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Traffic & Routing Complexity

Rating model: Express every finding as Impact 1–5 using the Impact Indicator rubric (security/reputation · business/revenue · nature & effort to remediate). Band mapping is a starting point — GREEN→🟡 1–2, AMBER→🟠 3–4, RED→🔴 5 — but the Impact Indicator criteria set the final score (e.g. an easy-to-deploy prerequisite stays 🟡 low even if it blocks a path). All checks are read-only (kubectl get/describe, aws … describe/list).

Purpose​

Assess routing complexity and map current patterns to Gateway API HTTPRoute equivalents.

Checks to Execute​

5.1 — Routing Pattern Mapping​

What to check:

  • Host-based routing → HTTPRoute hostnames field
  • Path-based routing → HTTPRoute matches[].path
  • Default backend → HTTPRoute with no matches (catch-all)
  • Complexity per Ingress resource

How to check:

  1. For each Ingress, count spec.rules entries
  2. Count unique hosts across all Ingress resources
  3. Check path types (Prefix, Exact, ImplementationSpecific)
  4. Flag ImplementationSpecific — Gateway API only supports Exact and PathPrefix

Gateway API mapping:

  • Ingress spec.rules[].host → HTTPRoute spec.hostnames[]
  • Ingress spec.rules[].http.paths[] → HTTPRoute spec.rules[].matches[].path
  • Ingress Prefix → HTTPRoute PathPrefix
  • Ingress Exact → HTTPRoute Exact
  • Ingress ImplementationSpecific → ❌ Must be converted to Exact or PathPrefix

Impact (per Impact Indicator):

  • 🟡 1–2 (Low): Simple host+path routing, all Prefix/Exact — direct HTTPRoute mapping
  • 🟠 3–4 (Medium): Some ImplementationSpecific paths or regex patterns needing conversion
  • 🔴 5 (High): Heavy regex routing, >20 rules per Ingress, complex rewrite chains
  • ⬜ Unknown: Cannot parse routing rules

Path-matching semantics change — converting regex/ImplementationSpecific → PathPrefix is NOT behavior-preserving. ingress-nginx evaluates regex paths by rule order / regex specificity; ALB and Gateway API use "most specific path wins." A hard switch can silently route traffic to the wrong backend or yield 404s that generic monitoring misses. Do not flip path types blindly: build a routing comparison table (every host+path → backend) for NGINX vs the target, and shadow/replay representative requests to confirm 100% match before cutover. Treat any cluster with regex/ImplementationSpecific paths as needing this validation step (raise its impact accordingly).

Report output format: In the report's "Current Config" column, show actual config as compact 1-liner: Ingress/<name>: <host><path> → <backend>:<port> (<pathType>, TLS:<yes/no>) Example: Ingress/shopping-app: /*→frontend:80 (Prefix, TLS:no) Example: Ingress/nginx-alb: app.example.com/* → nginx-service:80 (Prefix, TLS:ACM)

5.2 — Advanced Traffic Features​

What to check:

  • Canary/weighted routing → HTTPRoute backendRefs[].weight
  • Header-based routing → HTTPRoute matches[].headers
  • URL rewriting → HTTPRoute filters[].urlRewrite
  • Request redirect → HTTPRoute filters[].requestRedirect
  • Request/response header modification → HTTPRoute filters[].requestHeaderModifier
  • Authentication → No native Gateway API equivalent (use ALB Cognito/OIDC annotation)
  • Rate limiting → No native equivalent (use AWS WAF)
  • CORS → No native equivalent (use application-level or WAF)

How to check:

  1. Scan annotations for advanced features
  2. Map each to Gateway API equivalent or workaround
  3. Flag features with no equivalent

Impact (per Impact Indicator):

  • 🟡 1–2 (Low): Features used have direct HTTPRoute equivalents (weighted routing, header matching, rewrites)
  • 🟠 3–4 (Medium): Some features need AWS service substitution (WAF for rate limiting, Cognito for auth)
  • 🔴 5 (High): Critical dependency on nginx lua/snippets with no Gateway API path
  • ⬜ Unknown: Cannot determine feature usage

5.3 — Cross-Namespace Routing​

What to check:

  • Ingress resources referencing services in other namespaces
  • Gateway API model: cross-namespace routing requires explicit ReferenceGrant
  • Service mesh integration (Istio, Linkerd)

How to check:

  1. Check Ingress backends for cross-namespace references
  2. List Services of type ExternalName
  3. Check for Istio VirtualService / Linkerd ServiceProfile CRDs

Impact (per Impact Indicator):

  • 🟡 1–2 (Low): All routing within same namespace — straightforward HTTPRoute conversion
  • 🟠 3–4 (Medium): Some cross-namespace routing — need to create ReferenceGrant resources
  • 🔴 5 (High): Heavy service mesh integration — Gateway API migration must coordinate with mesh
  • ⬜ Unknown: Cannot determine cross-namespace routing

5.4 — ALB IngressGroup Sharing​

What to check (read-only): alb.ingress.kubernetes.io/group.name and group.order on each Ingress.

  • Multiple Ingresses (often across namespaces) sharing one group.name are served by a single ALB. This materially affects Gateway listener design and ALB consolidation during migration.
  • Record group membership in the topology JSON and Routing Topology — do not drop it.

5.5 — Declarative Blind Spot & Optional Route Verification​

Blind spot (always note when snippets are present): topology and routing are derived from Ingress objects only. Routes injected via server-snippet / configuration-snippet (e.g. a raw location block) do not appear as Ingress rules/backends, so the 3D diagram and Routing Topology under-count them. State this limitation explicitly in the report whenever snippet annotations exist — these are exactly the routes that block migration.

Optional deep read (requires --allow-sensitive-data-access, still read-only):

  • Enumerate snippet-injected routes: kubectl exec <nginx-pod> -n <ns> -- nginx -T and scan for location blocks not represented by an Ingress.
  • Verify live L7 behavior in-cluster: from a throwaway pod, wget/curl each controller's ClusterIP with the Host: header and record the status code (200/301/308/404/5xx) in Routing Topology. This raises confidence that routing actually works (vs. config-only inference). Keep it optional — the assessment is config-first.

Topology data to collect: Record all routing patterns, hosts, paths, and features for the 3D visualization.