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KubeAuto Day IDP — AI Platform Building Scorecard

A production-grade Internal Developer Platform on EKS, built with AI assistance and measured honestly.

What This Is

This repository contains a complete IDP built for KubeAuto Day Europe 2026. Every component was built using AI-assisted development (Claude Code) with test-driven methodology. Every correction cycle was documented.

The platform is real. The scorecard is honest. The methodology is reusable.

The Scorecard

Metric Value
AI build time 3 hours 10 min
Manual estimate 12 hours
Toil reduction 73.8%
Components scored 27/27
Zero-correction rate 41% (11/27)
Average quality score 8.0/10

Full scorecard: spec/SCORECARD.md

Deep Dives

  • Architecture — Platform architecture, component relationships, data flows
  • Walkthrough — Complete build narrative with Three-Layer Guardrail Architecture
  • Eight Guardrails — Defense-in-depth framework (Git → Claude Code → Kubernetes)
  • Security — Kyverno, Falco, RBAC, ESO, NetworkPolicies, cert-manager
  • Lessons Learned — What went wrong and what we'd do differently

Platform Stack

Layer Component Version
Infrastructure EKS on AWS 1.34
GitOps ArgoCD 3.3.0
Policy Enforcement Kyverno 1.17.0
Runtime Security Falco (eBPF) 0.43.0
Secret Management ESO + AWS Secrets Manager 1.3.2
Observability Prometheus + Grafana + OTel 3.9.1 / 12.3.3 / 0.145.0
Developer Portal Backstage 1.9.1
TLS cert-manager + Let's Encrypt 1.19.3

27 ArgoCD Applications managed via app-of-apps pattern.

Repository Structure

infrastructure/terraform/   # EKS, VPC, IAM (Terraform)
gitops/
  bootstrap/                # ArgoCD + root app-of-apps
  apps/                     # 26 ArgoCD Application manifests
  namespaces/               # Namespace definitions
security/
  kyverno/                  # 6 ClusterPolicies
  falco/                    # 5 custom Falco rules
  eso/                      # ClusterSecretStore + ExternalSecrets
  rbac/                     # ClusterRoles + RoleBindings
  network-policies/         # Default-deny + allow rules
  cert-manager/             # ClusterIssuers
  quotas-pdbs/              # ResourceQuota + 5 PDBs
observability/
  grafana/dashboards/       # Grafana Platform Overview dashboard
backstage/
  catalog/                  # System, Component, Templates
  templates/                # deploy-service, create-namespace
sample-app/                 # Python Flask app with OTel
tests/                      # 59 tests across 7 phases (real infra, no mocks)
docs/
  adr/                      # 9 Architecture Decision Records
  ARCHITECTURE.md           # Platform architecture overview
  SETUP.md                  # Reproduction guide
  TEARDOWN.md               # Cluster destruction guide
  SECURITY.md               # Security posture summary
  COST.md                   # AWS cost breakdown
scorecard/
  methodology.md            # Scoring definitions
  raw-scores.json           # Machine-readable results
  SCORECARD-TEMPLATE.md     # Blank template for your own builds
collateral/
  demo-runbook.md           # Live demo commands
  blog-post-draft.md        # Conference blog post
  slide-outline.md          # Talk slide structure
  attendee-handout.md       # Audience reference card
  social-media-thread.md    # Announcement thread

Use the Scorecard Template

Want to measure your own AI-assisted builds?

  1. Copy scorecard/SCORECARD-TEMPLATE.md
  2. Read scorecard/methodology.md for scoring definitions
  3. Fill it in as you build (don't reconstruct after the fact)
  4. Share your results

Reproduce the Platform

See docs/SETUP.md for step-by-step instructions.

Prerequisites: AWS account, Terraform >= 1.7, kubectl, Helm, Python 3.12+, uv.

Cost: ~$0.57/hr while running. See docs/COST.md.

Teardown: See docs/TEARDOWN.md.

Architecture Decisions

ADR Decision
000 Domain name (ai-enhanced-devops.com)
001 Terraform over Pulumi/CDK
002 ArgoCD over Flux
003 Kyverno over OPA/Gatekeeper
003b Falco for runtime security
004 ESO over Secrets Store CSI
005 Prometheus + Grafana over Datadog/Mimir
006 Backstage for developer portal
007 GitHub OIDC for authentication

Key Findings

  1. AI reduces IDP build toil by ~74% — but the remaining 26% is harder toil
  2. 41% of components had zero corrections — AI excels at boilerplate
  3. Version currency is AI's #1 weakness — stale chart versions, deprecated APIs
  4. TDD catches AI mistakes fast — write the test first, always
  5. Skill files/context are essential — generic prompts get generic errors

License

Apache 2.0. See LICENSE.

Author

Michael Forrester — KodeKloud

Built for KubeAuto Day Europe 2026, Amsterdam.

About

Production-grade IDP on EKS built with AI in 3 hours. 27 components, 59 tests, honest scorecard. Reusable template included.

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