Blueprint coverage map
Every line of the Core Technology List, the AI Infrastructure Technology List, and the Learning Matrix v1.1 AI-sheet deltas, mapped to the note(s) that own it. This is the honest answer to "is the vault blueprint-complete?" - updated whenever a gap closes. See also Glossary.
Core Technology List
1.0 Transport technologies
- 1.1 Ethernet -> Ethernet as transport
- 1.2 CWDM/DWDM -> Optical transport - CWDM vs DWDM
- 1.3 Frame Relay (migration only) -> WAN and last-mile transport selection, Transport resiliency, diversity, and migration
- 1.4 Cellular and broadband as transport -> WAN and last-mile transport selection
- 1.5 Wireless as transport -> WAN and last-mile transport selection (design depth in Core 7)
- 1.6 Physical mediums -> Physical mediums - fiber and copper
2.0 Layer 2 control plane
- 2.1 Physical media considerations (down detection, interface convergence) -> Physical media and Layer 2 convergence
- 2.2 Loop detection / loop-free mechanisms (STP types + tuning, multipath, clustering) -> Spanning Tree - types, tuning, and loop mitigation, Layer 2 multipath and switch clustering, Layer 2 design fundamentals
- 2.3 Loop detection and mitigation -> Spanning Tree - types, tuning, and loop mitigation
- 2.4 Multicast switching (IGMP/MLD, snooping, querier) -> Layer 2 multicast - IGMP and MLD snooping
- 2.5 Fault isolation and resiliency (fate sharing, redundancy, virtualization, segmentation) -> Layer 2 fault isolation and resiliency, Infrastructure segmentation
3.0 Layer 3 control plane
- 3.1 Hierarchy, topologies, topology hiding -> Network hierarchy and topologies
- 3.2 Unicast routing protocols (neighbors, loop-free paths, flooding, scalability, policy, redistribution, security, aggregation) -> IGP selection - OSPF vs IS-IS vs EIGRP, BGP in enterprise design, Redistribution and route manipulation, Securing routing protocols, Route aggregation and summarization
- 3.3 Fast convergence (protocols, timers, topologies, LFA) -> Fast convergence techniques
- 3.4 Factors affecting convergence (recursion, microloops, microbursts, physical failures) -> Factors affecting convergence, Buffering, microbursts, and congestion signaling
- 3.5 Route aggregation (leaking, more-specifics, location) -> Route aggregation and summarization
- 3.6 Fault isolation and resiliency -> Network hierarchy and topologies, Factors affecting convergence
- 3.7 Metric-based traffic flow, third-party next hop -> Metric-based traffic engineering
- 3.8 Generic routing and addressing (PBR, NAT, subnetting, RIB-FIB) -> Generic routing and addressing - PBR, NAT, RIB-FIB, IPv6 design and migration
- 3.9 Multicast routing (concepts, inter/intradomain, MSDP/anycast, PIM flavors, RP) -> Multicast routing design - PIM, RP, MSDP
4.0 Data plane transport protocols
- 4.1 Areas of application and deployment -> Transport protocols overview - TCP, UDP, QUIC
- 4.2 Characteristics and properties -> TCP behavior and the network, MTU, fragmentation, and PMTUD, Buffering, microbursts, and congestion signaling, Load balancing and hashing - ECMP and entropy
- 4.3 Security -> Transport security and encrypted-traffic implications
5.0 Network and network virtualization
- 5.1 MPLS (forwarding/control, MP-BGP, label distribution, segment routing) -> MPLS fundamentals, Segment Routing
- 5.2 L2/L3 VPN and tunneling (selection, endpoints, optimization, routing effects, overlays VXLAN/LISP/MP-BGP, BGP EVPN, segmentation VLAN/PVLAN/VRF/SGT) -> MPLS L3VPN and L2VPN, Tunneling technology selection, Overlays and BGP EVPN, Infrastructure segmentation
- 5.3 SD-WAN (planes, segmentation, policy) -> SD-WAN design, WAN transport architecture selection
- 5.4 Migration techniques -> Reference models and migration considerations, Transport resiliency, diversity, and migration
- 5.5 Design considerations -> WAN transport architecture selection, Reference models and migration considerations
- 5.6 QoS techniques and strategies -> QoS design - models and strategy
- 5.7 Network management (SNMP/syslog vs NETCONF/gNMI/streaming telemetry) -> Network management - traditional vs model-driven
- 5.8 Reference models (FCAPS, ITIL, TOGAF, DevOps) -> Reference models and migration considerations
6.0 Security
- 6.1.a-c Device/control/management/data-plane hardening -> Infrastructure hardening - control, management, and data plane
- 6.1.d Policy plane signaling (RADIUS, TACACS+, pxGrid, SXP) -> AAA and identity - RADIUS, TACACS+, 802.1X, Network access control and segmentation - NAC, TrustSec, guest and BYOD
- 6.1.e Layer 2 security techniques -> Layer 2 security
- 6.1.e.viii-ix MACsec incl. WAN -> MACsec and secure transport
- 6.1.f Wireless security -> Wireless security
- 6.2 Protecting network services (DPI, data plane) -> Perimeter security - firewalls and IPS-IDS, Infrastructure hardening - control, management, and data plane
- 6.3 Perimeter security, IPS/IDS, common attacks -> Perimeter security - firewalls and IPS-IDS, Threat detection and mitigation - DDoS, spoofing, MITM
- 6.4 Zero trust (ZTNA, AI/ML-assisted policy, migration) -> Zero Trust and ZTNA
- 6.5 Network control and identity (802.1X/MAB, guest/BYOD, identity sources, EAP chaining, MFA) -> AAA and identity - RADIUS, TACACS+, 802.1X, Network access control and segmentation - NAC, TrustSec, guest and BYOD
7.0 Wireless
- 7.1 802.11 standards up to Wi-Fi 7; RF deployments (coverage, throughput, voice, location, HD) -> Wireless fundamentals and 802.11 standards, RF design - coverage, capacity, high density, voice, location
- 7.2 Enterprise wireless (HA, controller placement/mobility, L2/L3 roaming, tunnel optimization, AP groups/modes) -> WLAN architectures, Controller placement, HA, and tunnel optimization, Roaming - L2 vs L3 mobility
8.0 Automation
- 8.1 Zero-touch provisioning -> Zero-touch provisioning
- 8.2 Infrastructure as Code (CI/CD platforms, config management, provisioning, orchestration, Python) -> Infrastructure as Code - declarative, idempotent, source of truth, Automation tooling - Ansible vs Terraform and orchestration, CI-CD pipelines for networks (NetDevOps), Network automation fundamentals - why and the operating model, Telemetry-driven and closed-loop automation
AI Infrastructure Technology List
1.0 AI/Machine learning
- 1.1.a-d ML, deep learning, LLM, GenAI impacts -> AI-ML workloads and their infrastructure impact
- 1.2 Service placement -> Service placement - on-prem, cloud, hybrid, distributed
- 1.3 Data sovereignty -> Data sovereignty and data gravity
- 1.4 Regulations, policies, governance -> Regulations, governance, and AI security policy
- 1.5.a-d Sustainability (Green AI, affordability, accelerators, power/cooling) -> Sustainability - Green AI, power and cooling, Cost, ROI, and scalability of AI infrastructure, AI-enabling hardware - GPU, DPU, SmartNIC
2.0 Network
- 2.1 Lossless fabrics + 2.2 QoS in lossless fabrics -> Lossless fabric - PFC, ECN, DCQCN, Validated reference design - Cisco AI-ML lossless fabric (CVD)
- 2.3.a-b Ethernet / InfiniBand -> Fabric transport - Ethernet vs InfiniBand vs UEC
- 2.3.c Latency -> Latency and the straggler problem
- 2.3.d Bandwidth and capacity -> Bandwidth and capacity planning
- 2.3.e Single-site or multi-site -> Connectivity models and SDN in AI fabrics, Fabric resiliency and failure handling (site-level DR)
- 2.3.f Optics impacts -> Optics and cabling selection
- 2.4 Traditional vs SDN (ACI) infrastructure, fabric interconnection -> Connectivity models and SDN in AI fabrics, Validated reference design - Cisco AI-ML lossless fabric (CVD)
- 2.5 Layer 2 scalability, learning and propagation -> Connectivity models and SDN in AI fabrics, Overlays and BGP EVPN
- 2.6 Routing-protocol optimizations -> Rail-optimized CLOS topology, Validated reference design - Cisco AI-ML lossless fabric (CVD)
- 2.7 RDMA and RoCE/RoCEv2 -> RDMA, RoCE and RoCEv2
- 2.8 Connectivity models (islands vs main DC, CLOS/hierarchical) -> Connectivity models and SDN in AI fabrics, Rail-optimized CLOS topology
3.0 Security
- 3.1 Hosting implications + 3.2 air-gapped/public/private -> AI security design and hosting models - air-gapped, private, public
- 3.3 Protection against malicious uses (WAF etc.) -> Protecting AI services - WAF, API security, and inference endpoints
- (fabric + tenancy depth) -> Securing the high-performance fabric, Tenant isolation and segmentation in shared AI clusters, Model and data protection
4.0 Hardware and environment
- 4.1 Compute resources -> AI-enabling hardware - GPU, DPU, SmartNIC, Scale-up vs scale-out
- 4.2.a-c GPU, SmartNIC, DPU -> AI-enabling hardware - GPU, DPU, SmartNIC
- 4.3.a-c Data scrubbing, log correlation, telemetry analysis -> AI-assisted operations - AIOps, AI-assisted threat detection (AI for security operations)
- 4.4.a Data storage strategy + 4.4.c IP-based storage -> Storage and checkpointing for AI
- 4.4.b FC, FCoE, NVMe, NVMe-oF, software-defined storage -> Storage networking - FC, FCoE, iSCSI, and NVMe-oF, Storage and checkpointing for AI (closed 2026-07-02; the James Long book remains queued for parity triage)
- 4.5 Timing protocols (PTP) -> PTP timing for AI fabrics (matrix row 4.6; BRKENS-2094 full pass 2026-07-05: BMCA, BC-vs-TC + PTP-unaware transit, profiles, AVB/TSN mined)
Learning Matrix v1.1 deltas (audited 2026-07-02)
- 1.1.e SLM -> parity: AI-ML workloads and their infrastructure impact (LLM-vs-SLM design treatment + card)
- 1.5 Flexible workload placement between sites -> parity: Workload placement, mobility, and vendor lock-in
- 1.7 Interoperability, multi-cloud, vendor lock-in -> parity: Workload placement, mobility, and vendor lock-in, Fabric transport - Ethernet vs InfiniBand vs UEC
- 2.3 Redundancy, resiliency, and DR -> Fabric resiliency and failure handling - site/cluster-level DR section added this batch
- 2.4.f Direct-attach cables alongside optics -> parity: Optics and cabling selection (DAC/AEC/AOC/LPO ladder)
- 3.4 Resource security (on-prem, cloud, clustered, containers) -> AI security design and hosting models - air-gapped, private, public, Tenant isolation and segmentation in shared AI clusters - container/orchestration layer added this batch
- 4.2.c CPU -> parity: AI-enabling hardware - GPU, DPU, SmartNIC (CPU-as-inference-accelerator, AMX)
- 4.3 Real-time operations and monitoring -> parity: AI-assisted operations - AIOps, Telemetry-driven and closed-loop automation