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This page outlines the end-to-end flow for deploying a GPU cluster using io.net Cloud VMaaS APIs. It is intended to help you understand the steps you can take and API calls needed to provision, price, and manage a cluster programmatically.

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Workflow Summary

The cluster deployment process consists of the following steps:
  1. Retrieve available hardware Use the GET Hardware List endpoint to fetch all supported GPU hardware configurations, including available GPU counts, locations, and resource specifications.
  2. Select hardware and configuration
    From the hardware list response, select the desired hardware type, number of GPUs per VM, and deployment region.
  3. Validate deployment pricing (optional)
    Use the GET Deployment Price endpoint to calculate the expected cost for the selected hardware configuration and duration.
  4. Deploy the cluster Use the POST Deploy VM endpoint to provision the cluster using the selected hardware, GPU count, location, and duration.
  5. Manage the cluster lifecycle After deployment, manage the cluster using one of the following endpoints:
The first hour of usage is non-refundable.
1

Retrieving Available Hardware

Using the GET Hardware List endpoint, retrieve all currently available GPU hardware configurations.Request Example
curl -X 'GET' \
  'https://api.io.solutions/enterprise/v1/io-cloud/vmaas/hardware' \
  -H 'accept: application/json' \
  -H 'x-api-key: <api-key>'

{
    "data": {
        "hardware": [
            {
                "id": "12__2",
                "deploy_id": 12,
                "name": "GeForce RTX 4090",
                "num_cards": 2,
                "supplier": "internal",
                "sold_out": false,
                "price": 0.6,
                "vram_per_card": 24,
                "interconnect": null,
                "nvlink": false,
                "storage": 1000,
                "vcpu": 39,
                "memory": 125,
                "location": "US"
            },
            {
                "id": "12__1",
                "deploy_id": 12,
                "name": "GeForce RTX 4090",
                "num_cards": 1,
                "supplier": "internal",
                "sold_out": false,
                "price": 0.3,
                "vram_per_card": 24,
                "interconnect": null,
                "nvlink": false,
                "storage": 500,
                "vcpu": 39,
                "memory": 125,
                "location": "US"
            },
            {
                "id": "B200_sxm6x8__US",
                "deploy_id": "B200_sxm6x8",
                "name": "B200",
                "num_cards": 8,
                "supplier": "external",
                "sold_out": false,
                "price": 39.92,
                "vram_per_card": 192,
                "interconnect": "sxm6",
                "nvlink": false,
                "storage": 22528,
                "vcpu": 208,
                "memory": 2900,
                "location": "US"
            },
            {
                "id": "B200_sxm6x8__AU",
                "deploy_id": "B200_sxm6x8",
                "name": "B200",
                "num_cards": 8,
                "supplier": "external",
                "sold_out": false,
                "price": 39.92,
                "vram_per_card": 192,
                "interconnect": "sxm6",
                "nvlink": false,
                "storage": 22528,
                "vcpu": 208,
                "memory": 2900,
                "location": "AU"
            }
        ]       
     }
}
2

Selecting your Hardware and Configuration

From the response of the GET Hardware List endpoint, select your chosen GPU and save the following values:
​
deploy_id
string/integer
required
Hardware identifier used for pricing and deployment. Can be a string or integer.
​
num_cards
integer
required
Number of GPUs per VM.
​
location
string
required
Deployment region.
3

Validating your Deployment Price (Optional)

Using the GET Deployment Price endpoint and the values you have saved, validate the price of your desired deployment before you deploy your cluster.Request Example
curl -X GET "https://api.io.solutions/enterprise/v1/io-cloud/vmaas/price" \
  -H "x-api-key: YOUR_API_KEY" \
  --data-urlencode "hardware_id=12" \
  --data-urlencode "gpus_per_vm=1" \
  --data-urlencode "replica_count=1" \
  --data-urlencode "duration_hours=1" \
  --data-urlencode "currency=usdc" \
  --data-urlencode 'location_ids=["US"]'
Ensure that the following fields have been assigned a value:
​
hardware_id
string/integer
required
Value of deploy_id from the Hardware List response.
​
gpus_per_vm
integer
required
Number of GPUs per VM. Value of num_cards from the Hardware List response.
​
duration_hours
integer
required
Duration of your deployment, in hours.
​
currency
string
required
Pricing currency.Example: usdc
​
location_ids
string
required
URL-encoded JSON array of locations. Use --data-urlencode in your cURL request if you use a plain string.Example: %5B%22US%22%5D = ["US"]
4

Deploying your Cluster

Using the POST Deploy VM enndpoint, deploy your selected hardware for the specified duration.Request Example
curl -X POST "https://api.io.solutions/enterprise/v1/io-cloud/vmaas/deploy" \
  -H "Content-Type: application/json" \
  -H 'x-api-key: <api-key>'
  -d '{
    "resource_private_name": "name of cluster",
    "duration_hours": 1,
    "gpus_per_vm": 1,
    "hardware_id": 12,
    "location_ids": ["US"],
    "ssh_keys": {
      "name of key": "<public-key>"
    }
  }'
Ensure that the following fields have been assigned a value:
​
resource_private_name
string
required
The name of your cluster.
​
duration_hours
integer
required
Duration of your deployment, in hours.
​
gpus_per_vm
integer
required
Number of GPUs per VM. Value of num_cards from the Hardware List response.
​
hardware_id
string/integer
required
Value of deploy_id from the Hardware List response.
​
location_ids
string
required
Location of your chosen GPU.
​
ssh_keys
object
required
Your public SSH key, use RSA, ECDSA, or ED25519.Format: "name of key": "<public-key>"