CLOUD PROVIDERS - nself-org/cli GitHub Wiki

Multi-Cloud Deployment Guide

Version: 0.4.8+ | Last Updated: January 30, 2026

Overview

nself supports deployment to 26+ cloud providers with custom services fully integrated. This guide covers provider-specific configurations, optimization strategies, and best practices for deploying custom services (CS_N) to production cloud infrastructure.

Table of Contents

  1. Provider Categories
  2. Major Cloud Providers
  3. Developer Cloud Providers
  4. Budget EU Providers
  5. Multi-Cloud Strategies
  6. Cost Optimization
  7. Auto-Scaling Configuration
  8. Load Balancer Setup
  9. Provider-Specific Examples

Provider Categories

Category Providers Best For
Major Cloud AWS, GCP, Azure, Oracle, IBM Enterprise, compliance, global scale
Developer Cloud DigitalOcean, Linode, Vultr, Scaleway, UpCloud Simplicity, predictable pricing
Budget EU Hetzner, Contabo, OVH, Netcup, IONOS Best value, GDPR compliance
Budget Global BuyVM, RackNerd, Hosthatch, Dediserve Ultra-low cost
Regional Tencent, Alibaba, Yandex, Selectel China, Russia, specific regions

Major Cloud Providers

Amazon Web Services (AWS)

Overview

Attribute Value
Best For Enterprise, complex architectures, massive scale
Compute Options EC2, ECS, EKS, Fargate
Managed K8s EKS (Elastic Kubernetes Service)
Starting Price ~$8/mo (t3.micro)
Free Tier 750 hours/mo EC2 for 12 months

Provision Server

# Initialize AWS provider
nself infra provider init aws

# Provision EC2 instance for Docker Compose
nself infra provider server create aws --size medium --region us-east-1

# This creates:
# - t3.medium (2 vCPU, 4GB RAM)
# - 50GB SSD storage
# - Security groups configured
# - SSH key pair generated

Deploy Custom Services

# Deploy to AWS EC2
nself deploy production

# Custom services deploy via Docker Compose
# All CS_N services included automatically

Deploy to EKS (Kubernetes)

# Create EKS cluster
aws eks create-cluster \
  --name myapp-prod \
  --role-arn arn:aws:iam::123456789012:role/eks-service-role \
  --resources-vpc-config subnetIds=subnet-xxx,subnet-yyy

# Configure kubectl
aws eks update-kubeconfig --name myapp-prod --region us-east-1

# Convert and deploy
nself infra k8s convert
nself infra k8s deploy --env production

# Custom services deploy as K8s Deployments with:
# - Auto-scaling (HPA)
# - Load balancing (ALB)
# - Health checks
# - Rolling updates

Cost Optimization

# Use Spot Instances for workers
nself infra provider server create aws --spot --size large

# Use ARM instances (Graviton2) - 20% cheaper
nself infra provider server create aws --architecture arm64 --size medium

# Reserved Instances for production
# Save 30-40% with 1-year commitment

Auto-Scaling

# EKS with Cluster Autoscaler
nself infra k8s scale payment-api --auto \
  --min 3 --max 20 \
  --cpu 70

# EC2 Auto Scaling Group
aws autoscaling create-auto-scaling-group \
  --auto-scaling-group-name myapp-asg \
  --min-size 2 --max-size 10 \
  --desired-capacity 3

Load Balancer

# Application Load Balancer
aws elbv2 create-load-balancer \
  --name myapp-alb \
  --subnets subnet-xxx subnet-yyy \
  --security-groups sg-xxx

# Configure target groups for custom services
aws elbv2 create-target-group \
  --name payment-api-tg \
  --protocol HTTP \
  --port 8001 \
  --vpc-id vpc-xxx \
  --health-check-path /health

Monitoring

  • CloudWatch metrics (automatic)
  • nself monitoring bundle (Prometheus/Grafana)
  • X-Ray for distributed tracing

Example Production Setup

# Complete AWS production deployment

# 1. Provision infrastructure
nself infra provider server create aws \
  --size large \
  --region us-east-1 \
  --high-availability \
  --backup-enabled

# 2. Configure environment
nself config env create prod prod

# 3. Generate secrets
nself config secrets generate --env prod

# 4. Deploy
nself deploy production

# Services deployed:
# - Core: PostgreSQL, Hasura, Auth, Nginx
# - Custom: payment-api, notification-worker, analytics-api
# - Monitoring: Prometheus, Grafana, Loki

Google Cloud Platform (GCP)

Overview

Attribute Value
Best For ML/AI workloads, data analytics, BigQuery
Compute Options Compute Engine, GKE, Cloud Run
Managed K8s GKE (Google Kubernetes Engine)
Starting Price ~$6/mo (e2-micro)
Free Tier e2-micro always free

Provision Server

# Initialize GCP
nself infra provider init gcp

# Provision VM instance
nself infra provider server create gcp --size medium --region us-central1

# Creates:
# - e2-medium (2 vCPU, 4GB)
# - 50GB SSD boot disk
# - Firewall rules configured

Deploy to GKE

# Create GKE cluster
gcloud container clusters create myapp-prod \
  --num-nodes=3 \
  --machine-type=e2-standard-2 \
  --region=us-central1

# Get credentials
gcloud container clusters get-credentials myapp-prod --region us-central1

# Deploy custom services
nself infra k8s convert
nself infra k8s deploy --env production

Cost Optimization

# Use preemptible VMs (80% cheaper)
nself infra provider server create gcp --preemptible --size medium

# Use committed use discounts
# Save 37% with 1-year commitment

# Use Google's free tier
nself infra provider server create gcp --size micro  # Always free

Auto-Scaling

# GKE Autopilot mode (fully managed)
gcloud container clusters create myapp-auto \
  --enable-autoscaling \
  --min-nodes=2 --max-nodes=10

# Custom service auto-scaling
nself infra k8s scale payment-api --auto \
  --min 2 --max 15 \
  --cpu 70 --memory 80

Load Balancer

# Cloud Load Balancing (automatic with GKE)
# Configured via Ingress resource

# nself generates Ingress automatically
# Access at: payment-api.example.com

Monitoring

  • Cloud Monitoring (Stackdriver)
  • nself monitoring bundle
  • Cloud Trace for distributed tracing

Microsoft Azure

Overview

Attribute Value
Best For Microsoft stack, enterprise, hybrid cloud
Compute Options Virtual Machines, AKS, Container Instances
Managed K8s AKS (Azure Kubernetes Service)
Starting Price ~$7/mo (B1s)
Free Tier 750 hours B1s for 12 months

Provision Server

# Initialize Azure
nself infra provider init azure

# Provision VM
nself infra provider server create azure --size medium --region eastus

# Creates:
# - Standard_B2s (2 vCPU, 4GB)
# - 50GB SSD
# - Network security group

Deploy to AKS

# Create AKS cluster
az aks create \
  --resource-group myapp-rg \
  --name myapp-aks \
  --node-count 3 \
  --node-vm-size Standard_D2s_v3

# Get credentials
az aks get-credentials --resource-group myapp-rg --name myapp-aks

# Deploy
nself infra k8s deploy --env production

Cost Optimization

# Use Spot VMs
nself infra provider server create azure --spot --size large

# Use Azure reservations
# Save 40% with 1-year commitment

Auto-Scaling

# AKS cluster autoscaler
az aks update \
  --resource-group myapp-rg \
  --name myapp-aks \
  --enable-cluster-autoscaler \
  --min-count 2 --max-count 10

Oracle Cloud Infrastructure (OCI)

Overview

Attribute Value
Best For Budget workloads, ARM development, always free tier
Free Tier 2 AMD VMs + 4 ARM cores FOREVER
Compute Options Compute VMs, OKE (Kubernetes), Container Instances
Starting Price FREE

Provision Server (Free Tier)

# Initialize Oracle Cloud
nself infra provider init oracle

# Provision FREE VM (amazing value)
nself infra provider server create oracle --size free

# This gives you:
# - 2 AMD VMs (1GB each) OR 1 ARM VM (4 cores, 24GB)
# - 200GB storage
# - 10TB bandwidth/month
# - FOREVER FREE

Deploy Custom Services

# Use ARM VM for best free tier value
nself infra provider server create oracle --size free --arm

# Deploy normally
nself deploy production

# You get full nself stack + custom services for FREE:
# - PostgreSQL, Hasura, Auth, Nginx
# - payment-api, notification-worker
# - Redis, monitoring (optional)

ARM Optimization

Oracle's ARM instances are powerful and free:

# Optimize Dockerfile for ARM
FROM --platform=linux/arm64 node:18-alpine

# Build for ARM
docker buildx build --platform linux/arm64 -t payment-api .

Cost (After Free Tier)

# Paid instances
nself infra provider server create oracle --size small  # ~$10/mo
nself infra provider server create oracle --size medium # ~$30/mo

Developer Cloud Providers

DigitalOcean

Overview

Attribute Value
Best For Developer experience, simple pricing, great docs
Compute Options Droplets, DOKS (Kubernetes), App Platform
Starting Price $6/mo
Free Credit $200 for 60 days

Provision Droplet

# Initialize DigitalOcean
nself infra provider init digitalocean

# Provision droplet
nself infra provider server create digitalocean --size medium --region nyc1

# Creates:
# - 4GB RAM, 2 vCPU
# - 80GB SSD
# - 4TB bandwidth
# - Backups enabled (optional)

Deploy Custom Services

# Deploy via Docker Compose
nself deploy production

# All custom services included:
# - CS_1: payment-api
# - CS_2: notification-worker
# - CS_3: analytics-api

Deploy to DOKS (Kubernetes)

# Create Kubernetes cluster
doctl kubernetes cluster create myapp-prod \
  --count 3 \
  --size s-2vcpu-4gb \
  --region nyc1

# Deploy custom services
nself infra k8s convert
nself infra k8s deploy --env production

# Custom services get:
# - Load balancing (via LoadBalancer service)
# - Auto-scaling (HPA)
# - Persistent volumes

Cost Optimization

# Right-size your droplet
# Start small, scale up as needed
nself infra provider server create digitalocean --size small  # $6/mo

# Use snapshots for backup (cheaper than backups)
doctl compute snapshot create --droplet-id <id>

# Reserved instances available (no commitment period)

Monitoring

  • DigitalOcean monitoring (free, basic)
  • nself monitoring bundle (advanced)

Production Example

# Recommended production setup

# 1. Provision droplet
nself infra provider server create digitalocean \
  --size dedicated-cpu-2 \
  --region nyc1 \
  --vpc myapp-vpc \
  --tag production

# 2. Setup
nself config env create prod prod
nself config secrets generate --env prod

# 3. Deploy
nself deploy production

# Cost: ~$48/mo for 2 dedicated vCPU, 4GB RAM

Linode (Akamai)

Overview

Attribute Value
Best For Reliable VPS, good support, Akamai CDN
Compute Options Linodes, LKE (Kubernetes)
Starting Price $5/mo (Nanode)
Free Credit $100 for 60 days

Provision Linode

# Initialize Linode
nself infra provider init linode

# Provision server
nself infra provider server create linode --size medium --region us-east

# Creates:
# - 4GB RAM, 2 vCPU
# - 80GB SSD
# - 4TB bandwidth

Deploy Custom Services

nself deploy production
# Custom services deploy normally via Docker Compose

Deploy to LKE

# Create Kubernetes cluster
linode-cli lke cluster-create \
  --label myapp-prod \
  --region us-east \
  --k8s_version 1.28

# Deploy
nself infra k8s deploy --env production

Vultr

Overview

Attribute Value
Best For Global coverage (32 locations), bare metal options
Compute Options Cloud Compute, VKE (Kubernetes), Bare Metal
Starting Price $5/mo ($2.50 for IPv6-only)
Free Credit $250 for 30 days

Provision Server

# Initialize Vultr
nself infra provider init vultr

# Provision instance
nself infra provider server create vultr --size medium --region ewr

# High-frequency compute (better CPU)
nself infra provider server create vultr --size high-frequency --region ewr

# Bare metal (dedicated hardware)
nself infra provider server create vultr --bare-metal --size bm-small

Global Deployment

Vultr has 32+ locations worldwide:

# Deploy to multiple regions
nself infra provider server create vultr --size medium --region ewr  # Newark
nself infra provider server create vultr --size medium --region lax  # Los Angeles
nself infra provider server create vultr --size medium --region fra  # Frankfurt
nself infra provider server create vultr --size medium --region sgp  # Singapore

# Setup geo-routing with CloudFlare or Route53

Hetzner Cloud

Overview

Attribute Value
Best For BEST price/performance ratio in industry
Compute Options Cloud Servers, Dedicated Servers
Starting Price €3.29/mo (~$3.50) for 2GB RAM
Bandwidth 20TB included (most generous)

Provision Server

# Initialize Hetzner
nself infra provider init hetzner

# Provision cloud server
nself infra provider server create hetzner --size medium --region fsn1

# Creates CX21:
# - 2 vCPU
# - 4GB RAM
# - 40GB SSD
# - 20TB bandwidth
# - Cost: €5.83/mo (~$6.20)

Deploy Custom Services

nself deploy production

# Hetzner's value makes it perfect for:
# - Multiple custom services
# - Heavy bandwidth usage
# - Cost-conscious production

Production Recommendation

# Best value production setup
nself infra provider server create hetzner --size large --region fsn1

# CX31:
# - 2 vCPU
# - 8GB RAM
# - 80GB SSD
# - 20TB bandwidth
# - €11.90/mo (~$12.70)

# Can easily run:
# - Core services
# - 4-6 custom services
# - Full monitoring stack
# - All for ~$13/mo

Dedicated Servers

# Even better value for high-traffic apps
nself infra provider server create hetzner --dedicated --size ax41-nvme

# AX41-NVMe:
# - AMD Ryzen 5 3600 (6 cores, 12 threads)
# - 64GB RAM
# - 2x 512GB NVMe SSD
# - 20TB bandwidth
# - €49/mo (~$52)

Multi-Cloud Strategies

Active-Active Multi-Cloud

Deploy to multiple providers for redundancy:

# Region 1: AWS US-East (primary)
nself infra provider server create aws --region us-east-1
nself config env create prod-aws prod
nself deploy prod-aws

# Region 2: GCP US-Central (secondary)
nself infra provider server create gcp --region us-central1
nself config env create prod-gcp prod
nself deploy prod-gcp

# Region 3: Hetzner EU (tertiary)
nself infra provider server create hetzner --region fsn1
nself config env create prod-eu prod
nself deploy prod-eu

Setup geo-routing with CloudFlare:

// CloudFlare Workers for geo-routing
export default {
  async fetch(request) {
    const country = request.cf.country;

    // Route by geography
    if (country === 'US') {
      return fetch('https://api-aws.example.com' + request.url.pathname);
    } else if (country in ['DE', 'FR', 'GB', 'IT', 'ES']) {
      return fetch('https://api-hetzner.example.com' + request.url.pathname);
    } else {
      return fetch('https://api-gcp.example.com' + request.url.pathname);
    }
  }
}

Active-Passive (DR)

# Primary: DigitalOcean
nself deploy production

# Disaster Recovery: Vultr (standby)
nself config env create prod-dr prod
nself deploy prod-dr

# Automated failover with health checks

Hybrid Cloud

# On-premises: Core database
# Cloud: Custom services + APIs

# Deploy custom services to cloud
nself infra provider server create aws --size large
CS_1=payment-api:express-ts:8001 nself deploy production

# Connect to on-prem database
POSTGRES_HOST=on-prem.example.com
POSTGRES_PORT=5432

Cost Optimization

Provider Price Comparison

Monthly cost for running nself + 4 custom services (4GB RAM, 2 vCPU):

Provider Instance RAM vCPU Price/mo Bandwidth
Hetzner CX21 4GB 2 $6.20 20TB ⭐
Vultr Regular 4GB 2 $12 3TB
Linode 4GB 4GB 2 $24 4TB
DigitalOcean Basic 4GB 2 $24 4TB
Oracle Free Tier 24GB 4 FREE 10TB ⭐⭐
AWS t3.medium 4GB 2 $30 100GB + $0.09/GB
GCP e2-medium 4GB 2 $32 100GB + $0.12/GB
Azure B2s 4GB 2 $34 100GB + $0.087/GB

Winner for value:

  1. Oracle (FREE tier - unbeatable)
  2. Hetzner (best price/performance)
  3. Vultr (good global coverage + value)

Cost Optimization Strategies

1. Right-Sizing

Start small, scale up as needed:

# Start with small instance
nself infra provider server create hetzner --size small  # 2GB RAM, $3.50/mo

# Monitor resource usage
nself metrics

# Scale up when needed
nself infra provider server create hetzner --size medium  # 4GB RAM, $6.20/mo

2. Spot/Preemptible Instances

Save 60-80% for fault-tolerant workloads:

# AWS Spot
nself infra provider server create aws --spot --size large

# GCP Preemptible
nself infra provider server create gcp --preemptible --size large

# Good for:
# - Background workers
# - Batch processing
# - Development/staging

3. Reserved/Committed Instances

Save 30-40% with commitment:

# AWS Reserved Instances (1-3 years)
# GCP Committed Use Discounts
# Azure Reserved VM Instances

# Best for: Production workloads with predictable usage

4. ARM Architecture

Save 20% with ARM instances:

# AWS Graviton2
nself infra provider server create aws --architecture arm64

# Oracle Always Free ARM (4 cores, 24GB!)
nself infra provider server create oracle --size free --arm

# Build multi-arch images
docker buildx build --platform linux/amd64,linux/arm64 -t payment-api .

5. Bandwidth Optimization

  • Choose providers with generous bandwidth (Hetzner: 20TB, Oracle: 10TB free)
  • Use CDN for static assets (CloudFlare, Fastly)
  • Compress responses (gzip)
  • Cache aggressively

6. Storage Optimization

# Use object storage for files (cheaper than block storage)
MINIO_ENABLED=true nself deploy production

# Or use provider object storage
# - AWS S3
# - GCP Cloud Storage
# - DigitalOcean Spaces

Auto-Scaling Configuration

Docker Compose (Single Server)

Limited auto-scaling, but can use resource limits:

# docker-compose.yml
services:
  payment_api:
    deploy:
      replicas: 3
      resources:
        limits:
          cpus: '1.0'
          memory: 512M
        reservations:
          cpus: '0.5'
          memory: 256M

Kubernetes (All Providers)

Full horizontal pod autoscaling:

# Scale based on CPU
nself infra k8s scale payment-api --auto \
  --min 2 --max 10 \
  --cpu 70

# Scale based on memory
nself infra k8s scale payment-api --auto \
  --min 2 --max 10 \
  --memory 80

# Scale based on custom metrics
nself infra k8s scale payment-api --auto \
  --min 2 --max 10 \
  --custom 'http_requests_per_second>100'

Provider-Specific Auto-Scaling

AWS

# ECS Service Auto Scaling
aws application-autoscaling register-scalable-target \
  --service-namespace ecs \
  --scalable-dimension ecs:service:DesiredCount \
  --resource-id service/myapp/payment-api \
  --min-capacity 2 \
  --max-capacity 10

# Scaling policy
aws application-autoscaling put-scaling-policy \
  --policy-name payment-api-cpu-scaling \
  --service-namespace ecs \
  --scalable-dimension ecs:service:DesiredCount \
  --resource-id service/myapp/payment-api \
  --policy-type TargetTrackingScaling \
  --target-tracking-scaling-policy-configuration \
    "PredefinedMetricSpecification={PredefinedMetricType=ECSServiceAverageCPUUtilization},TargetValue=70.0"

GCP

# Managed Instance Group Auto Scaling
gcloud compute instance-groups managed set-autoscaling myapp-mig \
  --max-num-replicas 10 \
  --min-num-replicas 2 \
  --target-cpu-utilization 0.70 \
  --cool-down-period 60

DigitalOcean

# DOKS HPA
kubectl autoscale deployment payment-api \
  --cpu-percent=70 \
  --min=2 \
  --max=10

Load Balancer Setup

Nginx (Built-in)

nself includes Nginx for load balancing:

# nginx/sites/payment-api.conf (auto-generated)
upstream payment_api_backend {
    least_conn;
    server payment_api_1:8001 max_fails=3 fail_timeout=30s;
    server payment_api_2:8001 max_fails=3 fail_timeout=30s;
    server payment_api_3:8001 max_fails=3 fail_timeout=30s;
}

server {
    listen 443 ssl http2;
    server_name payment-api.example.com;

    ssl_certificate /etc/letsencrypt/live/example.com/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/example.com/privkey.pem;

    location / {
        proxy_pass http://payment_api_backend;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_cache_bypass $http_upgrade;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;

        # Health checks
        proxy_next_upstream error timeout http_502 http_503 http_504;
    }
}

Provider Load Balancers

AWS Application Load Balancer

# Create ALB
aws elbv2 create-load-balancer \
  --name myapp-alb \
  --subnets subnet-xxx subnet-yyy \
  --security-groups sg-xxx

# Create target group for each custom service
aws elbv2 create-target-group \
  --name payment-api-tg \
  --protocol HTTP \
  --port 8001 \
  --vpc-id vpc-xxx \
  --health-check-enabled \
  --health-check-path /health \
  --health-check-interval-seconds 30 \
  --health-check-timeout-seconds 5 \
  --healthy-threshold-count 2 \
  --unhealthy-threshold-count 3

GCP Cloud Load Balancing

# Create backend service
gcloud compute backend-services create payment-api-backend \
  --protocol HTTP \
  --health-checks payment-api-health \
  --global

# Add instance group
gcloud compute backend-services add-backend payment-api-backend \
  --instance-group myapp-ig \
  --instance-group-zone us-central1-a \
  --global

DigitalOcean Load Balancer

# Create load balancer
doctl compute load-balancer create \
  --name myapp-lb \
  --region nyc1 \
  --forwarding-rules entry_protocol:https,entry_port:443,target_protocol:http,target_port:8001 \
  --health-check protocol:http,port:8001,path:/health \
  --tag-name payment-api

Provider-Specific Examples

Complete AWS Production Setup

#!/bin/bash
# Complete AWS production deployment with custom services

# 1. Initialize AWS
nself infra provider init aws
export AWS_REGION=us-east-1

# 2. Provision infrastructure
nself infra provider server create aws \
  --size large \
  --region $AWS_REGION \
  --high-availability \
  --multi-az

# 3. Setup environment
nself config env create prod prod

# 4. Configure custom services
cat > .environments/prod/.env <<EOF
ENV=prod
PROJECT_NAME=myapp
BASE_DOMAIN=example.com

# Custom Services
CS_1=payment-api:express-ts:8001
CS_2=notification-worker:bullmq-js:8002
CS_3=analytics-api:fastapi:8003
CS_4=ml-inference:fastapi:8004

# Enable monitoring
MONITORING_ENABLED=true
REDIS_ENABLED=true
MINIO_ENABLED=true
EOF

# 5. Generate secrets
nself config secrets generate --env prod

# 6. Add custom secrets
cat >> .environments/prod/.env.secrets <<EOF
PAYMENT_API_STRIPE_SECRET_KEY=sk_live_...
NOTIFICATION_WORKER_SENDGRID_API_KEY=SG....
ANALYTICS_API_CLICKHOUSE_PASSWORD=...
ML_INFERENCE_S3_SECRET_KEY=...
EOF

chmod 600 .environments/prod/.env.secrets

# 7. Deploy
nself deploy production

# 8. Configure DNS
# Point *.example.com to server IP

# 9. Setup SSL
nself auth ssl bootstrap --env prod

# 10. Verify
nself deploy health --env prod
curl https://payment-api.example.com/health
curl https://analytics-api.example.com/health

# 11. Setup monitoring alerts
# Access Grafana at https://grafana.example.com

echo "✓ AWS production deployment complete"
echo "  - Core services: Running"
echo "  - Custom services: 4 deployed"
echo "  - Monitoring: Enabled"
echo "  - SSL: Let's Encrypt configured"

Complete Hetzner Budget Setup

#!/bin/bash
# Ultra-budget production setup on Hetzner
# Total cost: ~$13/mo for full stack + custom services

# 1. Initialize Hetzner
nself infra provider init hetzner

# 2. Provision server (best value)
nself infra provider server create hetzner \
  --size large \
  --region fsn1 \
  --backups

# CX31: 8GB RAM, 2 vCPU, 80GB SSD, 20TB bandwidth
# Cost: €11.90/mo (~$12.70)

# 3. Setup
nself config env create prod prod

# 4. Configure (enable everything, we have resources)
cat > .environments/prod/.env <<EOF
ENV=prod
PROJECT_NAME=myapp
BASE_DOMAIN=example.com

# Custom Services (can run 4-6 easily)
CS_1=api:express-ts:8001
CS_2=worker:bullmq-js:8002
CS_3=analytics:fastapi:8003
CS_4=webhooks:express-ts:8004

# Enable optional services
MONITORING_ENABLED=true
REDIS_ENABLED=true
MINIO_ENABLED=true
MEILISEARCH_ENABLED=true
EOF

# 5. Deploy
nself config secrets generate --env prod
nself deploy production

# 6. SSL
nself auth ssl bootstrap --env prod

echo "✓ Hetzner budget setup complete"
echo "  - Total cost: ~$13/mo"
echo "  - Services: 4 core + 7 optional + 10 monitoring + 4 custom"
echo "  - Bandwidth: 20TB included"

Oracle Free Tier Setup

#!/bin/bash
# COMPLETELY FREE production setup on Oracle Cloud
# Cost: $0/mo forever

# 1. Initialize Oracle Cloud
nself infra provider init oracle

# 2. Provision FREE ARM instance
nself infra provider server create oracle --size free --arm

# This gives you:
# - 4 ARM cores (Ampere Altra)
# - 24GB RAM
# - 200GB storage
# - 10TB bandwidth
# - FOREVER FREE

# 3. Setup
nself config env create prod prod

# 4. Configure (be generous, it's free)
cat > .environments/prod/.env <<EOF
ENV=prod
PROJECT_NAME=myapp
BASE_DOMAIN=example.com

# Custom Services (ARM optimized)
CS_1=api:express-ts:8001
CS_2=worker:bullmq-js:8002
CS_3=grpc:grpc:50051

# Enable services
MONITORING_ENABLED=true
REDIS_ENABLED=true
EOF

# 5. Build for ARM
docker buildx create --use
docker buildx build --platform linux/arm64 -t myapp_api services/api

# 6. Deploy
nself config secrets generate --env prod
nself deploy production

echo "✓ Oracle free tier setup complete"
echo "  - Cost: $0/mo FOREVER"
echo "  - ARM cores: 4"
echo "  - RAM: 24GB"
echo "  - Perfect for side projects, MVPs, learning"

Summary

Provider Recommendations by Use Case

Use Case Recommended Provider Why
Side Project / MVP Oracle (free tier) Free forever, generous resources
Budget Production Hetzner Best value, 20TB bandwidth
Developer Experience DigitalOcean Simple, great docs
Global Scale AWS / GCP Most regions, enterprise features
ML/AI Workloads GCP Best ML tools
European GDPR Hetzner / Scaleway EU data centers
High Availability Multi-cloud Redundancy across providers

Custom Services Support

✅ All 26+ providers support custom services (CS_N) ✅ Deploy via Docker Compose (single server) or Kubernetes (multi-server) ✅ Full monitoring, logging, health checks included ✅ Auto-scaling available on K8s-enabled providers ✅ Provider-agnostic deployment (same commands everywhere)

See Also

ɳSelf CLI v1.0.9. MIT licensed. Docs CC BY 4.0.

GitHub · Issues · Discussions · nself.org · docs.nself.org

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