Terminology

2205 terms, tools, patterns and metrics an architect is expected to use precisely. Each one gets a short explanation of what it is, and — where it matters — what it is commonly confused with. Search filters as you type; the column headers sort.

All areas2205 Architecture Fundamentals77 Distributed Systems107 Data Architecture110 Cloud Architecture94 Networking88 API & Integration Architecture82 Reliability & Resilience75 Observability70 Performance & Capacity Engineering72 Security Architecture86 Cost Architecture & FinOps71 Business Architecture67 Architecture Communication67 Enterprise Architecture66 Legacy Modernization71 AI-Era Architecture69 Software Architecture & Engineering71 Architecture Patterns71 Architecture Decision-Making63 The Architect's Meta-Skills61 Delivery & Release Engineering66 Platform Engineering & Developer Experience70 Testing & Quality Architecture66 Data Platform Architecture64 Streaming & Real-Time Data69 Data Governance & Semantics69 Frontend & Experience Architecture66 Edge, Mobile & IoT68 Regulatory & Data Protection Architecture65 Assurance, Audit & Model Risk64

Kind Any concept794 practice734 pattern368 metric125 case-study77 tool62 protocol45

4 terms shown.

Term	Kind	Topic	What it is
Fan-Out Latency Amplification	concept	Tail Latency	The effect by which a request that depends on many parallel sub-requests is governed by the slowest of them, so rare slowness becomes common at the user level.
Tail Composition Effect Fan-Out Tail Amplification, Page-Level Tail	concept	Tail Latency	The multiplication that turns a small per-request slow rate into a large user-visible slow rate, because a single user action makes many requests and is only as fast as its slowest one.
Tail Latency Amplification Fan-out Tail, Slowest-Component Latency	concept	Tail Latency	A parallel fan-out completes when its slowest component does, so ordinary per-component tails combine into a much worse end-to-end tail.
Tail Latency Amplification	concept	Tail Latency	The effect where a request that fans out to many services experiences the worst case of all of them, making rare slowness common at the user level.