GraphDB Deployment Options for Syntopica

Date: 2025-11-24 Status: Ready to Deploy

Overview

You now have 3 options for deploying GraphDB staging environment:

Option	Time	Effort	Flexibility	Recommended For
1. Custom Image (Packer)	5 min	Low	Medium	Production-like testing
2. Manual Deployment	2-3 hours	High	High	Learning, customization
3. Docker (Marketplace)	10 min	Low	Low	Quick testing

Option 1: Custom Image Deployment (Recommended ⭐)

Benefits

⚡ Fastest: 5 minutes from nothing to running server
🔒 Consistent: Same configuration every time
📦 Pre-built: GraphDB binary already compiled
🚀 Scalable: Deploy multiple instances instantly
✅ Tested: Image verified before use

Cost

Staging: $22/month (droplet $12 + volume $10)
Weekly backups: $7/month (4 weekly snapshots)
Image storage: $2.50/month (50GB snapshot)
Total: $31.50/month

Quick Start

# 1. Build image (one-time, ~15 minutes)
cd /home/ddowney/Workspace/github.com/graphdb/packer
export DIGITALOCEAN_API_TOKEN="your-token"
packer build graphdb-staging.pkr.hcl

# 2. Deploy from image (~5 minutes)
doctl compute droplet create graphdb-staging \
  --image <snapshot-id> \
  --size s-1vcpu-2gb \
  --region nyc1 \
  --ssh-keys <your-key>

# 3. Attach volume
doctl compute volume create graphdb-data --region nyc1 --size 100GiB
doctl compute volume-action attach <volume-id> <droplet-id>

# 4. SSH and mount
ssh root@<droplet-ip>
mkfs.ext4 -F /dev/disk/by-id/scsi-0DO_Volume_graphdb-data
mount -o discard,defaults /dev/disk/by-id/scsi-0DO_Volume_graphdb-data /mnt/graphdb-data
echo '/dev/disk/by-id/scsi-0DO_Volume_graphdb-data /mnt/graphdb-data ext4 defaults,nofail,discard 0 2' >> /etc/fstab
mkdir -p /mnt/graphdb-data/{data,wal,audit,backups}
chown -R graphdb:graphdb /mnt/graphdb-data

# 5. Start GraphDB
systemctl start graphdb
curl http://localhost:8080/health

# Done! 🎉

Documentation

Build guide: /home/ddowney/Workspace/github.com/graphdb/packer/README-CUSTOM-IMAGE.md
Packer template: /home/ddowney/Workspace/github.com/graphdb/packer/graphdb-staging.pkr.hcl

Option 2: Manual Deployment (Most Control)

Benefits

🎛️ Full control: Customize every step
📚 Educational: Learn how everything works
🔧 Flexible: Easy to modify on the fly
🐛 Debugging: Understand each component

Cost

Staging: $22/month (droplet $12 + volume $10)
Time investment: 2-3 hours first time, 30 min after practice

Quick Start

# Follow the comprehensive step-by-step guide
cat /home/ddowney/Workspace/github.com/graphdb/SYNTOPICA-STAGING-DEPLOYMENT.md

Documentation

Full deployment guide: /home/ddowney/Workspace/github.com/graphdb/SYNTOPICA-STAGING-DEPLOYMENT.md (1,020 lines)
Includes: Setup, configuration, monitoring, DR drill, troubleshooting

Option 3: Docker Deployment (Marketplace)

Benefits

🐳 Containerized: Isolation and portability
🛒 One-click: From DigitalOcean Marketplace (future)
🔄 Easy updates: Pull new image
📦 Self-contained: All dependencies in container

Cost

Staging: $22/month (droplet $12 + volume $10)
Overhead: Docker uses ~200MB RAM extra

Quick Start

# 1. Build marketplace image
cd /home/ddowney/Workspace/github.com/graphdb/packer
packer build graphdb.pkr.hcl

# 2. Deploy and use Docker Compose
ssh root@<droplet-ip>
cd /var/lib/graphdb
docker compose up -d

# Done!

Documentation

Marketplace template: /home/ddowney/Workspace/github.com/graphdb/packer/graphdb.pkr.hcl
Docker Compose: Included in image at /var/lib/graphdb/docker-compose.yml

Comparison Table

Feature	Custom Image	Manual	Docker
Deployment Time	5 min	2-3 hours	10 min
Memory Overhead	None	None	200MB
Performance	Native	Native	Container overhead
Flexibility	Medium	High	Low
Scalability	Excellent	Manual	Good
Updates	Rebuild image	Manual steps	Pull image
Complexity	Low	High	Low
Best For	Production-like	Learning	Quick tests

Recommendation for Syntopica Staging

Use Option 1: Custom Image Deployment ⭐

Why:

Speed: After initial 15-min build, deploy in 5 minutes
- Perfect for 48-hour soak test iterations
- Disaster recovery: spin up replacement in 60 seconds
Consistency: Eliminates "works on my machine" issues
- Same image for staging and production
- Reproducible deployments
Cost-effective: $2.50/month for image storage
- Time saved: ~2-3 hours per deployment
- After 2nd deployment, ROI is positive
Scalability: Need more GraphDB instances?
- Multi-region: Deploy to NYC, SFO, AMS instantly
- Load balancing: Multiple instances behind Cloudflare
Production-ready: This is how production systems are deployed
- Netflix, Spotify, GitHub all use custom images
- Industry best practice

Workflow:

# Week 1: Build image once
packer build graphdb-staging.pkr.hcl  # 15 minutes

# Weeks 2-52: Deploy instantly
doctl compute droplet create ... --image <snapshot-id>  # 60 seconds
# + 4 minutes for volume mount and start

# Test failed? Need fresh environment?
doctl compute droplet delete graphdb-staging-01
doctl compute droplet create graphdb-staging-01 --image <snapshot-id>
# Fresh environment in 5 minutes! 🚀

Decision Tree

Do you need GraphDB staging NOW (< 30 min)?
├─ YES: Have you built custom image already?
│  ├─ YES → Use Custom Image (5 min)
│  └─ NO → Use Docker (10 min), build custom image later
└─ NO: Want to learn or customize heavily?
   └─ YES → Use Manual Deployment (2-3 hours)

Next Steps: Building Custom Image

Phase 1: One-Time Setup (15 minutes)

# 1. Install Packer
brew install packer  # or download from packer.io

# 2. Install doctl
brew install doctl

# 3. Authenticate
doctl auth init  # Enter your DO API token
export DIGITALOCEAN_API_TOKEN="your-token"

# 4. Build image
cd /home/ddowney/Workspace/github.com/graphdb/packer
packer validate graphdb-staging.pkr.hcl
packer build graphdb-staging.pkr.hcl

# Wait ~15 minutes...
# Output: Snapshot ID (save this!)

Phase 2: Deploy Staging (5 minutes)

# 1. Create droplet from snapshot
doctl compute droplet create graphdb-staging \
  --image <snapshot-id> \
  --size s-1vcpu-2gb \
  --region nyc1 \
  --ssh-keys <your-key-id> \
  --enable-monitoring \
  --wait

# 2. Create and attach volume
doctl compute volume create graphdb-data --region nyc1 --size 100GiB
doctl compute volume-action attach <volume-id> <droplet-id>

# 3. Mount volume
ssh root@<droplet-ip>
mkfs.ext4 -F /dev/disk/by-id/scsi-0DO_Volume_graphdb-data
mount -o discard,defaults /dev/disk/by-id/scsi-0DO_Volume_graphdb-data /mnt/graphdb-data
echo '/dev/disk/by-id/scsi-0DO_Volume_graphdb-data /mnt/graphdb-data ext4 defaults,nofail,discard 0 2' >> /etc/fstab
mkdir -p /mnt/graphdb-data/{data,wal,audit,backups}
chown -R graphdb:graphdb /mnt/graphdb-data

# 4. Start services
systemctl start graphdb
systemctl status graphdb

# 5. Test
curl http://localhost:8080/health
# {"status":"healthy","uptime_seconds":5}

Phase 3: Cloudflare Tunnel (5 minutes)

# 1. Authenticate
cloudflared tunnel login

# 2. Create tunnel
cloudflared tunnel create graphdb-staging

# 3. Configure
vim /etc/cloudflared/config.yaml
# Update tunnel ID and hostname

# 4. Route DNS
cloudflared tunnel route dns graphdb-staging graphdb-staging.yourdomain.com

# 5. Start
systemctl start cloudflared
systemctl enable cloudflared

# 6. Test
curl https://graphdb-staging.yourdomain.com/health

Phase 4: Syntopica Integration (5 minutes)

# 1. Update Syntopica Workers
cd ~/Workspace/github.com/syntopica-v2/workers
npx wrangler secret put GRAPHDB_URL
# Enter: https://graphdb-staging.yourdomain.com

# 2. Deploy Workers
npx wrangler deploy --env staging

# 3. Sync data
curl -X POST https://staging.yourdomain.com/api/internal/sync/batch/all \
  -H "Authorization: Bearer $ADMIN_API_KEY"

# 4. Verify
curl https://graphdb-staging.yourdomain.com/stats | jq '.'
# {"nodes": 5000, "edges": 18000, ...}

Total time: 30 minutes (15 min build + 15 min deploy) Future deployments: 5 minutes (using existing image)

FAQ

Q: Can I use the custom image for production?

A: Yes! Just modify the Packer template:

Change size from s-1vcpu-2gb to s-2vcpu-4gb
Update environment variable to production
Build new image: packer build -var="environment=production" graphdb-staging.pkr.hcl

Q: How do I update GraphDB in the image?

A: Rebuild the image:

cd ~/Workspace/github.com/graphdb
git pull  # Get latest changes
cd packer
packer build graphdb-staging.pkr.hcl
# New snapshot created with latest code

Q: Can I customize the image before building?

A: Yes! Edit the Packer template:

Modify configuration templates in packer/config/
Add provisioning steps in graphdb-staging.pkr.hcl
Update scripts in packer/scripts/

Q: What if I need to deploy to multiple regions?

A: Update snapshot_regions in Packer template:

snapshot_regions = ["nyc1", "sfo3", "ams3", "lon1"]

Rebuild image - snapshot replicated to all regions automatically.

Q: How much does the custom image cost?

Snapshot storage: $0.05/GB/month
50GB image = $2.50/month
Each additional region snapshot = $2.50/month
Build time: $0.03 (15 min of temporary droplet)

Total: ~$2.50/month for single-region, ~$10/month for 4 regions

All Documentation Files

DEPLOYMENT-OPTIONS.md (this file) - Overview of all options
SYNTOPICA-STAGING-DEPLOYMENT.md - Manual deployment guide (1,020 lines)
packer/README-CUSTOM-IMAGE.md - Custom image guide
packer/graphdb-staging.pkr.hcl - Staging image template
packer/graphdb.pkr.hcl - Marketplace/Docker image template
FUZZING-E2E-SUMMARY.md - Testing improvements summary
GOCERT-VERIFICATION-REPORT.md - Formal verification findings
GOCERT-FIX-SUMMARY.md - Critical bug fix summary

Summary

You're ready to deploy GraphDB staging!

Fastest path to running system:

Build custom image: 15 minutes
Deploy to DigitalOcean: 5 minutes
Setup Cloudflare Tunnel: 5 minutes
Integrate Syntopica: 5 minutes
Total: 30 minutes to fully operational staging environment

Then:

Run 48-hour soak test with real Syntopica workload
Perform DR drill (backup/restore)
Validate production readiness

Production readiness: 75% → 80%+ after soak test and DR drill ✅

Ready to start?

cd /home/ddowney/Workspace/github.com/graphdb/packer
cat README-CUSTOM-IMAGE.md  # Read the guide
packer build graphdb-staging.pkr.hcl  # Build the image!

Author: Claude Code Last Updated: 2025-11-24 Status: Ready to Deploy 🚀

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GraphDB Deployment Options for Syntopica

Overview

Option 1: Custom Image Deployment (Recommended ⭐)

Benefits

Cost

Quick Start

Documentation

Option 2: Manual Deployment (Most Control)

Benefits

Cost

Quick Start

Documentation

Option 3: Docker Deployment (Marketplace)

Benefits

Cost

Quick Start

Documentation

Comparison Table

Recommendation for Syntopica Staging

Use Option 1: Custom Image Deployment ⭐

Decision Tree

Next Steps: Building Custom Image

Phase 1: One-Time Setup (15 minutes)

Phase 2: Deploy Staging (5 minutes)

Phase 3: Cloudflare Tunnel (5 minutes)

Phase 4: Syntopica Integration (5 minutes)

FAQ

Q: Can I use the custom image for production?

Q: How do I update GraphDB in the image?

Q: Can I customize the image before building?

Q: What if I need to deploy to multiple regions?

Q: How much does the custom image cost?

All Documentation Files

Summary