follow-up topics.

Framework Rules of Thumb to Reuse

  • Estimate QPS as requests per period divided by seconds in the period.
  • Use read/write ratios to sanity-check storage and cache pressure.
  • Treat the 80/20 rule as a practical cache sizing heuristic.
  • Estimate incoming and outgoing bandwidth separately.
  • Remember that retention windows can dominate long-term storage.

Interview Practice Checklist

  1. Start with requirements and explicitly name what is out of scope.
  2. Give a quick estimate before proposing technologies.
  3. Explain one data model choice and one caching choice.
  4. Walk through the main request flow end-to-end.
  5. Deep dive into the hardest component only.
  6. End with failure handling, monitoring, and scaling.

How to Study Efficiently

  • Read one case from each category, not all of them in one sitting.
  • Practice re-telling the design in your own words.
  • Compare two similar case studies to see which trade-offs repeat.
  • Ask how the design changes if traffic becomes 10x higher or much more skewed.
  • Use the same seven-step framework every time so your answers stay consistent.