> For the complete documentation index, see [llms.txt](https://ai-docs.fptcloud.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai-docs.fptcloud.com/fpt-gpu-cloud/gpu-virtual-machine/on-fpt-cloud-console/quick-start.md).

# Quick Start

## Sign up for an account <a href="#gettingstarted-signupforanaccount" id="gettingstarted-signupforanaccount"></a>

{% stepper %}
{% step %}

### Create an FPT Cloud account

* Go to <https://fptcloud.com/>, click **Sign Up**, and follow the system instructions to enter your details.
* Our support team will contact you shortly to verify your information and activate your account.
  {% endstep %}

{% step %}

### Log in to the FPT Portal

* Sign in to <https://console.fptcloud.com/> in Vietnam region and [https://console.fptcloud.jp/](https://console.fptcloud.com/) in Japan region with your **FPT Cloud account and password**, depending on where your quota has been provisioned. Make sure to select the correct **Tenant and Region**.
* **Supported GPUs by Region**\
  **Hanoi 2 (Vietnam)**: NVIDIA H100 SXM, NVIDIA B300\
  **Tokyo (Japan)**: NVIDIA H200 SXM
* **Set up an SSH key:** Navigate to **SSH Management** to generate an SSH key. This key will be used for secure access to your servers.
  {% endstep %}
  {% endstepper %}

## Step-by-step <a href="#gettingstarted-step-by-step" id="gettingstarted-step-by-step"></a>

{% stepper %}
{% step %}

### Create a Subnet

A subnet is required before deploying your GPU VM.

1. In the left-side menu, go to **Network → Subnets**.
2. Click **Create Subnet** and complete the configuration.

Follow the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-create-a-subnet).
{% endstep %}

{% step %}

### Create a GPU VM

1. In the side menu, go to **Compute Engine** → **Instance Management**.
2. Click **Create Instance** and configure the virtual machine deployment.
   * **Choose the instance type**: **H100** instances are available on the **.com** site and **H200** instances are available on the **.jp** site.
   * **Select a disk type**: \
     **Ephemeral Disk (NVMe)** – The storage disk is bundled with the instance and cannot be resized.\
     **Persistent Disk (Block Storage SSD)** – A storage disk is required, with a minimum size of **100 GB**.

Follow the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-create-a-gpu-vm).
{% endstep %}

{% step %}

### **Allocate a public IP address (Floating IP)**

1. In the left-side menu, go to **Network → Floating IPs**.
2. Click **Allocate IP Address** and assign the IP to your VM.\
   \&#xNAN;**\* Ephemeral Disk (NVMe):** Use **port forwarding (NAT)**&#x74;o connect the floating IP with the VM. You’ll need to specify both **the** **IP port** and **the Instance port.**

Follow the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-manage-floating-ips).
{% endstep %}

{% step %}

### Create Security Group

By default, the Default **Security Group allows all outbound traffics. You have to create a new one to allow inbound rules to access the VM.**

1. Click on **Network** and select **Security Groups** in the Side menu.
2. Choose **Create Security Group** in the Security Groups Screen and define the inbound rules for VM (e.g., **Allow SSH access on port 22** from your client’s public IP)

Follow the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-manage-security-group).
{% endstep %}

{% step %}

### Access to GPU Virtual Machine

After successfully creating the GPU VM, you can access the server via SSH:

1. **Terminal:** Open your terminal and enter the command with your SSH key.
2. **Web Console**: Go to the server’s detail page and click **“Open at Console”** to log in with a password through the web console.

\*The default username is **`root` .**

Follow the detailed guide [here](https://ai-docs.fptcloud.com/ai-infastructure/gpu-virtual-machine/tutorials/how-to-access-a-gpu-vm)[.](https://wiki.fci.vn/display/NCPP/GPU+VM+Access+to+GPU+instances)
{% endstep %}
{% endstepper %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://ai-docs.fptcloud.com/fpt-gpu-cloud/gpu-virtual-machine/on-fpt-cloud-console/quick-start.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.