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How to Use Clawdbot with AWS: The Complete 2026 Deployment Guide

Complete guide to deploying OpenClaw (Clawdbot) on AWS EC2 and ECS. Step-by-step tutorial covering security, cost optimization, EC2 vs ECS comparison, and infrastructure-as-code with Pulumi.

Serenities Team12 min read
Complete guide to deploying Clawdbot on AWS EC2 and ECS

How to Use Clawdbot with AWS: The Complete 2026 Deployment Guide

If you've heard the buzz about OpenClaw (formerly known as Clawdbot and Moltbot)—the open-source AI assistant that gained 100,000+ GitHub stars and 2 million visitors in a single week—you're probably wondering how to get it running on your own infrastructure. While most tutorials focus on DigitalOcean's 1-Click deployment, there's a compelling case for deploying Clawdbot AWS style: enterprise-grade security, global infrastructure, and unmatched scalability.

In this comprehensive guide, we'll walk you through everything you need to know about running Clawdbot on AWS, from choosing the right deployment strategy (EC2 vs ECS) to optimizing your costs while maintaining rock-solid security.

Why Deploy Clawdbot on AWS?

Before diving into the technical setup, let's understand why AWS is an excellent choice for hosting your personal AI assistant.

Enterprise-Grade Security and Compliance

OpenClaw has deep access to your files, shell commands, and messaging platforms. Security experts have emphasized the importance of proper isolation—Cisco's security team even described misconfigured deployments as a "security nightmare." AWS provides:

  • VPC (Virtual Private Cloud): Complete network isolation from the public internet
  • IAM (Identity and Access Management): Granular control over who and what can access your instance
  • Security Groups: Stateful firewalls that control inbound and outbound traffic
  • AWS PrivateLink: Private connectivity without exposing traffic to the internet

Global Infrastructure

With data centers in 115+ regions worldwide, AWS lets you deploy Clawdbot close to your users for minimal latency. Whether you're in the US, Europe, or Asia-Pacific, there's an AWS region nearby.

Scalability and Reliability

Need more power for faster AI inference? AWS makes it easy to scale vertically (bigger instances) or horizontally (more instances). Plus, you get AWS's legendary 99.99% uptime SLA.

Prerequisites for Clawdbot AWS Deployment

Before we begin, ensure you have:

  • An AWS account with billing enabled
  • Node.js 22+ (for building locally, or handled via cloud-init)
  • An Anthropic API key (or OpenAI/OpenRouter alternative)
  • Basic familiarity with the AWS Console or CLI
  • Optionally: Tailscale account for secure remote access

Understanding OpenClaw Architecture

OpenClaw uses a gateway-centric architecture that's important to understand before deployment:

ComponentPortDescription
Gateway18789WebSocket server handling channels, sessions, and tools
Browser Control18791Headless Chrome for web automation
Docker SandboxIsolated container environment for safe tool execution

The Gateway is the heart of OpenClaw—it connects to messaging platforms (WhatsApp, Slack, Discord, Telegram), the CLI, web UI, and mobile apps.

EC2 vs ECS: Choosing Your Deployment Strategy

When deploying Clawdbot on AWS, you have two primary options. Here's a detailed comparison:

AWS EC2 (Elastic Compute Cloud)

Best for: Individual users, small teams, and those who want full control. Pros:
  • Complete control over the server environment
  • Easier to debug and troubleshoot
  • Simpler architecture for single-instance deployments
  • Direct SSH access for maintenance
Cons:
  • Manual scaling required
  • You manage OS updates and security patches
  • No built-in container orchestration
Recommended Instance Types:
InstancevCPUsRAMMonthly Cost (On-Demand)Use Case
t3.medium24 GiB~$30/monthMinimum recommended
t3.large28 GiB~$60/monthStandard usage
t3.xlarge416 GiB~$120/monthHeavy usage + local models
Important: Do NOT use t3.micro or t3.small. OpenClaw requires at least 4GB RAM for stable operation. The 1GB on t3.micro is insufficient even for installation.

AWS ECS (Elastic Container Service)

Best for: Teams, production environments, and those comfortable with containers. Pros:
  • Built-in container orchestration
  • Auto-scaling capabilities
  • Better integration with AWS services (ALB, CloudWatch)
  • Easier rolling updates
Cons:
  • More complex setup
  • Requires container expertise
  • Higher operational overhead for simple deployments
When to choose ECS:
  • You're running multiple AI agents
  • You need auto-scaling based on demand
  • You have a DevOps team managing infrastructure
  • You want blue-green deployments

Step-by-Step EC2 Deployment Guide

Let's deploy Clawdbot on AWS EC2—the most straightforward approach for personal use.

Step 1: Launch an EC2 Instance

  • Navigate to EC2 DashboardLaunch Instance
  • Choose Ubuntu Server 24.04 LTS (recommended)
  • Select t3.medium or larger
  • Configure instance details:
  • - Enable Auto-assign Public IP (or use Elastic IP) - Keep default VPC or create a dedicated one

  • Add storage: 30 GB gp3 minimum
  • Configure Security Group:
  • Inbound Rules:
    
    • SSH (22) from your IP only
    • Custom TCP (18789) from your IP only (or Tailscale range)
  • Create or select an SSH key pair
  • Launch the instance
  • Step 2: Connect and Install Dependencies

    SSH into your instance:

    ssh -i your-key.pem ubuntu@your-ec2-ip
    

    Update the system and install dependencies:

    Update system

    sudo apt-get update && sudo apt-get upgrade -y

    Install Docker

    curl -fsSL https://get.docker.com | sh sudo usermod -aG docker ubuntu sudo systemctl enable docker sudo systemctl start docker

    Install NVM and Node.js

    curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.1/install.sh | bash source ~/.bashrc nvm install 22 nvm use 22

    Step 3: Install and Configure OpenClaw

    Install OpenClaw globally

    npm install -g openclaw@latest

    Set your API key

    export ANTHROPIC_API_KEY="sk-ant-your-key-here"

    Run the onboarding wizard

    openclaw onboard --install-daemon

    The wizard will walk you through:

    • Auth configuration: API key or OAuth
    • Gateway settings: Port binding, security options
    • Channel setup: WhatsApp, Discord, Telegram, etc.
    • Workspace bootstrap: Skills and default configurations

    Step 4: Configure for Production

    Edit the OpenClaw configuration for AWS-appropriate settings:

    nano ~/.openclaw/openclaw.json
    

    Key configurations:

    {
    

    "gateway": { "port": 18789, "bind": "0.0.0.0", "auth": { "mode": "token", "token": "your-secure-generated-token" }, "trustedProxies": ["127.0.0.1"] }, "agents": { "defaults": { "sandbox": { "mode": "non-main", "docker": { "network": "none", "memory": "1g", "cpus": 1 } } } } }

    Step 5: Start the Gateway

    Check status

    openclaw gateway status

    If not running, start it

    openclaw gateway start

    Verify health

    openclaw health

    Securing Your Clawdbot AWS Deployment

    Security is paramount when deploying an AI agent that can execute commands. Here are essential hardening steps:

    Use Tailscale for Secure Access

    Tailscale creates a secure mesh VPN, keeping your OpenClaw instance off the public internet:

    Install Tailscale

    curl -fsSL https://tailscale.com/install.sh | sh

    Connect to your Tailnet

    sudo tailscale up --authkey=tskey-auth-xxxxx --ssh

    Enable HTTPS proxy (requires admin console setup)

    tailscale serve --bg 18789

    With Tailscale, you can:

    • Remove public inbound rules except SSH (as backup)
    • Access OpenClaw via https://your-machine.your-tailnet.ts.net
    • Use Tailscale SSH instead of managing keys

    VPC Best Practices

  • Create a dedicated VPC for OpenClaw
  • Use private subnets where possible
  • Enable VPC Flow Logs for security auditing
  • Consider AWS WAF if exposing to the internet
  • AWS Secrets Manager

    Store your API keys securely:

    aws secretsmanager create-secret \
    

    --name openclaw/anthropic-key \ --secret-string "sk-ant-your-key"

    Then retrieve at startup via your init script.

    Infrastructure as Code with Pulumi

    For reproducible deployments, use Pulumi (or Terraform). Here's a condensed example:

    import * as aws from "@pulumi/aws";
    

    import * as pulumi from "@pulumi/pulumi";

    const config = new pulumi.Config(); const instanceType = config.get("instanceType") ?? "t3.medium";

    // VPC and networking const vpc = new aws.ec2.Vpc("openclaw-vpc", { cidrBlock: "10.0.0.0/16", enableDnsHostnames: true, });

    // Security group - minimal exposure const sg = new aws.ec2.SecurityGroup("openclaw-sg", { vpcId: vpc.id, ingress: [ { fromPort: 22, toPort: 22, protocol: "tcp", cidrBlocks: ["YOUR-IP/32"] } ], egress: [ { fromPort: 0, toPort: 0, protocol: "-1", cidrBlocks: ["0.0.0.0/0"] } ], });

    // EC2 instance with cloud-init const instance = new aws.ec2.Instance("openclaw", { ami: "ami-ubuntu-24-04-latest", instanceType: instanceType, vpcSecurityGroupIds: [sg.id], rootBlockDevice: { volumeSize: 30, volumeType: "gp3" }, userData: installScript, });

    Run pulumi up and your entire infrastructure is deployed in minutes.

    Cost Optimization Strategies

    Running Clawdbot on AWS doesn't have to break the bank. Here are proven strategies:

    1. Use Savings Plans

    AWS Savings Plans can reduce your EC2 costs by up to 28%:

    Commitmentt3.medium HourlyMonthly Cost
    On-Demand$0.0416~$30
    1-Year No Upfront$0.030~$22
    1-Year All Upfront$0.027~$19

    2. Right-Size Your Instance

    Monitor your CPU and memory usage with CloudWatch. If you're consistently under 50% utilization, consider downsizing.

    3. Use Spot Instances for Non-Critical Workloads

    Spot instances can save up to 90%, but they can be interrupted. Useful for:

    • Development/testing environments
    • Batch processing tasks
    • Non-production AI experiments

    4. Schedule Instance Runtime

    If you only use Clawdbot during work hours:

    Create a Lambda function to start/stop your instance

    Or use AWS Instance Scheduler

    5. Optimize LLM API Costs

    The biggest ongoing cost isn't EC2—it's API calls. Consider:

    • Using OpenRouter for model routing and cost optimization
    • Running local models via Ollama for non-critical tasks
    • Implementing conversation compaction to reduce token usage

    Troubleshooting Common Issues

    Issue: Gateway Won't Start

    Check logs

    openclaw logs --tail 100

    Verify port isn't in use

    sudo lsof -i :18789

    Check Docker is running (for sandbox)

    docker ps

    Issue: WhatsApp/Telegram Connection Fails

    Ensure you're running with Node.js (not Bun):

    Verify Node runtime

    node --version # Should be 22+

    Restart gateway with Node explicitly

    NODE_ENV=production node $(which openclaw) gateway --port 18789

    Issue: High Memory Usage

    OpenClaw with browser automation can use significant memory:

    Monitor memory

    htop

    If needed, upgrade to t3.large

    Or disable browser in sandbox

    Connecting Messaging Platforms

    Once your Clawdbot AWS deployment is running, connect your channels:

    WhatsApp

    openclaw channels login
    

    Scan QR code with WhatsApp → Settings → Linked Devices

    Discord

    openclaw channels add --channel discord --token "YOUR_BOT_TOKEN"
    

    Telegram

    openclaw channels add --channel telegram --token "YOUR_BOT_TOKEN"
    

    Final Thoughts

    Deploying Clawdbot on AWS gives you enterprise-grade infrastructure for your personal AI assistant. While it requires more setup than a 1-click solution, the benefits—security, scalability, and control—make it worthwhile for serious users.

    Quick Summary:
    • Use t3.medium minimum ($30/month on-demand)
    • Secure with Tailscale or VPC private subnets
    • Choose EC2 for simplicity, ECS for scale
    • Optimize costs with Savings Plans (save up to 35%)
    • Monitor with CloudWatch for right-sizing opportunities

    Whether you're a developer wanting full control or an enterprise requiring compliance, AWS provides the foundation for a secure, reliable Clawdbot deployment. Now go build something amazing with your AI assistant!


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