Quiz

2667 questions of the kind that actually get asked — in interviews, in architecture review boards, and by the person who has to run the thing at 3 AM. Every answer states the trade-off rather than the slogan, and says when the obvious choice is the wrong one.

All areas2667 Architecture Fundamentals81 Distributed Systems101 Data Architecture90 Cloud Architecture87 Networking86 API & Integration Architecture78 Reliability & Resilience88 Observability81 Performance & Capacity Engineering90 Security Architecture95 Cost Architecture & FinOps92 Business Architecture93 Architecture Communication91 Enterprise Architecture91 Legacy Modernization92 AI-Era Architecture86 Software Architecture & Engineering84 Architecture Patterns84 Architecture Decision-Making91 The Architect's Meta-Skills92 Delivery & Release Engineering93 Platform Engineering & Developer Experience92 Testing & Quality Architecture90 Data Platform Architecture88 Streaming & Real-Time Data93 Data Governance & Semantics81 Frontend & Experience Architecture91 Edge, Mobile & IoT88 Regulatory & Data Protection Architecture90 Assurance, Audit & Model Risk88

Difficulty Any beginner intermediate advanced

5 questions in Cardinality.

Quiz

A live-streaming platform of Twitch's shape needs usable latency quantiles for 300 API endpoints whose responses span 2 ms to 90 seconds. The current histograms use 12 fixed buckets topping out at 10 seconds and every p99 above that reads as the overflow bucket. Which change fits the problem?

A single deploy took down your monitoring platform. What happened, and how do you prevent a recurrence?

A team wants to debug failures nobody predicted, using wide high-cardinality events rather than pre-aggregated metrics. How does the storage design differ, and how must sampling preserve rare errors?

An observability platform ingests billions of telemetry events daily, and some customers attach dimensions with unbounded distinct values. How should ingestion, storage, indexing and query be designed so cost and latency stay manageable?

An observability platform ingests enormous telemetry volume, but a small number of dimensions create extreme cardinality. How should ingestion, aggregation, indexing, sampling, retention and storage tiers be designed so cost and query performance stay predictable?