curl --request POST \
--url https://api.gcore.com/cloud/v3/gpu/virtual/{project_id}/{region_id}/clusters \
--header 'Authorization: <api-key>' \
--header 'Content-Type: application/json' \
--data '{
"flavor": "g3-ai-32-192-1500-l40s-48-1",
"name": "gpu-cluster-1",
"servers_count": 3,
"servers_settings": {
"credentials": {
"password": "securepassword",
"ssh_key_name": "my-ssh-key",
"username": "admin"
},
"interfaces": [
{
"ip_family": "ipv4",
"name": "eth0",
"type": "<string>"
}
],
"security_groups": [
{
"id": "b4849ffa-89f2-45a1-951f-0ae5b7809d98"
}
],
"user_data": "eyJ0ZXN0IjogImRhdGEifQ==",
"volumes": [
{
"boot_index": 1,
"delete_on_termination": true,
"name": "my-data-disk",
"size": 100,
"source": "<string>",
"tags": {
"key1": "value1"
},
"type": "cold"
}
]
},
"tags": {
"my-tag": "my-tag-value"
}
}'
{
"tasks": [
"d478ae29-dedc-4869-82f0-96104425f565"
]
}
Create a new virtual GPU cluster with the specified configuration.
curl --request POST \
--url https://api.gcore.com/cloud/v3/gpu/virtual/{project_id}/{region_id}/clusters \
--header 'Authorization: <api-key>' \
--header 'Content-Type: application/json' \
--data '{
"flavor": "g3-ai-32-192-1500-l40s-48-1",
"name": "gpu-cluster-1",
"servers_count": 3,
"servers_settings": {
"credentials": {
"password": "securepassword",
"ssh_key_name": "my-ssh-key",
"username": "admin"
},
"interfaces": [
{
"ip_family": "ipv4",
"name": "eth0",
"type": "<string>"
}
],
"security_groups": [
{
"id": "b4849ffa-89f2-45a1-951f-0ae5b7809d98"
}
],
"user_data": "eyJ0ZXN0IjogImRhdGEifQ==",
"volumes": [
{
"boot_index": 1,
"delete_on_termination": true,
"name": "my-data-disk",
"size": 100,
"source": "<string>",
"tags": {
"key1": "value1"
},
"type": "cold"
}
]
},
"tags": {
"my-tag": "my-tag-value"
}
}'
{
"tasks": [
"d478ae29-dedc-4869-82f0-96104425f565"
]
}
API key for authentication. Make sure to include the word apikey
, followed by a single space and then your token.
Example: apikey 1234$abcdef
Project ID
1
Region ID
7
OK
The response is of type object
.
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