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

53 questions in Performance & Capacity.

Quiz

A marketplace's search page is slow. CPU is moderate, memory is fine, and the database reports healthy query times. How do you find the bottleneck?

A service's p99 latency has tripled over three months with no single obvious change. How do you investigate?

CPU, memory, disk and network all look healthy, and the service will not go faster. What are you looking for?

p99 latency on the booking endpoint jumped from 300 ms to 4 s at 09:00 today. Error rate is normal. Walk through your diagnosis.

A search platform adds a cache and sees only a small latency improvement. What are the likely reasons, and what should be measured?

What happens to your system if the entire cache tier is flushed at peak traffic?

Which caching failure appears only under load, and what are the fixes in order of deployability?

A compute platform must plan accelerator capacity where lead times are months, demand is uncertain, and jobs vary from minutes to weeks. How should the capacity model be built?

A game hosts a scheduled in-world event for 30 million concurrent players. How should matchmaking, instance allocation, pre-scaling, login queues and degradation be planned, and what is rehearsed?

A training cluster has 512 NVIDIA H100-class GPUs in 64 eight-GPU nodes and the scheduler reports 96 GPUs free. Roughly how much collective bandwidth per GPU does a new 64-GPU job get, and what should the capacity report say instead of "96 GPUs free"?

A platform must handle millions of concurrent connections per process cluster where most connections are idle most of the time. Which concurrency model fits, and what does the wrong choice cost?

A service holds a concurrency limit of 60 with a 50 ms mean service time and serves clients that give up after 2 seconds. Offered load triples. Where should the excess requests wait?