cleanup and prefect service setup
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Deeman
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infra/readme.md
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infra/readme.md
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# Materia Infrastructure
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Pulumi-managed infrastructure for BeanFlows.coffee
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## Stack Overview
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- **Storage:** Cloudflare R2 buckets with Iceberg Data Catalog
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- **Compute:** Hetzner Cloud CCX dedicated vCPU instances
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- **Orchestration:** Custom Python scheduler (see `src/orchestrator/`)
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## Prerequisites
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1. **Cloudflare Account**
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- Sign up at https://dash.cloudflare.com
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- Create API token with R2 + Data Catalog permissions
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- Get your Account ID from dashboard
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2. **Hetzner Cloud Account**
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- Sign up at https://console.hetzner.cloud
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- Create API token with Read & Write permissions
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3. **Pulumi Account** (optional, can use local state)
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- Sign up at https://app.pulumi.com
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- Or use local state with `pulumi login --local`
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4. **SSH Key**
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- Generate if needed: `ssh-keygen -t ed25519 -C "materia-deploy"`
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## Initial Setup
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```bash
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cd infra
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# Login to Pulumi (local or cloud)
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pulumi login # or: pulumi login --local
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# Initialize the stack
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pulumi stack init dev
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# Configure secrets
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pulumi config set --secret cloudflare:apiToken <your-cloudflare-token>
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pulumi config set cloudflare_account_id <your-account-id>
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pulumi config set --secret hcloud:token <your-hetzner-token>
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pulumi config set --secret ssh_public_key "$(cat ~/.ssh/id_ed25519.pub)"
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# Preview changes
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pulumi preview
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# Deploy infrastructure
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pulumi up
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```
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## What Gets Provisioned
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### Cloudflare R2 Buckets
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1. **materia-raw** - Raw data from extraction (immutable archives)
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2. **materia-lakehouse** - Iceberg tables for SQLMesh (ACID transactions)
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### Hetzner Cloud Servers
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1. **materia-scheduler** (CCX12: 2 vCPU, 8GB RAM)
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- Runs cron scheduler
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- Lightweight orchestration tasks
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- Always-on, low cost (~€6/mo)
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2. **materia-worker-01** (CCX22: 4 vCPU, 16GB RAM)
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- Heavy SQLMesh transformations
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- Can be stopped when not in use
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- Scale up to CCX32/CCX42 for larger workloads (~€24-90/mo)
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3. **materia-firewall**
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- SSH access (port 22)
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- All outbound traffic allowed
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- No inbound HTTP/HTTPS (we're not running web services yet)
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## Enabling R2 Data Catalog (Iceberg)
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As of October 2025, R2 Data Catalog is in public beta. Enable it manually:
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1. Go to Cloudflare Dashboard → R2
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2. Select the `materia-lakehouse` bucket
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3. Navigate to Settings → Data Catalog
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4. Click "Enable Data Catalog"
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Once enabled, you can connect DuckDB to the Iceberg REST catalog:
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```python
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import duckdb
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# Get catalog URI from Pulumi outputs
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# pulumi stack output duckdb_r2_config
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conn = duckdb.connect()
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conn.execute("INSTALL iceberg; LOAD iceberg;")
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conn.execute(f"""
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ATTACH 'iceberg_rest://catalog.cloudflarestorage.com/<account_id>/r2-data-catalog'
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AS lakehouse (
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TYPE ICEBERG_REST,
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SECRET '<r2_api_token>'
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);
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""")
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```
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## Server Access
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Get server IPs from Pulumi outputs:
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```bash
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pulumi stack output scheduler_ip
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pulumi stack output worker_ip
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```
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SSH into servers:
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```bash
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ssh root@<scheduler_ip>
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ssh root@<worker_ip>
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```
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## Cost Estimates (Monthly)
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| Resource | Type | Cost |
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|----------|------|------|
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| R2 Storage | 10 GB | $0.15 |
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| R2 Operations | 1M reads | $0.36 |
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| R2 Egress | Unlimited | $0.00 (zero egress!) |
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| Scheduler | CCX12 | €6.00 |
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| Worker (on-demand) | CCX22 | €24.00 |
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| **Total** | | **~€30/mo (~$33)** |
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Compare to AWS equivalent: ~$300-500/mo with S3 + EC2 + egress fees.
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## Scaling Workers
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To add more worker capacity or different instance sizes:
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1. Edit `infra/__main__.py` to add new server resources
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2. Update worker config in `src/orchestrator/workers.yaml`
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3. Run `pulumi up` to provision
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Example worker sizes:
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- CCX12: 2 vCPU, 8GB RAM (light workloads)
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- CCX22: 4 vCPU, 16GB RAM (medium workloads)
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- CCX32: 8 vCPU, 32GB RAM (heavy workloads)
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- CCX42: 16 vCPU, 64GB RAM (very heavy workloads)
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## Destroying Infrastructure
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```bash
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cd infra
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pulumi destroy
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```
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**Warning:** This will delete all buckets and servers. Backup data first!
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## Next Steps
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1. Deploy orchestrator to scheduler server (see `src/orchestrator/README.md`)
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2. Configure SQLMesh to use R2 lakehouse (see `transform/sqlmesh_materia/config.yaml`)
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3. Set up CI/CD pipeline to deploy on push (see `.gitlab-ci.yml`)
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