One-line definitions, A-Z, each pointing at its owning note - the design angle, not the textbook one. Entries use Term::definition lines so the Ghost export renders every entry as a toggle card. Deliberately not tagged for spaced repetition: entries are reference, not review cards. Coverage proof lives in
Success: Elective complete All four AI Infrastructure sections (1-4) are written - your CCDE Practical Scenario 4. Notes are numbered section.NN in study order. The flagship is Fabric transport - Ethernet vs InfiniBand vs UEC. 1.0 AI/ML fundamentals & governance * AI-ML workloads and their infrastructure impact * Service
Success: Core blueprint complete All eight Core technology areas (1.0-8.0) are written. Notes are numbered area.NN in recommended study order (built up the stack). The CCDE Practical's first three scenarios draw from these; the fourth is your AI Infrastructure elective (AI Infrastructure - MOC). The
Important: The five lenses are HOW you read a scenario The technology notes (Core + AI Infrastructure) are the what; these five design domains are the how to think. In the Practical you reason about a single scenario through all five lenses at once, and each note links down into the
This is an Obsidian vault built to prepare for the CCDE v3.1 Practical exam, with the AI Infrastructure elective as the focus. It is a single-hub system: capture, visual review, and spaced repetition all live in Obsidian. No MindNode, no separate Anki app. Important: The exam tests judgment,
What this lens evaluates Whether the design serves the business - its priorities, risk appetite, economics, and obligations - before any technology is chosen. The Practical brief leads with business intent; this lens is how you convert that intent into requirements and constraints that bound every later decision. The questions it forces
What this lens evaluates Whether each plane of the network is designed to scale, converge, fail gracefully, and be operated - and whether day-2 operations (monitoring, change, automation) are designed in, not bolted on. This is one of the heaviest domains in the blueprint. The questions it forces * Control plane:
What this lens evaluates Whether the topology delivers resilience, scalability, modularity, and clean addressing, converges fast enough, and can migrate from today's state - the structural heart of the design, and one of the largest domains. The questions it forces * Is the topology hierarchical/modular with bounded failure domains?
What this lens evaluates Whether the network delivers the specific services and applications the business runs - with the right QoS, multicast, network services, and segmentation - to meet application SLAs. The network exists to carry services; this lens keeps the design application-driven. The questions it forces * What are the application
What this lens evaluates Whether security is woven through every layer of the design - identity, segmentation, perimeter, hardening, and compliance - rather than bolted on at the edge. Security is risk- and compliance-driven, and it touches every other lens. The questions it forces * What is the threat model and the
Warning: These are tempting wrong answers Each trap below looks reasonable and is often the offered option a candidate reaches for first. The CCDE-correct move is in the fix. These patterns are distilled from worked practice scenarios and generalised (and AI-updated) - they are answer-selection discipline, not new
In one line Different AI workloads - and above all training vs inference - stress infrastructure in very different ways, and that profile is what drives every fabric, compute, and storage decision in this elective. The workload spectrum Classic ML (often CPU, lighter) -> deep learning (GPU) -> LLM / GenAI (massive GPU