Deploying autonomous AI agents on the cloud doesn’t have to be a complex process. Hermes Agent is an open-source, production-ready framework that enables developers to build, deploy, and scale intelligent AI agents capable of reasoning, planning, tool usage, API integration, code execution, and workflow automation.
The Hermes Agent — Build, Deploy & Scale Autonomous AI virtual machine on Microsoft Azure Marketplace provides a fully configured environment with all the required components pre-installed, allowing you to start building AI-powered applications within minutes. Whether you’re running local Ollama models, integrating cloud-based LLM providers, or developing production-ready autonomous AI workflows, this VM eliminates the need for manual installation and configuration.
In this guide, you’ll learn how to deploy the Hermes Agent VM from Azure Marketplace, connect to the instance using SSH or Remote Desktop (RDP), access the Hermes Web Interface, configure language models, and begin building autonomous AI applications on Azure.
Step-by-Step Guide
This section describes how to launch and connect to the ‘Hermes Agent — Build, Deploy & Scale Autonomous AI’ VM solution on the Azure Platform.
- Open the Hermes Agent — Build, Deploy & Scale Autonomous AI VM listing on Azure Marketplace.
- Click on Get It Now
- Log in with your credentials and provide the details here. Once done, click on the Get it now button at the bottom.
- It will take you to the Product details page. Click on Create.
- Select a Resource group for your virtual machine
- Select a Region where you want to launch the VM(such as East US)
- Note: If you see the “This image is not compatible with selected security type. To keep trusted launch virtual machines, select a compatible image. Otherwise change your security type back to Standard” error message below the Image name as shown in the screenshot below, then please change the Security type to Standard.
- Optionally change the number of cores and amount of memory.
Minimum VM Specs: 16GB RAM / 4 vCPUs. Please also check publisher recommendations for more instance options.
The VM can also be deployed using an NVIDIA GPU instance for faster execution. Please check the Publisher recommendations instance type for GPU (Standard_NC4as_T4_v3–4 vCPUs, 28 GiB memory) or check the available NVIDIA GPU instances on the Azure documentation page.
Select the Authentication type as Password and enter Username as ubuntu and Password of your choice.
- Optionally change the OS disk size and its type. By default, the VM comes with 50GB of disk.
- Optionally change the network and subnetwork names. Be sure that whichever network you specify has ports 22 (for SSH), 3389 (for RDP), 80 (for HTTP), and 443 (for HTTPS) exposed.
The VM comes with the preconfigured NSG rules. You can check them by clicking on the Create New option available under the security group option.
- Optionally, go to the Management, Advanced, and Tags tabs for any advanced settings you want for the VM.
- Click on Review + create and then click on Create when you are done. The virtual machine will begin deploying.
- A summary page displays when the virtual machine is successfully created. Click on Go to resource link to go to the resource page. It will open an overview page of the virtual machine.
- If you want to update your password, then open up the left navigation pane, select Run command, select RunShellScript, and enter the following command to change the password of the VM.
sudo echo ubuntu:yourpassword | chpasswd
Now that the password for the Ubuntu user is set, you can SSH to the VM. To do so, first note the public IP address of the VM from the VM details page as highlighted below.
Open PuTTY, paste the IP address, and click on Open.
Log in as ubuntu and provide the password for the ‘ubuntu’ user.
You can also connect to the VM’s desktop environment from any local Windows machine using the RDP protocol or a local Linux machine using Remmina.
To connect using RDP via a Windows Machine, copy the public IP address of the VM from the VM details page, then from your local Windows machine, go to the “Start” menu, in the search box type 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 as ubuntu and the password set in step 4 to authenticate. Click OK
- Now you are connected to the out-of-box “Hermes Agent — Build, Deploy & Scale Autonomous AI” 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, paste the external IP, and click Enter.
- This will connect you to the VM’s desktop environment. Provide “ubuntu” as the user ID and the password set in the above reset password step to authenticate. Click OK
- Now you are connected to the out-of-box “Hermes Agent — Build, Deploy & Scale Autonomous AI” VM’s desktop environment via Linux machine.
- The VM will generate a random password to log in to Hermes Web Interface. To get the password, connect via SSH terminal as shown in the above step and run the command.
cat /home/ubuntu/.hermes/.env | grep HERMES_DASHBOARD_BASIC_AUTH
- To access the Hermes 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 click Continue.
- It will open a login page. Provide the password we got in the above step and click Sign In.
- Now you are connected to the out-of-box Hermes Web Interface.
- You can use the Hermes chat feature to run tasks or ask questions.
- By default, the LLM model set is “deepseek-r1:8b”h. You can pull other Ollama models.
ollama pull <model_name>
e.g ollama pull gemma2:9b
- Once your model is pulled, you can set it to default from the web interface as well as from the terminal. To switch models from the web interface, simply click on the model dropdown from the top right of your chat window. Choose the model you want to set and click Switch
Or from the terminal, you can run,
hermes config set model <provider_name>/<model_name>
e.g. hermes config set model ollama/gemma2:9b
- To change the LLM provider and set the API Keys, please run the command.
hermes model
Choose your provider of choice and follow the on-screen instructions. Once the process is complete, go back to the web interface and refresh the page to see the changes.
- If, for any Ollama model, you are getting a context length error as shown in the screenshot below while running the chat, then set the context_length and ollama_num_ctx to the required value by running the commands in the terminal, then refresh the WebUI.
Note: This is specific to Ollama; if you want to do it for other providers, then make the appropriate changes in the commands.
hermes config set model.ollama_num_ctx 65536
hermes config set model.context_length 65536
For more details, please visit the Official Documentation page
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