$ Your agent works on your laptop. Great. Now how do you make it run 24/7 without you babysitting it? Deployment is where most AI agent projects die — not because the agent doesn't work, but because nobody figured out how to keep it running reliably. This guide covers three deployment approaches (VPS, Docker, serverless), with real configs, cost breakdowns, and the monitoring you need to sleep at night while your agent works.

Choosing Your Deployment Model Approach Best For Monthly Cost Complexity Always-On? **VPS (bare metal)** 24/7 autonomous agents $5-20 Medium Yes **Docker + VPS** Reproducible, multi-agent $10-30 Medium-High Yes **Serverless (Lambda/Cloud Run)** Event-triggered agents $1-50 (pay-per-use) Low-Medium No (triggered) **Managed platforms** No-ops teams $20-200 Low Varies

Option 1: VPS Deployment (What We Use) The simplest path to a 24/7 agent. Rent a virtual server, -weight: 500;">install your agent, set up a process manager, and let it run.

Step 1: Choose a VPS Provider Provider Cheapest Plan Specs Best For **Hetzner** $4.50/mo 2 vCPU, 4GB RAM, 40GB SSD Best value in EU **DigitalOcean** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Simple UI, good docs **Vultr** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Global locations **Contabo** $6.50/mo 4 vCPU, 8GB RAM, 50GB SSD Most specs per dollar **What Paxrel uses:** A Hetzner CX22 ($5.50/mo) with 2 vCPU, 4GB RAM. Runs our full agent stack: newsletter pipeline, social media automation, web scraping, and Reddit karma builder — all on one server.

Step 2: Initial Server Setup Your agent works on your laptop. Great. Now how do you make it run 24/7 without you babysitting it? Deployment is where most AI agent projects die — not because the agent doesn't work, but because nobody figured out how to keep it running reliably. This guide covers three deployment approaches (VPS, Docker, serverless), with real configs, cost breakdowns, and the monitoring you need to sleep at night while your agent works.

Choosing Your Deployment Model Approach Best For Monthly Cost Complexity Always-On? **VPS (bare metal)** 24/7 autonomous agents $5-20 Medium Yes **Docker + VPS** Reproducible, multi-agent $10-30 Medium-High Yes **Serverless (Lambda/Cloud Run)** Event-triggered agents $1-50 (pay-per-use) Low-Medium No (triggered) **Managed platforms** No-ops teams $20-200 Low Varies

Option 1: VPS Deployment (What We Use) The simplest path to a 24/7 agent. Rent a virtual server, -weight: 500;">install your agent, set up a process manager, and let it run.

Step 1: Choose a VPS Provider Provider Cheapest Plan Specs Best For **Hetzner** $4.50/mo 2 vCPU, 4GB RAM, 40GB SSD Best value in EU **DigitalOcean** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Simple UI, good docs **Vultr** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Global locations **Contabo** $6.50/mo 4 vCPU, 8GB RAM, 50GB SSD Most specs per dollar **What Paxrel uses:** A Hetzner CX22 ($5.50/mo) with 2 vCPU, 4GB RAM. Runs our full agent stack: newsletter pipeline, social media automation, web scraping, and Reddit karma builder — all on one server.

Step 2: Initial Server Setup Your agent works on your laptop. Great. Now how do you make it run 24/7 without you babysitting it? Deployment is where most AI agent projects die — not because the agent doesn't work, but because nobody figured out how to keep it running reliably. This guide covers three deployment approaches (VPS, Docker, serverless), with real configs, cost breakdowns, and the monitoring you need to sleep at night while your agent works.

Choosing Your Deployment Model Approach Best For Monthly Cost Complexity Always-On? **VPS (bare metal)** 24/7 autonomous agents $5-20 Medium Yes **Docker + VPS** Reproducible, multi-agent $10-30 Medium-High Yes **Serverless (Lambda/Cloud Run)** Event-triggered agents $1-50 (pay-per-use) Low-Medium No (triggered) **Managed platforms** No-ops teams $20-200 Low Varies

Option 1: VPS Deployment (What We Use) The simplest path to a 24/7 agent. Rent a virtual server, -weight: 500;">install your agent, set up a process manager, and let it run.

Step 1: Choose a VPS Provider Provider Cheapest Plan Specs Best For **Hetzner** $4.50/mo 2 vCPU, 4GB RAM, 40GB SSD Best value in EU **DigitalOcean** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Simple UI, good docs **Vultr** $6/mo 1 vCPU, 1GB RAM, 25GB SSD Global locations **Contabo** $6.50/mo 4 vCPU, 8GB RAM, 50GB SSD Most specs per dollar **What Paxrel uses:** A Hetzner CX22 ($5.50/mo) with 2 vCPU, 4GB RAM. Runs our full agent stack: newsletter pipeline, social media automation, web scraping, and Reddit karma builder — all on one server.

Step 2: Initial Server Setup # SSH into your new server ssh root@your-server-ip # Create a non-root user adduser agent usermod -aG -weight: 600;">sudo agent # Install essentials -weight: 500;">apt -weight: 500;">update && -weight: 500;">apt -weight: 500;">install -y python3 python3--weight: 500;">pip python3-venv -weight: 500;">git -weight: 500;">curl # Switch to agent user su - agent # Clone your agent code -weight: 500;">git clone https://github.com/your-org/your-agent.-weight: 500;">git cd your-agent # Set up Python environment python3 -m venv .venv source .venv/bin/activate -weight: 500;">pip -weight: 500;">install -r requirements.txt # Create environment file for credentials cat > .env > logs/pipeline.log 2>&1 # Social media posting: Every 6 hours 0 */6 * * * cd /home/agent/your-agent && .venv/bin/python3 post_tweet.py >> logs/twitter.log 2>&1 # Daily monitoring report 30 9 * * * cd /home/agent/your-agent && .venv/bin/python3 monitoring.py >> logs/monitoring.log 2>&1 # SSH into your new server ssh root@your-server-ip # Create a non-root user adduser agent usermod -aG -weight: 600;">sudo agent # Install essentials -weight: 500;">apt -weight: 500;">update && -weight: 500;">apt -weight: 500;">install -y python3 python3--weight: 500;">pip python3-venv -weight: 500;">git -weight: 500;">curl # Switch to agent user su - agent # Clone your agent code -weight: 500;">git clone https://github.com/your-org/your-agent.-weight: 500;">git cd your-agent # Set up Python environment python3 -m venv .venv source .venv/bin/activate -weight: 500;">pip -weight: 500;">install -r requirements.txt # Create environment file for credentials cat > .env > logs/pipeline.log 2>&1 # Social media posting: Every 6 hours 0 */6 * * * cd /home/agent/your-agent && .venv/bin/python3 post_tweet.py >> logs/twitter.log 2>&1 # Daily monitoring report 30 9 * * * cd /home/agent/your-agent && .venv/bin/python3 monitoring.py >> logs/monitoring.log 2>&1 # SSH into your new server ssh root@your-server-ip # Create a non-root user adduser agent usermod -aG -weight: 600;">sudo agent # Install essentials -weight: 500;">apt -weight: 500;">update && -weight: 500;">apt -weight: 500;">install -y python3 python3--weight: 500;">pip python3-venv -weight: 500;">git -weight: 500;">curl # Switch to agent user su - agent # Clone your agent code -weight: 500;">git clone https://github.com/your-org/your-agent.-weight: 500;">git cd your-agent # Set up Python environment python3 -m venv .venv source .venv/bin/activate -weight: 500;">pip -weight: 500;">install -r requirements.txt # Create environment file for credentials cat > .env > logs/pipeline.log 2>&1 # Social media posting: Every 6 hours 0 */6 * * * cd /home/agent/your-agent && .venv/bin/python3 post_tweet.py >> logs/twitter.log 2>&1 # Daily monitoring report 30 9 * * * cd /home/agent/your-agent && .venv/bin/python3 monitoring.py >> logs/monitoring.log 2>&1

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# Dockerfile FROM python:3.12-slim WORKDIR /app # Install system dependencies RUN -weight: 500;">apt-get -weight: 500;">update && -weight: 500;">apt-get -weight: 500;">install -y --no--weight: 500;">install-recommends \ -weight: 500;">curl -weight: 500;">git && rm -rf /var/lib/-weight: 500;">apt/lists/* # Install Python dependencies COPY requirements.txt . RUN -weight: 500;">pip -weight: 500;">install --no-cache-dir -r requirements.txt # Copy agent code COPY . . # Non-root user for security RUN useradd -m agent USER agent CMD ["python3", "agent.py"] # Dockerfile FROM python:3.12-slim WORKDIR /app # Install system dependencies RUN -weight: 500;">apt-get -weight: 500;">update && -weight: 500;">apt-get -weight: 500;">install -y --no--weight: 500;">install-recommends \ -weight: 500;">curl -weight: 500;">git && rm -rf /var/lib/-weight: 500;">apt/lists/* # Install Python dependencies COPY requirements.txt . RUN -weight: 500;">pip -weight: 500;">install --no-cache-dir -r requirements.txt # Copy agent code COPY . . # Non-root user for security RUN useradd -m agent USER agent CMD ["python3", "agent.py"] # Dockerfile FROM python:3.12-slim WORKDIR /app # Install system dependencies RUN -weight: 500;">apt-get -weight: 500;">update && -weight: 500;">apt-get -weight: 500;">install -y --no--weight: 500;">install-recommends \ -weight: 500;">curl -weight: 500;">git && rm -rf /var/lib/-weight: 500;">apt/lists/* # Install Python dependencies COPY requirements.txt . RUN -weight: 500;">pip -weight: 500;">install --no-cache-dir -r requirements.txt # Copy agent code COPY . . # Non-root user for security RUN useradd -m agent USER agent CMD ["python3", "agent.py"] # -weight: 500;">docker-compose.yml version: '3.8' services: agent: build: . -weight: 500;">restart: always env_file: .env volumes: - ./data:/app/data # Persist agent memory/state - ./logs:/app/logs # Persist logs deploy: resources: limits: memory: 2G cpus: '1.0' healthcheck: test: ["CMD", "python3", "-c", "import requests; requests.get('http://localhost:8080/health')"] interval: 60s timeout: 10s retries: 3 # Optional: vector database for RAG chromadb: image: chromadb/chroma:latest -weight: 500;">restart: always volumes: - chroma_data:/chroma/chroma ports: - "8000:8000" volumes: chroma_data: # -weight: 500;">docker-compose.yml version: '3.8' services: agent: build: . -weight: 500;">restart: always env_file: .env volumes: - ./data:/app/data # Persist agent memory/state - ./logs:/app/logs # Persist logs deploy: resources: limits: memory: 2G cpus: '1.0' healthcheck: test: ["CMD", "python3", "-c", "import requests; requests.get('http://localhost:8080/health')"] interval: 60s timeout: 10s retries: 3 # Optional: vector database for RAG chromadb: image: chromadb/chroma:latest -weight: 500;">restart: always volumes: - chroma_data:/chroma/chroma ports: - "8000:8000" volumes: chroma_data: # -weight: 500;">docker-compose.yml version: '3.8' services: agent: build: . -weight: 500;">restart: always env_file: .env volumes: - ./data:/app/data # Persist agent memory/state - ./logs:/app/logs # Persist logs deploy: resources: limits: memory: 2G cpus: '1.0' healthcheck: test: ["CMD", "python3", "-c", "import requests; requests.get('http://localhost:8080/health')"] interval: 60s timeout: 10s retries: 3 # Optional: vector database for RAG chromadb: image: chromadb/chroma:latest -weight: 500;">restart: always volumes: - chroma_data:/chroma/chroma ports: - "8000:8000" volumes: chroma_data: # Deploy -weight: 500;">docker compose up -d # View logs -weight: 500;">docker compose logs -f agent # Update agent -weight: 500;">git pull && -weight: 500;">docker compose build && -weight: 500;">docker compose up -d # Deploy -weight: 500;">docker compose up -d # View logs -weight: 500;">docker compose logs -f agent # Update agent -weight: 500;">git pull && -weight: 500;">docker compose build && -weight: 500;">docker compose up -d # Deploy -weight: 500;">docker compose up -d # View logs -weight: 500;">docker compose logs -f agent # Update agent -weight: 500;">git pull && -weight: 500;">docker compose build && -weight: 500;">docker compose up -d

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# handler.py import json import boto3 def lambda_handler(event, context): """Triggered by EventBridge cron or API Gateway webhook""" # Your agent logic here from agent import run_agent result = run_agent(event) return { 'statusCode': 200, 'body': json.dumps(result) } # handler.py import json import boto3 def lambda_handler(event, context): """Triggered by EventBridge cron or API Gateway webhook""" # Your agent logic here from agent import run_agent result = run_agent(event) return { 'statusCode': 200, 'body': json.dumps(result) } # handler.py import json import boto3 def lambda_handler(event, context): """Triggered by EventBridge cron or API Gateway webhook""" # Your agent logic here from agent import run_agent result = run_agent(event) return { 'statusCode': 200, 'body': json.dumps(result) } # serverless.yml (Serverless Framework) -weight: 500;">service: ai-agent provider: name: aws runtime: python3.12 timeout: 300 # 5 minutes max memorySize: 512 environment: OPENAI_API_KEY: ${ssm:/ai-agent/openai-key} functions: newsletter: handler: handler.lambda_handler events: - schedule: cron(0 8 ? * MON,WED,FRI *) # Mon/Wed/Fri 8am webhook: handler: handler.lambda_handler events: - httpApi: path: /webhook method: post # serverless.yml (Serverless Framework) -weight: 500;">service: ai-agent provider: name: aws runtime: python3.12 timeout: 300 # 5 minutes max memorySize: 512 environment: OPENAI_API_KEY: ${ssm:/ai-agent/openai-key} functions: newsletter: handler: handler.lambda_handler events: - schedule: cron(0 8 ? * MON,WED,FRI *) # Mon/Wed/Fri 8am webhook: handler: handler.lambda_handler events: - httpApi: path: /webhook method: post # serverless.yml (Serverless Framework) -weight: 500;">service: ai-agent provider: name: aws runtime: python3.12 timeout: 300 # 5 minutes max memorySize: 512 environment: OPENAI_API_KEY: ${ssm:/ai-agent/openai-key} functions: newsletter: handler: handler.lambda_handler events: - schedule: cron(0 8 ? * MON,WED,FRI *) # Mon/Wed/Fri 8am webhook: handler: handler.lambda_handler events: - httpApi: path: /webhook method: post

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# For longer-running agents (up to 60 min) gcloud run deploy ai-agent \ --source . \ --region us-central1 \ --memory 1Gi \ --timeout 3600 \ --set-env-vars "OPENAI_API_KEY=sk-..." \ --no-allow-unauthenticated # For longer-running agents (up to 60 min) gcloud run deploy ai-agent \ --source . \ --region us-central1 \ --memory 1Gi \ --timeout 3600 \ --set-env-vars "OPENAI_API_KEY=sk-..." \ --no-allow-unauthenticated # For longer-running agents (up to 60 min) gcloud run deploy ai-agent \ --source . \ --region us-central1 \ --memory 1Gi \ --timeout 3600 \ --set-env-vars "OPENAI_API_KEY=sk-..." \ --no-allow-unauthenticated Platform Max Runtime Cold Start Cost per Run AWS Lambda 15 minutes 1-5 seconds $0.0001-0.01 Google Cloud Run 60 minutes 2-10 seconds $0.001-0.05 Vercel Functions 5 minutes (pro: 15) $0.0001-0.005 Cloudflare Workers 30 seconds (free) $0.00005

Monitoring Your Deployed Agent A deployed agent without monitoring is a liability. Here's the minimum monitoring stack:

Health Check Endpoint Platform Max Runtime Cold Start Cost per Run AWS Lambda 15 minutes 1-5 seconds $0.0001-0.01 Google Cloud Run 60 minutes 2-10 seconds $0.001-0.05 Vercel Functions 5 minutes (pro: 15) $0.0001-0.005 Cloudflare Workers 30 seconds (free) $0.00005

Monitoring Your Deployed Agent A deployed agent without monitoring is a liability. Here's the minimum monitoring stack:

Health Check Endpoint Platform Max Runtime Cold Start Cost per Run AWS Lambda 15 minutes 1-5 seconds $0.0001-0.01 Google Cloud Run 60 minutes 2-10 seconds $0.001-0.05 Vercel Functions 5 minutes (pro: 15) $0.0001-0.005 Cloudflare Workers 30 seconds (free) $0.00005

Monitoring Your Deployed Agent A deployed agent without monitoring is a liability. Here's the minimum monitoring stack:

Health Check Endpoint from flask import Flask, jsonify import psutil app = Flask(__name__) @app.route('/health') def health(): return jsonify({ "-weight: 500;">status": "healthy", "uptime_hours": get_uptime(), "memory_mb": psutil.Process().memory_info().rss / 1024 / 1024, "last_run": get_last_run_timestamp(), "errors_24h": get_error_count(hours=24), "api_balance": check_api_balance() }) from flask import Flask, jsonify import psutil app = Flask(__name__) @app.route('/health') def health(): return jsonify({ "-weight: 500;">status": "healthy", "uptime_hours": get_uptime(), "memory_mb": psutil.Process().memory_info().rss / 1024 / 1024, "last_run": get_last_run_timestamp(), "errors_24h": get_error_count(hours=24), "api_balance": check_api_balance() }) from flask import Flask, jsonify import psutil app = Flask(__name__) @app.route('/health') def health(): return jsonify({ "-weight: 500;">status": "healthy", "uptime_hours": get_uptime(), "memory_mb": psutil.Process().memory_info().rss / 1024 / 1024, "last_run": get_last_run_timestamp(), "errors_24h": get_error_count(hours=24), "api_balance": check_api_balance() })

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$ import requests def send_alert(message, level="warning"): """Send alert via Telegram/Slack/email""" if level == "critical": # Telegram for immediate attention requests.post( f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage", data={"chat_id": OWNER_ID, "text": f"🚨 {message}"} ) else: # Slack webhook for non-critical requests.post(SLACK_WEBHOOK, json={"text": f"⚠️ {message}"}) # Alerts to configure: # - Agent crash / -weight: 500;">restart # - API balance below threshold # - Error rate spike (3+ errors in 10 min) # - Agent stuck (no activity for 2+ hours) # - Cost spike (daily spend > 2x average) import requests def send_alert(message, level="warning"): """Send alert via Telegram/Slack/email""" if level == "critical": # Telegram for immediate attention requests.post( f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage", data={"chat_id": OWNER_ID, "text": f"🚨 {message}"} ) else: # Slack webhook for non-critical requests.post(SLACK_WEBHOOK, json={"text": f"⚠️ {message}"}) # Alerts to configure: # - Agent crash / -weight: 500;">restart # - API balance below threshold # - Error rate spike (3+ errors in 10 min) # - Agent stuck (no activity for 2+ hours) # - Cost spike (daily spend > 2x average) import requests def send_alert(message, level="warning"): """Send alert via Telegram/Slack/email""" if level == "critical": # Telegram for immediate attention requests.post( f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage", data={"chat_id": OWNER_ID, "text": f"🚨 {message}"} ) else: # Slack webhook for non-critical requests.post(SLACK_WEBHOOK, json={"text": f"⚠️ {message}"}) # Alerts to configure: # - Agent crash / -weight: 500;">restart # - API balance below threshold # - Error rate spike (3+ errors in 10 min) # - Agent stuck (no activity for 2+ hours) # - Cost spike (daily spend > 2x average)

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$ import logging from logging.handlers import RotatingFileHandler # Structured logging handler = RotatingFileHandler( 'logs/agent.log', maxBytes=10_000_000, # 10MB per file backupCount=5 # Keep 5 rotated files ) handler.setFormatter(logging.Formatter( '%(asctime)s [%(levelname)s] %(name)s: %(message)s' )) logger = logging.getLogger('agent') logger.addHandler(handler) # Log every significant action logger.info("Scraping 12 RSS feeds") logger.info("Scored 97 articles, top score: 28") logger.warning("API rate limited, retrying in 30s") logger.error("Beehiiv publish failed: 401 Unauthorized") import logging from logging.handlers import RotatingFileHandler # Structured logging handler = RotatingFileHandler( 'logs/agent.log', maxBytes=10_000_000, # 10MB per file backupCount=5 # Keep 5 rotated files ) handler.setFormatter(logging.Formatter( '%(asctime)s [%(levelname)s] %(name)s: %(message)s' )) logger = logging.getLogger('agent') logger.addHandler(handler) # Log every significant action logger.info("Scraping 12 RSS feeds") logger.info("Scored 97 articles, top score: 28") logger.warning("API rate limited, retrying in 30s") logger.error("Beehiiv publish failed: 401 Unauthorized") import logging from logging.handlers import RotatingFileHandler # Structured logging handler = RotatingFileHandler( 'logs/agent.log', maxBytes=10_000_000, # 10MB per file backupCount=5 # Keep 5 rotated files ) handler.setFormatter(logging.Formatter( '%(asctime)s [%(levelname)s] %(name)s: %(message)s' )) logger = logging.getLogger('agent') logger.addHandler(handler) # Log every significant action logger.info("Scraping 12 RSS feeds") logger.info("Scored 97 articles, top score: 28") logger.warning("API rate limited, retrying in 30s") logger.error("Beehiiv publish failed: 401 Unauthorized")

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