> ## Documentation Index
> Fetch the complete documentation index at: https://docs.hivenet.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Understand and choose your Compute instance

> A practical guide to choosing, launching, and connecting to the right Compute instance for your workload.

## What makes up a Compute instance?

A Compute instance is a unit of compute resources you run on Hivenet. Depending on your use case, an instance can run as a **container** or as a **virtual machine**.

When you create an instance, you choose a combination of hardware, runtime type, and configuration that determines how it behaves and what level of control you have.

### **Container-based instances**

Containers are designed for most common workloads, such as running scripts, applications, and models.

* Root access is disabled. Commands that require sudo won’t work.
* System-level packages are managed through templates rather than manual installation.

### **Virtual machine instances**

Virtual machines are intended for workloads that need full operating system control.

* Full OS-level access, including sudo and kernel-level configuration.
* Support for standard Linux distributions such as Ubuntu, Fedora, and Debian.

## What you choose when creating an instance

Regardless of the instance type, you’ll configure the following:

* **GPU(s)**\
  Choose the number and type of GPUs for your workload. NVIDIA RTX 4090 GPUs are available, with up to 8 GPUs per instance, suitable for training, inference, rendering, and other GPU-heavy tasks.
* **vCPUs and RAM**\
  CPU and memory resources are matched to your GPU selection to ensure balanced performance without manual tuning.
* **Storage**\
  Instances include fast local SSD storage. Storage behavior depends on the instance type and lifecycle. See the instance lifecycle documentation for details.
* **Region**\
  Select where your instance runs. Currently supported regions include France and the UAE. Region choice affects latency and data residency.
* **Billing type**\
  Instances use on-demand billing. You pay only while the instance is running.

### How to choose the right instance

The right choice depends on what you’re building.

* Running scripts, apps, or model inference?\
  A container-based instance is usually the simplest and fastest option.
* Training large models or running GPU-heavy workloads?\
  Choose the number of GPUs based on your model size and VRAM needs. Each RTX 4090 provides 24 GB of VRAM.
* Need full OS control, custom system packages, or kernel access?\
  Use a virtual machine instance.

If you’re unsure, that’s normal. You can reach out through the in-app chatbot or [join the community on Discord](https://discord.gg/invite/f5aBCn5HZK) for guidance.

## Managing your instance from the dashboard

Once your instance is running, you can manage it from the Compute dashboard:

* Start or stop the instance at any time
* Monitor usage, uptime, and cost
* Terminate the instance when you’re finished

Instances are billed per second. When an instance is stopped or terminated, compute charges stop according to the instance lifecycle rules.

## How to connect to your instance

When your instance is ready, you’ll have access to:

* A public IP address
* SSH access details
* GPU information for verification and diagnostics

You can connect using a standard SSH command:

```
ssh [your-username]@[your-instance-ip]
```

You can use a terminal or a graphical SSH client, depending on your workflow.