learning_ai_common_plat/docs/devops/single_azure_vm/docker

ByteLyst Single-VM Deployment

Deploy the entire ByteLyst ecosystem (31 services, 11 products) on a single raw Azure VM. Nothing pre-installed required — the script handles everything from a blank Ubuntu machine. Two files: this README and setup.sh. Copy both to the VM and run the script.

Related:

• SECURE_API_EXPOSURE.md — recommended public API exposure model, alternatives, and security guidance for client-facing URLs
• DEPLOYMENT_STATUS_2026-03-29.md — deployment snapshot: what completed on the Azure VM, what was manually fixed, and what remains

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Prerequisites

• Azure VM: Ubuntu 24.04 LTS (or 22.04), Standard_D8s_v5 (8 vCPU, 32 GB RAM) recommended
• Disk: 128 GB+ (Docker images, Cosmos emulator, Ollama models, build artifacts)
• Network: NSG allowing inbound on ports: 22, 80, 1025, 1234, 3000-3003, 3030, 3035, 3040, 3045, 3050, 3055, 3060, 3070, 3075, 3100, 3300, 4003, 4005, 4007, 4010-4019, 8025, 8080, 10000, 11434
• GitHub access: Repos must be accessible (public or GITHUB_TOKEN for private)
• Nothing else needed — the script installs Docker, Node.js, pnpm, Gitea, Ollama, and everything

Quick Start

# 1. SSH into your Azure VM
ssh azureuser@<vm-ip>

# 2. Copy setup.sh and make executable
chmod +x setup.sh

# 3. Run — provide your GitHub username (repos are cloned via HTTPS)
#    If repos are private, also export GITHUB_TOKEN first.
sudo ./setup.sh

# 4. Wait ~15-25 minutes for full build + deploy

# 5. Verify
/opt/bytelyst/check-health.sh

Resume & Retry

Phase completion is tracked. If anything fails, you don't have to start over:

sudo ./setup.sh --phase=7          # Retry just the deploy phase
sudo ./setup.sh --resume           # Auto-resume after SSH disconnect
sudo ./setup.sh --resume-from=7    # Jump to deploy after manual fix
sudo ./setup.sh --status           # Check what's done
sudo ./setup.sh --reset            # Start completely over
sudo ./setup.sh --help             # Show full usage

What the Script Installs & Does

Software installed on the VM (from scratch)

Software	Version	Purpose
Docker CE	latest	Container runtime + Compose + BuildKit
Node.js	22 LTS	Build toolchain for TypeScript packages
pnpm	10.6.5	Package manager (workspace-aware)
Gitea	1.22 (Docker)	Local npm package registry on :3300
Ollama	latest	Local LLM inference for LocalMemGPT on :11434
git, jq, curl	latest	System utilities

Execution phases

Phase	Duration	Description
1. System	~3 min	Pre-flight checks (disk ≥40 GB, RAM ≥16 GB), install Docker, Node.js 22, pnpm 10.6.5, Ollama, git, jq, build-essential
2. Gitea + CI	~2 min	Start Gitea Docker container, admin + org + token, install act_runner
3. Clone	~3 min	Clone all 12 repos to /opt/bytelyst/, push to Gitea for CI
4. Build	~5 min	pnpm install && pnpm -r build all @bytelyst/* packages
5. Publish	~3 min	Publish all packages to local Gitea npm registry
6. Env	instant	Generate .env.ecosystem with Cosmos emulator key, Azurite key, JWT secret
7. Deploy	~10 min	Stop Ollama (free RAM), per-service Docker build + deploy (31 services, with fallback), prune build cache, restart Ollama
8. Verify	~1 min	Health-check all 31+ endpoints + create /opt/bytelyst/check-health.sh

Port Map (after deployment)

Infrastructure (installed by setup.sh)

Service	Port	URL
Gitea (npm registry)	3300	http://<vm-ip>:3300
Ollama (LLM API)	11434	http://<vm-ip>:11434
Cosmos Data Explorer	1234	http://<vm-ip>:1234
Azurite (Blob)	10000	http://<vm-ip>:10000
Mailpit UI	8025	http://<vm-ip>:8025
Loki (Logs)	3100	http://<vm-ip>:3100/ready
Grafana	3000	http://<vm-ip>:3000
Traefik Dashboard	8080	http://<vm-ip>:8080

Platform Services

Service	Port	URL
platform-service	4003	http://<vm-ip>:4003/health
extraction-service	4005	http://<vm-ip>:4005/health
mcp-server	4007	http://<vm-ip>:4007/health

Platform Dashboards

Dashboard	Port	URL
Admin Console	3001	http://<vm-ip>:3001
Issue Tracker	3003	http://<vm-ip>:3003

Product Backends

Product	Port	Health
PeakPulse	4010	http://<vm-ip>:4010/health
ChronoMind	4011	http://<vm-ip>:4011/health
JarvisJr	4012	http://<vm-ip>:4012/health
NomGap	4013	http://<vm-ip>:4013/health
MindLyst	4014	http://<vm-ip>:4014/health
LysnrAI	4015	http://<vm-ip>:4015/health
NoteLett	4016	http://<vm-ip>:4016/health
FlowMonk	4017	http://<vm-ip>:4017/health
ActionTrail	4018	http://<vm-ip>:4018/health
LocalMemGPT	4019	http://<vm-ip>:4019/health

Product Web Apps

Product	Port	URL
LysnrAI Dashboard	3002	http://<vm-ip>:3002
ChronoMind	3030	http://<vm-ip>:3030
JarvisJr	3035	http://<vm-ip>:3035
FlowMonk	3040	http://<vm-ip>:3040
NoteLett	3045	http://<vm-ip>:3045
MindLyst	3050	http://<vm-ip>:3050
NomGap	3055	http://<vm-ip>:3055
ActionTrail	3060	http://<vm-ip>:3060
LocalMemGPT	3070	http://<vm-ip>:3070
LLM Lab Dashboard	3075	http://<vm-ip>:3075

Post-Deployment Commands

# Check all service health
/opt/bytelyst/check-health.sh

# View logs for a specific service
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml \
  logs -f platform-service

# Restart a specific service
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml \
  restart flowmonk-backend

# Stop everything
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml down

# Stop and wipe all data
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml down -v

Environment Variables

All optional — defaults work for most setups:

Variable	Default	Description
GITHUB_USER	saravanakumardb1	GitHub org/user to clone repos from
GITHUB_TOKEN	(empty)	Set for private repos (HTTPS auth)
GITEA_ADMIN	bytelyst-admin	Gitea admin username
GITEA_PASS	ByteLyst2026!	Gitea admin password
OLLAMA_MODEL	llama3.2:3b	Default LLM model to pull
SKIP_CLONE	0	Set 1 to skip cloning (re-runs)
SKIP_BUILD	0	Set 1 to skip package build+publish (re-runs)

CLI Flags

Flag	Description
--resume	Auto-resume from last completed phase
--resume-from=N	Resume from phase N (1-8)
--phase=N	Run ONLY phase N (useful for retrying)
--dry-run	Validate prerequisites without building or deploying
--reset	Clear phase markers and start fresh
--status	Show completed phases and exit
-h, --help	Show usage help

Troubleshooting

• Cosmos emulator slow: It needs 20-30s on first boot. Services wait via health checks.
• Out of memory: Use at least 32 GB RAM. Cosmos emulator needs ~4 GB, Ollama needs ~4 GB for 3B models.
• Build failures: Check Gitea is running (docker ps | grep gitea) and packages published (curl http://localhost:3300/api/packages/bytelyst/npm/). Per-service build logs: /opt/bytelyst/.setup-state/builds/<service>.log. Retry: sudo ./setup.sh --phase=7.
• Ollama not responding: Check systemctl status ollama or curl http://localhost:11434/api/version.
• Port conflicts: Ensure nothing else runs on the listed ports before deploying.
• CORS errors in browser: The generated .env.ecosystem sets CORS_ORIGIN=* for dev/test. If you restrict it, update the value to match your access URL.
• Services in development mode: .env.ecosystem now sets NODE_ENV=production for all services. If you need debug logging, remove or change this value.

HTTPS Gateway

• Public backend access is intended to flow through Caddy on https://api.bytelyst.com, not direct backend port exposure.
• The gateway config lives at /opt/bytelyst/Caddyfile and is mounted into the caddy container.
• Backend routes are path-based and strip their prefixes before proxying:
  • /platform/* → platform-service:4003
  • /extraction/* → extraction-service:4005
  • /mcp/* → mcp-server:4007
  • /peakpulse/* → peakpulse-backend:4010
  • /chronomind/* → chronomind-backend:4011
  • /jarvisjr/* → jarvisjr-backend:4012
  • /nomgap/* → nomgap-backend:4013
  • /mindlyst/* → mindlyst-backend:4014
  • /lysnrai/* → lysnrai-backend:4015
  • /notelett/* → notelett-backend:4016
  • /flowmonk/* → flowmonk-backend:4017
  • /actiontrail/* → actiontrail-backend:4018
  • /localmemgpt/* → localmemgpt-backend:4019
• Keep backend ports closed publicly once DNS and NSG rules are aligned. Docker-internal service discovery remains unchanged.

Known Limitations

• Remote browser access: Product web apps use http://localhost:<port> for browser-side API calls (baked at Next.js build time via NEXT_PUBLIC_* args). This works when browsing from the VM itself but not from a remote browser (e.g., laptop accessing http://<vm-ip>:3060). For remote access, use SSH port-forwarding:

  # Forward all product ports to your laptop (run from your laptop)
  ssh -N -L 3001:localhost:3001 -L 3002:localhost:3002 -L 3030:localhost:3030 \
    -L 3035:localhost:3035 -L 3040:localhost:3040 -L 3045:localhost:3045 \
    -L 3050:localhost:3050 -L 3055:localhost:3055 -L 3060:localhost:3060 \
    -L 3070:localhost:3070 -L 3075:localhost:3075 \
    -L 4003:localhost:4003 -L 4010:localhost:4010 -L 4011:localhost:4011 \
    -L 4012:localhost:4012 -L 4013:localhost:4013 -L 4014:localhost:4014 \
    -L 4015:localhost:4015 -L 4016:localhost:4016 -L 4017:localhost:4017 \
    -L 4018:localhost:4018 -L 4019:localhost:4019 \
    azureuser@<vm-ip>
  

  Then open http://localhost:3060 etc. on your laptop. Server-side code (API routes, SSR) uses Docker service names and works regardless.
• Cosmos emulator is x86-only: Do not use ARM-based VMs (e.g., Dpsv6). Stick with Standard_D8s_v5 or similar Intel/AMD instances.
• Memory pressure: Phase 7 automatically stops Ollama (~3 GB) during Docker builds and restarts it after. If builds still OOM on 32 GB, retry with sudo ./setup.sh --phase=7 (per-service fallback skips what already built).
• Corporate proxy in Dockerfiles: Already removed at source across all repos. No runtime stripping needed.