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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.

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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.

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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.

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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.

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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 for guidance.

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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.

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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.