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Posted on Jun 9 • Originally published at Medium on Apr 20

Deploying OpenClaw: AI Agent Automation Stack on Amazon Web Services — A Complete Step-by-Step…

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Deploying OpenClaw: AI Agent Automation Stack on Amazon Web Services — A Complete Step-by-Step Guide

In the rapidly evolving world of AI automation, deploying powerful agent-based systems can often be complex and time-consuming. That’s where OpenClaw: AI Agent Automation Stack simplifies the process. By offering a pre-configured virtual machine environment, OpenClaw enables developers, startups, and enterprises to quickly launch intelligent AI agents capable of executing system-level tasks, managing workflows, and automating real-world operations.

When combined with the scalability and reliability of Amazon Web Services, this solution becomes even more powerful. Users can seamlessly deploy OpenClaw using CPU or GPU-backed instances, depending on their workload needs. The integration with tools like Ollama allows for efficient local execution of large language models, ensuring both performance and flexibility.

In this guide, we’ll walk through the complete step-by-step process of setting up and running OpenClaw on AWS — from launching the instance to accessing the web interface and configuring your first AI agent.

Step-by-Step Guide

Open OpenClaw: AI Agent Automation Stack VM listing on AWS marketplace.

Click on View purchase options.

Log in with your credentials and follow the instructions.
Review the prices and subscribe to the product by clicking on the subscribe button located at the bottom of this page. Once you are subscribed to the offer, click on the " Launch your software button.

The next page will show you the options to launch the instance: Launch through EC2 and One-click launch from AWS Marketplace. Tick the 2nd option, One-click launch from AWS Marketplace.

Select a Region where you want to launch the VM(such as US East (N.Virginia))
Optionally change the EC2 instance type. (This defaults to t2.xlarge instance type, 4 vCPUs, and 16 GB RAM.)

Please note that the VM can also be deployed using an NVIDIA GPU instance. If you want to deploy this instance with a GPU configuration, please choose NVIDIA GPU (e.g., g4dn.xlarge) or check the available NVIDIA GPU instances on the AWS documentation page.

Optionally change the network name and subnetwork names.

Select the Security Group. Be sure that whichever Security Group you specify has ports 22 (for SSH), 3389 (for RDP), and 443 (for HTTPS) exposed. Or you can create the new SG by clicking on the “Create Security Group” button. Provide the name and description, and save the SG for this instance.

Be sure to download the key pair, which is available by default, or you can create a new key pair and download it.
Click on Launch.
OpenClaw: AI Agent Automation Stack will begin deploying.

A summary page displays. To see this instance on EC2 Console, click on the View instance on EC2 link.

To connect to this instance through Putty, copy the IPv4 Public IP Address from the VM’s details page.

Open Putty, paste the IP address and browse your private key you downloaded while deploying the VM, by going to SSH->Auth->Credentials, click on Open. Enter ubuntu as the userid

Once connected, change the password for the Ubuntu user using the command below

sudo passwd ubuntu

Now that the password for the Ubuntu user is set, you can connect to the VM’s desktop environment from any local Windows Machine using RDP protocol or a Linux Machine using Remmina.

From your local Windows machine, go to the “Start” menu, type in the search box, and select “Remote Desktop Connection”. In the “Remote Desktop Connection” wizard, copy the public IP address and click Connect

This will connect you to the VM’s desktop environment. Provide the username “ubuntu” and the password set in the above “Reset password” step to authenticate. Click OK

Now you are connected to the out-of-the-box OpenClaw: AI Agent Automation Stack VM’s desktop environment via Windows Machine.

To connect using RDP via a Linux machine, first note the external IP of the VM from the VM details page, then from your local Linux machine, goto menu, in the search box type and select “Remmina”.

Note: If you don’t have Remmina installed on your Linux machine, first install Remmina as per your Linux distribution.

In the “Remmina Remote Desktop Client” wizard, select the RDP option from the dropdown and paste the external IP, and click Enter.

This will connect you to the VM’s desktop environment. Provide “ubuntu” as the username and the password set in the above reset password step to authenticate. Click OK

Now you are connected to the out-of-the-box OpenClaw: AI Agent Automation Stack VM’s desktop environment via Linux machine.

The VM will generate a random password to log in to the OpenClaw Web Interface. To get the password, connect via SSH terminal as shown in the above steps and run the command below.

sudo cat /home/ubuntu/setup/.gateway_pass

To access the Open Claw Web Interface, copy the public IP address of the VM and paste it in your local browser as https://public_ip_of_vm. Make sure to use https and not http.

The browser will display an SSL certificate warning message. Expand the warning message, accept the certificate warning, and continue.

It will open a login page. Provide the password we got at step 14 above and click connect.

After the connection is successful, it will ask you to pair the device. For that, go back to the SSH terminal and run the following command to get the request ID.

openclaw devices list

To approve the request, replace the request ID obtained in the previous step in the command below.

openclaw devices approve <requestId>

e.g openclaw devices approve 31b187f9–4545–44fc-bf49-dd1553753b25

Note: Sometimes the request may expire if there is a delay in approving it. If the request gets rejected, simply rerun the “openclaw devices list” command to obtain a new request ID, and then run the approve command using that ID. Also, each browser profile generates a unique device ID, so switching browsers or clearing browser data will require re-pairing. And lastly, if your VM's IP address is dynamic, which changes on VM reboot, then you also need to repair your device.

Now you are logged in to the OpenClaw Web Interface. You can set up your Agent, configure various channels, and start the automation.

By default, the LLM model set is “gpt-oss:20b”. You can pull other ollama models and switch them to primary models by running the commands below.

ollama pull llama3.1:8b

openclaw models set ollama/llama3.1:8b

Once the model is switched, go back to the Web Interface, refresh the page, and select the new model from the model dropdown. Once the model is loaded successfully, you can run your queries.

Please refer to the official documentation for more details:

Links to the official OpenClaw, Ollama website and documentation:

Conclusion

Deploying OpenClaw on Amazon Web Services provides a streamlined and secure way to harness the full potential of AI agent automation without dealing with complex setup processes. With its pre-configured environment, flexible infrastructure options, and seamless integration with tools like Ollama, users can focus entirely on building, experimenting, and scaling their AI workflows.

Whether you’re running lightweight API-based agents or high-performance local models on GPU instances, OpenClaw offers the versatility needed for modern AI use cases. By following this deployment guide, you now have everything required to get started and unlock the next level of automation with intelligent agents.