This section is not a gallery of pretty diagrams. It is a training ground for architectural judgment under different kinds of pressure: latency, consistency, cost, and product constraints.
The chapter helps turn the case list into a route: which problems sharpen edge and control-plane thinking, which build data-flow intuition, and which train correctness under concurrency and peak load.
For interviews and design reviews, it provides a stable case-solving vocabulary: framing, invariants, critical path, trade-offs, and evolution.
Coverage
This chapter maps the case-study domain and gives a practical route through all case categories.
Prioritization
Prioritize cases by risk profile: latency, consistency, throughput, and operating cost.
Transferability
The section is designed to transfer architectural patterns across different domains.
Interview Focus
Practice is aligned to a structured answer: framing, architecture, trade-offs, evolution.
Related chapter
Interview Approaches
A 7-step framework for working with system design problems.
This part is a practical unit on System Design. Now it already contains 30 full-fledged case tasks: from infrastructure primitives to product systems with a large number of dependencies and scenarios. The purpose of this section is to learn how to identify requirements, select architectural primitives, make informed trade-offs, and explain the evolution of the solution as the load grows.
If you go through the section sequentially, it builds a practical engineering habit: frame the problem and risks first, then architecture and deep dive, then growth and operational implications.
Coverage breadth
30 cases span infrastructure primitives, product scenarios, data flows, and transaction-heavy domains.
Depth of reasoning
Each case trains explicit trade-off articulation, risk framing, and solution evolution under growth.
Practical focus
The section mirrors real engineering workflow: requirement framing, NFR definition, and operational decisions.
Interview readiness
The path helps you keep structure under time pressure and defend architecture choices clearly.
How To Work Through The Section In 4 Phases
Core infrastructure primitives
Phase 1Start with Rate Limiter, API Gateway, Object Storage, and CDN to build strong design fundamentals.
Product and domain-heavy systems
Phase 2Then add booking, real-time, search, recommendation, and fintech flows with richer constraints.
Trade-off and reliability drills
Phase 3In every solution, explicitly cover SLA/SLO, bottlenecks, operating cost, and failure risks.
Timed interview simulation
Phase 4Solve cases under strict timing and keep a stable structure: framing -> design -> deep dive -> evolution.
Scale and coverage
Total in parts
30 cases
From basic infrastructure tasks to domain-specific product systems.
Infrastructure cases
11 tasks
Gateway, storage, CDN, limiter and other universal building blocks.
Product cases
19 problems
Marketplace, real-time, search, fintech, communications and geoservices.
Focus of training
NFR + trade-offs
Latency, throughput, consistency, availability, reliability and cost.
Case catalog
Infrastructure tasks
Fundamental services and platform components that are found in any system.
Product cases
Domain-specific tasks where user scenarios, business constraints and complex data flows are important.
Marketplace and bookings
Content and communications
Platforms and search
Fintech and transactions
Diversity Matrix: What exactly are you training?
Latency and real-time scenarios
Tasks where low-latency paths, fan-out, push mechanisms and predictable response time are critical.
Data-intensive and indexing
Ingestion flows, deduplication, indexing, ranking and high throughput requirements.
Storage, durability and delivery
Scenarios with metadata/data split, replication, fault tolerance and data distribution.
Transactions and Business Correctness
Cases where consistency boundaries, idempotency, anti-fraud and the correct state of orders are important.
Recommended training trajectories
Interview sprint (7-10 days)
A quick route to cover basic patterns and typical interview questions.
Platform / infrastructure focus
For platform and backend engineers: storage, data paths, resilience and control plane.
Product systems focus
For designing consumer products with a large number of user scenarios.
Key trade-offs in case solving
Answer speed vs reasoning quality
A quick high-level answer is useful, but without explicit assumptions and trade-offs the depth of engineering thinking is unclear.
Reusable patterns vs domain context
The same architecture building blocks behave differently in fintech, real-time and search due to different risk and SLO profiles.
Technical optimality vs operating cost
An elegant design may still be too expensive in support, on-call load and long-term operational ownership.
Deep dive depth vs end-to-end coverage
One strong deep dive is essential, but you still need a coherent end-to-end picture: data flow, bottlenecks, evolution and risks.
Why infrastructure first, then business
The order is structured as a learning path: first, universal primitives, then their application in products with more complex scenarios and domain restrictions.
1. Basic blocks
Rate limiter, gateway, storage and CDN form the foundation - without them, business systems will not scale.
2. Pattern combination
Using product tasks, we learn to combine cache, queues, sharding, consistency and degradation modes.
3. Real restrictions
Domain cases add UX, SLA, anti-fraud, compliance and cost constraints - this is closer to real work.
How to work with tasks
- First, clarify the requirements and specify the assumptions.
- Highlight the key NFRs: latency, throughput, consistency, availability and cost.
- Build a high-level architecture and identify critical components.
- Make a deep dive into the most difficult place and explain the trade-offs.
- Talk through the evolution: from MVP to scaling and operational support.
If you need a reference framework, take a look Design principles for scalable systems And Interview Approaches.
For additional hands-on practice on interview-style problem framing and depth, use System Design Primer (problem set) and High Scalability.
How to know the section is improving your skill
- You consistently fit the interview timebox while keeping response structure stable.
- You can explain 2-3 alternatives and justify why the selected approach fits this exact context.
- In each case you name SLO/NFR explicitly and map them to concrete architecture decisions.
- You can describe an evolution plan for 10x and 100x growth without hand-waving.
How to lock in case-study progress
Common pitfalls
Recommendations
Related chapters
- System Design Primer (short summary) - acts as an external problem bank and checklist source to extend practice beyond the local case catalog.
- A/B Testing platform - trains experiment data engineering: event ingestion, metric quality and statistical correctness.
- Airbnb - shows multi-domain product complexity: search, booking, ranking and anti-fraud in one architecture.
- API Gateway - covers foundational edge responsibilities: routing, auth, rate limiting and observability.
- Content Delivery Network (CDN) - adds practical latency/throughput trade-offs for global content delivery and caching.
- Chat System - strengthens real-time design skills around latency competition, fan-out and offline delivery paths.
- Distributed File System (GFS/HDFS) - deepens storage architecture reasoning: metadata/data split, replication strategy and recovery behavior.
- Google Maps / Proximity Service - introduces geospatial search and spatial indexing as a distinct class of design challenges.
- Hotel reservation system - focuses on transactional correctness and idempotency for booking-critical user flows.
- Interplanetary Distributed Computing System - extends system design thinking to extreme constraints: high latency, autonomous nodes and eventual sync.
- Feature Store & Model Serving - adds practice in offline/online parity, point-in-time correctness, and training-serving skew guardrails.
- ML Ops Pipeline - adds a dedicated AI/ML case class: feature pipelines, model rollout safety, drift monitoring, and operational guardrails.