Package com.eqixiac.equinix.design

package com.eqixiac.equinix.design
Value-add design engines built on top of the Equinix API clients: placement optimization, deployment planning, pricing/TCO analysis, peering intelligence, latency physics, and infrastructure-as-code export.

Module map

  • design.optimizer — placement: scores and ranks Equinix metros against sites, workloads, providers, and constraints (MetroOptimizer → OptimizationResult).
  • design.optimizer.wizard — plan & execute: turns an OptimizationResult into a validated DeploymentPlan (Cloud Routers, connections, backbone links, routing protocols) that can be dry-run, executed, and rolled back.
  • design.value — pricing and TCO: layered RateCards (live Equinix, custom, reference, cloud-provider adapters), egress savings, and total-cost-of-ownership comparison.
  • design.peering — PeeringDB intelligence: IX/facility presence matrices, Fabric on-ramp cross-referencing, resiliency and blast-radius analysis, peering opportunities.
  • design.geo — latency physics: speed-of-light-in-fibre latency floors and haversine distances between IBXes, metros, and raw coordinates.
  • design.export — export: Terraform HCL and Mermaid topology diagrams from plans and results.

A typical flow is optimizer → wizard → export, with design.value pricing feeding both the optimizer's cost dimension and the wizard's plan pricing, and design.geo supplying the distance/latency estimates used throughout.

Composition boundary

Every engine runs over FabricGateway — the narrow capability view of the Fabric client (metros, service profiles, cloud routers, connections, routing protocols, prices) — never over the full concrete client. Enter through Design.over(com.eqixiac.equinix.FabricGateway), the equivalent accessors on Fabric (optimizeMetros(), deploymentWizard(...), peeringIntelligence(), savingsCalculator(), tcoComparison()), or a shared Equinix session's design().

See Also: