Quiz

2707 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 areas2707 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 Architecture96 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 Architecture98 Streaming & Real-Time Data93 Data Governance & Semantics91 Frontend & Experience Architecture91 Edge, Mobile & IoT88 Regulatory & Data Protection Architecture90 Assurance, Audit & Model Risk98

Difficulty Any beginner intermediate advanced

45 questions in Platform Engineering.

Quiz

A platform must choose how much of the underlying infrastructure to abstract. What decides the level?

A platform team must decide how much to abstract the underlying infrastructure. What goes wrong at each extreme, and how do you choose?

An internal platform must decide how much of the underlying infrastructure to hide. What determines the right abstraction level, and what happens at each extreme?

Your platform abstracts Kubernetes entirely — teams write a short manifest and everything is generated. Now every production incident escalates to the platform team. What is happening?

A Kubernetes platform shows GPU utilisation below 40% because jobs request whole nodes. How should bin packing, gang scheduling, preemption, partitioning and queue-based admission raise utilisation without harming priority jobs?

A Kubernetes upgrade to 1.24 removes a deprecated node label. Within minutes the cluster's pod network loses all routes and stays down for over five hours, and the configuration responsible is not in any repository. What kind of dependency is this, and how would you have found it beforehand?

A platform must decide between one large cluster and many small ones. What are the trade-offs?

How many Kubernetes clusters should an organisation run, and what decides the boundaries?

How should compute clusters be structured for a platform running many teams' workloads with very different profiles?

Your platform team of five spends nearly all its capacity upgrading control planes across 38 Kubernetes clusters. How did this happen and how do you fix it?

An interviewer gives you this - "Every service has to propagate W3C trace context. You have 200 services across 6 languages and no authority to mandate anything. Get me to full coverage, and tell me how you would know you got there." Walk through it.

When should a platform prevent an action automatically, and when should it require a human decision?