'use client'

import Link from 'next/link'
import { ArrowLeft } from 'lucide-react'
import { motion } from 'framer-motion'

const skillCategories = [
  {
    title: 'Infrastructure & Orchestration',
    skills: ['Kubernetes (Talos Linux)', 'ArgoCD (GitOps)', 'Terraform (IaC)', 'Kustomize'],
  },
  {
    title: 'Networking & Ingress',
    skills: ['nginx Ingress Controller', 'Cloudflare Tunnel', 'CoreDNS', 'NetworkPolicy'],
  },
  {
    title: 'Storage',
    skills: ['Longhorn (distributed block)', 'MinIO (S3-compatible)'],
  },
  {
    title: 'Databases',
    skills: ['CloudNativePG (PostgreSQL)', 'pgvector (AI embeddings)'],
  },
  {
    title: 'Identity & Security',
    skills: ['Authentik (OIDC SSO)', 'SOPS (encrypted secrets)', 'cert-manager (TLS)'],
  },
  {
    title: 'Observability',
    skills: ['Prometheus', 'Grafana', 'Tempo (tracing)', 'OpenTelemetry', 'Loki (logs)'],
  },
  {
    title: 'CI/CD',
    skills: ['Forgejo (git + Actions)', 'Container Registry', 'DinD Runners'],
  },
  {
    title: 'AI/ML Platform',
    skills: ['vLLM (Qwen3-32B)', 'Ollama', 'TEI (embeddings)', 'KServe'],
  },
  {
    title: 'Workflow & Messaging',
    skills: ['Temporal (durable workflows)', 'Kafka/Redpanda (streaming)'],
  },
  {
    title: 'Languages & Frameworks',
    skills: ['Go (API gateway)', 'Python (ML)', 'Next.js (frontend)'],
  },
]

export default function HomelabPage() {
  return (
    <main className="min-h-screen bg-white dark:bg-gray-950">
      <div className="max-w-6xl mx-auto px-6 py-20">
        <Link 
          href="/#project-homelab" 
          className="inline-flex items-center gap-2 text-blue-600 dark:text-blue-400 hover:underline mb-8"
        >
          <ArrowLeft size={16} />
          Back to Projects
        </Link>

        {/* Hero */}
        <motion.div
          initial={{ opacity: 0, y: 20 }}
          animate={{ opacity: 1, y: 0 }}
          transition={{ duration: 0.6 }}
          className="mb-16"
        >
          <h1 className="text-5xl font-bold text-gray-900 dark:text-white mb-4">
            Building AWS at Home
          </h1>
          <p className="text-xl text-gray-600 dark:text-gray-400 mb-6">
            A 3-year journey through distributed systems, from Step Functions to LLM inference.
          </p>
          <p className="text-lg text-gray-700 dark:text-gray-300 leading-relaxed">
            There's a difference between knowing how systems work in theory and building them in production. I've spent the last 3 years learning this difference the hard way—first at AWS, then at RBC, and now at home. This is the story of how I learned distributed systems by owning every layer: from workflow orchestration to hardware networking, from GitOps to AI agents.
          </p>
        </motion.div>

        {/* Chapter 1: Homelab */}
        <motion.section
          initial={{ opacity: 0, y: 40 }}
          whileInView={{ opacity: 1, y: 0 }}
          viewport={{ once: true }}
          className="mb-16 border-l-4 border-purple-500 pl-8"
        >
          <div className="mb-6">
            <div className="text-sm font-semibold text-purple-600 dark:text-purple-400 uppercase tracking-wide mb-2">
              The Journey
            </div>
            <h2 className="text-3xl font-bold text-gray-900 dark:text-white mb-2">
              Homelab: Building AWS from Scratch
            </h2>
            <p className="text-gray-600 dark:text-gray-400 font-medium">May 2025 – Present</p>
          </div>

          <div className="prose prose-lg dark:prose-invert max-w-none mb-6">
            <p className="text-gray-700 dark:text-gray-300">
              The question: <strong>How does LLM serving work at scale?</strong> The only way to answer that was to build an entire cloud-like platform with SaaS fundamentals from scratch. 4 bare-metal machines, 1 GPU node, 1 Dell PowerEdge (now in the garage due to noise), and 2 mini-desktops. All running Talos Linux, a Kubernetes-native OS designed for immutability.
            </p>
          </div>

          {/* Infrastructure section + diagram */}
          <div className="mb-8">
            <h3 className="text-2xl font-bold text-gray-900 dark:text-white mb-4">
              Infrastructure Layer
            </h3>
            <div className="bg-gray-50 dark:bg-gray-900 rounded-lg p-6 border border-gray-200 dark:border-gray-800 mb-6">
              <p className="text-gray-700 dark:text-gray-300 mb-4">
                4-node bare-metal cluster (3 control plane + 1 worker) running Talos Linux—immutable, API-driven OS designed for Kubernetes. All wired ethernet to avoid etcd consensus issues.
              </p>
              <ul className="space-y-2 text-sm text-gray-600 dark:text-gray-400">
                <li>• <strong>Compute:</strong> Talos Linux nodes, machine config via Terraform</li>
                <li>• <strong>Networking:</strong> Cilium CNI, nginx ingress, Cloudflare Tunnel for zero-trust external access</li>
                <li>• <strong>Storage:</strong> Longhorn for distributed block storage with disk tagging, MinIO for S3</li>
                <li>• <strong>GitOps:</strong> ArgoCD with multi-source Applications and sync waves</li>
              </ul>
            </div>

            {/* Cluster Topology Diagram */}
            <div className="mb-6 bg-white dark:bg-gray-900 rounded-lg border border-gray-200 dark:border-gray-800 overflow-hidden hover:shadow-lg transition-shadow">
              <div className="p-4 bg-gradient-to-r from-blue-50 to-purple-50 dark:from-gray-800 dark:to-gray-800 border-b border-gray-200 dark:border-gray-800">
                <h4 className="font-semibold text-gray-900 dark:text-white">Talos Cluster Topology</h4>
                <p className="text-xs text-gray-600 dark:text-gray-400 mt-1">Control planes, worker GPU, storage, and networking architecture</p>
              </div>
              <div className="w-full" style={{ height: '700px' }}>
                <iframe
                  src="/diagrams/homelab-cluster.html"
                  className="w-full h-full border-none"
                  title="Talos Cluster Topology"
                />
              </div>
            </div>
          </div>

          {/* GitOps section + diagram */}
          <div className="mb-8">
            <h3 className="text-2xl font-bold text-gray-900 dark:text-white mb-4">
              GitOps Evolution
            </h3>
            <div className="bg-gray-50 dark:bg-gray-900 rounded-lg p-6 border border-gray-200 dark:border-gray-800 mb-6">
              <p className="text-gray-700 dark:text-gray-300 mb-4">
                Started with Terraform for everything—but constant reconciliation of pods and configmaps created chaos. Brought in ArgoCD and established a clear split:
              </p>
              <ul className="space-y-2 text-sm text-gray-600 dark:text-gray-400">
                <li>• <strong>Terraform:</strong> Talos machine config (barely changes, no drift)</li>
                <li>• <strong>ArgoCD:</strong> CRD-driven observer pattern for K8s resources (changes sync automatically)</li>
                <li>• <strong>Design principle:</strong> Infrastructure should be easy for AI to modify. Declarative config + clear abstractions = easier for models to reason about</li>
              </ul>
            </div>

            {/* GitOps Workflow Diagram */}
            <div className="mb-6 bg-white dark:bg-gray-900 rounded-lg border border-gray-200 dark:border-gray-800 overflow-hidden hover:shadow-lg transition-shadow">
              <div className="p-4 bg-gradient-to-r from-blue-50 to-purple-50 dark:from-gray-800 dark:to-gray-800 border-b border-gray-200 dark:border-gray-800">
                <h4 className="font-semibold text-gray-900 dark:text-white">GitOps Deployment Flow</h4>
                <p className="text-xs text-gray-600 dark:text-gray-400 mt-1">ArgoCD for Kubernetes and Terraform for Talos infrastructure</p>
              </div>
              <div className="w-full" style={{ height: '700px' }}>
                <iframe
                  src="/diagrams/homelab-gitops.html"
                  className="w-full h-full border-none"
                  title="GitOps Workflow"
                />
              </div>
            </div>
          </div>

          {/* AI/ML Platform */}
          <div className="mb-8">
            <h3 className="text-2xl font-bold text-gray-900 dark:text-white mb-4">
              AI/ML Platform
            </h3>
            <div className="bg-gray-50 dark:bg-gray-900 rounded-lg p-6 border border-gray-200 dark:border-gray-800 mb-6">
              <p className="text-gray-700 dark:text-gray-300 mb-4">
                Self-hosted LLM inference with multi-tenant GPU scheduling and 60% latency reduction.
              </p>
              <ul className="space-y-2 text-sm text-gray-600 dark:text-gray-400">
                <li>• <strong>Inference:</strong> vLLM serving Qwen3-32B with INT4 quantization</li>
                <li>• <strong>Multi-model:</strong> Ollama for smaller models, hot-swapping</li>
                <li>• <strong>Embeddings:</strong> TEI for text embeddings and reranking</li>
                <li>• <strong>Orchestration:</strong> KServe + custom Go API gateway</li>
                <li>• <strong>Scheduling:</strong> GPU node affinity with sm70/Volta constraints</li>
              </ul>
            </div>

            {/* LLM Stack Diagram */}
            <div className="mb-6 bg-white dark:bg-gray-900 rounded-lg border border-gray-200 dark:border-gray-800 overflow-hidden hover:shadow-lg transition-shadow">
              <div className="p-4 bg-gradient-to-r from-blue-50 to-purple-50 dark:from-gray-800 dark:to-gray-800 border-b border-gray-200 dark:border-gray-800">
                <h4 className="font-semibold text-gray-900 dark:text-white">LLM Inference Architecture</h4>
                <p className="text-xs text-gray-600 dark:text-gray-400 mt-1">Gateway routing to vLLM, Ollama, and TEI on GPU worker node</p>
              </div>
              <div className="w-full" style={{ height: '700px' }}>
                <iframe
                  src="/diagrams/homelab-llm-stack.html"
                  className="w-full h-full border-none"
                  title="LLM Inference Stack"
                />
              </div>
            </div>

            {/* Request Lifecycle Diagram */}
            <div className="mb-6 bg-white dark:bg-gray-900 rounded-lg border border-gray-200 dark:border-gray-800 overflow-hidden hover:shadow-lg transition-shadow">
              <div className="p-4 bg-gradient-to-r from-blue-50 to-purple-50 dark:from-gray-800 dark:to-gray-800 border-b border-gray-200 dark:border-gray-800">
                <h4 className="font-semibold text-gray-900 dark:text-white">Request Lifecycle</h4>
                <p className="text-xs text-gray-600 dark:text-gray-400 mt-1">Client → nginx → gateway → predictor → streaming response</p>
              </div>
              <div className="w-full" style={{ height: '700px' }}>
                <iframe
                  src="/diagrams/homelab-api-gateway-sequence.html"
                  className="w-full h-full border-none"
                  title="API Request Flow"
                />
              </div>
            </div>
          </div>

          {/* Data & Security */}
          <div className="grid grid-cols-1 md:grid-cols-2 gap-6 mb-8">
            <div className="bg-gray-50 dark:bg-gray-900 rounded-lg p-6 border border-gray-200 dark:border-gray-800">
              <h3 className="font-semibold text-gray-900 dark:text-white mb-3">
                Data Platform
              </h3>
              <ul className="space-y-2 text-sm text-gray-600 dark:text-gray-400">
                <li>• <strong>PostgreSQL:</strong> CloudNativePG operator with HA, automated failover</li>
                <li>• <strong>Vector DB:</strong> pgvector extension for AI embeddings</li>
                <li>• <strong>Streaming:</strong> Kafka/Redpanda for event-driven architecture</li>
                <li>• <strong>Workflows:</strong> Temporal for durable, long-running processes</li>
              </ul>
            </div>

            <div className="bg-gray-50 dark:bg-gray-900 rounded-lg p-6 border border-gray-200 dark:border-gray-800">
              <h3 className="font-semibold text-gray-900 dark:text-white mb-3">
                Identity & Security
              </h3>
              <ul className="space-y-2 text-sm text-gray-600 dark:text-gray-400">
                <li>• <strong>SSO:</strong> Authentik OIDC provider with custom claims</li>
                <li>• <strong>RBAC:</strong> Kubernetes RBAC synced with Authentik groups</li>
                <li>• <strong>Secrets:</strong> SOPS-encrypted secrets in git, decrypted at deploy time</li>
                <li>• <strong>TLS:</strong> cert-manager with DNS-01 ACME via Cloudflare</li>
              </ul>
            </div>
          </div>

          <div className="bg-purple-50 dark:bg-purple-900/30 border-l-4 border-purple-500 p-4 rounded-r">
            <div className="font-semibold text-purple-900 dark:text-purple-200 mb-1">Key Learnings</div>
            <ul className="text-purple-800 dark:text-purple-100 text-sm space-y-1">
              <li>• Powerline adapters killed etcd consensus at 200ms latency. Ethernet to garage solved it.</li>
              <li>• Network is foundational—hardware matters more than code sometimes.</li>
              <li>• Design infrastructure so AI can modify it easily. Declarative + immutable = no surprises.</li>
            </ul>
          </div>
        </motion.section>

        {/* Chapter 4 */}
        <motion.section
          initial={{ opacity: 0, y: 40 }}
          whileInView={{ opacity: 1, y: 0 }}
          viewport={{ once: true }}
          className="mb-16 border-l-4 border-yellow-500 pl-8"
        >
          <div className="mb-6">
            <div className="text-sm font-semibold text-yellow-600 dark:text-yellow-400 uppercase tracking-wide mb-2">
              Next: The AI System
            </div>
            <h2 className="text-3xl font-bold text-gray-900 dark:text-white mb-2">
              Poimen: The AI Agent System
            </h2>
            <p className="text-gray-600 dark:text-gray-400 font-medium">Building</p>
          </div>

          <div className="prose prose-lg dark:prose-invert max-w-none mb-6">
            <p className="text-gray-700 dark:text-gray-300">
              Current LLM architecture works seamlessly with lambda/serverless patterns. The key insight: <strong>if AI is powerful because of context, tool-calling, and memory, what if we provide the right context in the right environment?</strong>
            </p>
          </div>

          <ul className="space-y-3 text-gray-700 dark:text-gray-300 mb-6">
            <li className="flex gap-3">
              <span className="text-yellow-500 font-bold flex-shrink-0">•</span>
              <span><strong>poimen-memory:</strong> Graph-RAG with wiki-link indexing, 7B model for instruct QA, pgvector + OpenSearch hybrid search</span>
            </li>
            <li className="flex gap-3">
              <span className="text-yellow-500 font-bold flex-shrink-0">•</span>
              <span><strong>poimen-workflows:</strong> Natural language → executable WorkflowSpec via reasoning model, Temporal for durable execution</span>
            </li>
            <li className="flex gap-3">
              <span className="text-yellow-500 font-bold flex-shrink-0">•</span>
              <span><strong>Activity Knowledge Base:</strong> Informs LLM about timeouts, retry policies, dependencies before routing</span>
            </li>
            <li className="flex gap-3">
              <span className="text-yellow-500 font-bold flex-shrink-0">•</span>
              <span><strong>Generic state machine:</strong> JSON workflow spec + JSONPath parameter chaining. Temporal enables redrive + free self-hosted</span>
            </li>
          </ul>

          <div className="bg-yellow-50 dark:bg-yellow-900/30 border-l-4 border-yellow-500 p-4 rounded-r">
            <div className="font-semibold text-yellow-900 dark:text-yellow-200 mb-1">The Vision</div>
            <p className="text-yellow-800 dark:text-yellow-100 text-sm">
              Build a skill factory where a model generates workflows and completes them. Each Temporal activity is independently refined—enabling a general-purpose workflow orchestrator that improves through iteration.
            </p>
          </div>
        </motion.section>

        {/* Skills Grid */}
        <motion.section
          initial={{ opacity: 0 }}
          whileInView={{ opacity: 1 }}
          viewport={{ once: true }}
          className="mb-12 mt-24 pt-16 border-t border-gray-200 dark:border-gray-800"
        >
          <h2 className="text-4xl font-bold text-gray-900 dark:text-white mb-12">
            Technologies & Skills Mastered
          </h2>
          <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-8">
            {skillCategories.map((category, idx) => (
              <motion.div
                key={category.title}
                initial={{ opacity: 0, y: 20 }}
                whileInView={{ opacity: 1, y: 0 }}
                viewport={{ once: true }}
                transition={{ delay: idx * 0.05 }}
                className="bg-gradient-to-br from-blue-50 to-purple-50 dark:from-gray-900 dark:to-gray-800 rounded-lg p-8 border border-gray-200 dark:border-gray-800 hover:shadow-lg transition-shadow h-full"
              >
                <h3 className="font-bold text-gray-900 dark:text-white mb-6 text-xl">
                  {category.title}
                </h3>
                <div className="flex flex-wrap gap-3">
                  {category.skills.map((skill) => (
                    <span
                      key={skill}
                      className="text-base px-4 py-2 rounded-full bg-white dark:bg-gray-700 text-blue-700 dark:text-blue-300 font-semibold border border-blue-200 dark:border-blue-600 hover:border-blue-400 dark:hover:border-blue-400 transition-colors"
                    >
                      {skill}
                    </span>
                  ))}
                </div>
              </motion.div>
            ))}
          </div>
        </motion.section>
      </div>
    </main>
  )
}