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2948 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 areas2948 Architecture Fundamentals91 Distributed Systems101 Data Architecture90 Cloud Architecture87 Networking96 API & Integration Architecture87 Reliability & Resilience99 Observability92 Performance & Capacity Engineering100 Security Architecture105 Cost Architecture & FinOps102 Business Architecture103 Architecture Communication102 Enterprise Architecture100 Legacy Modernization102 AI-Era Architecture106 Software Architecture & Engineering93 Architecture Patterns94 Architecture Decision-Making101 The Architect's Meta-Skills102 Delivery & Release Engineering103 Platform Engineering & Developer Experience102 Testing & Quality Architecture102 Data Platform Architecture98 Streaming & Real-Time Data103 Data Governance & Semantics91 Frontend & Experience Architecture101 Edge, Mobile & IoT98 Regulatory & Data Protection Architecture99 Assurance, Audit & Model Risk98
Difficulty Any beginner intermediate advanced

6 questions in Vector Databases.

  1. Vector Databases advanced Multiple choice

    A multi-tenant assistant searches one HNSW index of 200M vectors and filters results to the requesting tenant. Large tenants are fine. For tenants with only a few thousand documents recall collapses and latency triples. Which change fixes it?

    3 min answer vector-databasehnswmulti-tenancyfiltering
  2. Vector Databases advanced Multiple choice

    A platform needs similarity search over a large and growing corpus. What decides between a dedicated vector database, a vector extension to an existing store, and a search engine with vector support?

    2 min answer vector-databaseoperational-costfilteringscale
  3. Vector Databases intermediate

    A team needs vector search. When is a dedicated vector database justified over adding vector search to an existing store?

    2 min answer replicatevector-searchdatastoresoperations
  4. Vector Databases intermediate

    A team wants a dedicated vector database for a RAG system over 200,000 documents. Is it necessary?

    2 min answer ragtechnology-selectionpragmatism
  5. Vector Databases intermediate

    A user uploads a policy document at 09:02 and it appears in the document list immediately. At 09:20 the assistant still says it cannot find anything on the subject. Error rates are flat and the ingest queue is empty. Where do you look first?

    2 min answer vector-databasesingestionread-after-writedead-letter
  6. Vector Databases advanced Multiple choice

    You must serve similarity search over 200 million embeddings of 1024 dimensions with an in-memory HNSW index. Which estimate and which lever are right?

    3 min answer vector searchhnswquantisationmemory estimation