Skip to main content
Monitor, update, and control your deployed AI models with comprehensive management tools for scaling and maintenance.

List Your Deployments

View all your active deployments:
  • CLI
  • Python SDK
  • JavaScript SDK
gravixlayer deployments list
Example Output:
Found 1 deployment(s):

Deployment ID: 5865969c-a1dc-4509-9651-89758b27c87c
Deployment Name: test_model
Model: qwen3-1.7b
Status: running
GPU Model: NVIDIA_T4_16GB
GPU Count: 1
Min Replicas: 1
Max Replicas: 1
Created: 2025-09-17T09:16:39.304602Z

Get Deployment Details

  • Python SDK
  • JavaScript SDK
import os
from gravixlayer import GravixLayer

client = GravixLayer()

# Get specific deployment details
deployment_id = "your-deployment-id"
deployment = client.deployments.get(deployment_id)

print(f"Deployment Details:")
print(f"  Name: {deployment.name}")
print(f"  Model: {deployment.model}")
print(f"  Status: {deployment.status}")
print(f"  GPU Model: {deployment.gpu_model}")
print(f"  GPU Count: {deployment.gpu_count}")
print(f"  Min Replicas: {deployment.min_replicas}")
print(f"  Max Replicas: {deployment.max_replicas}")
print(f"  Created: {deployment.created_at}")
print(f"  Updated: {deployment.updated_at}")

Monitor Deployment Status

  • Python SDK
  • JavaScript SDK
import os
import time
from gravixlayer import GravixLayer

client = GravixLayer()

def monitor_deployment(deployment_id, check_interval=30):
    """Monitor deployment status until it's ready"""
    print(f"Monitoring deployment: {deployment_id}")
    
    while True:
        try:
            deployment = client.deployments.get(deployment_id)
            status = deployment.status
            
            print(f"Status: {status}")
            
            if status == "running":
                print("✅ Deployment is ready!")
                break
            elif status == "failed":
                print("❌ Deployment failed!")
                break
            elif status in ["creating", "starting"]:
                print(f"⏳ Deployment is {status}... checking again in {check_interval}s")
                time.sleep(check_interval)
            else:
                print(f"ℹ️ Unknown status: {status}")
                time.sleep(check_interval)
                
        except Exception as e:
            print(f"Error checking deployment: {e}")
            break

# Monitor a deployment
monitor_deployment("your-deployment-id")

Hardware Information

  • CLI
  • Python SDK
  • JavaScript SDK
List Available Hardware:
gravixlayer deployments gpu --list
Get Hardware as JSON:
gravixlayer deployments gpu --list --json
Example JSON Output:
[
  {
    "accelerator_id": "2d7c7178-aa1d-4b27-840d-ca8c0f35d5b1",
    "gpu_id": "2d7c7178-aa1d-4b27-840d-ca8c0f35d5b1",
    "pricing": 0.39,
    "status": "available",
    "updated_at": "2025-09-08T01:35:50Z",
    "gpu_model": "NVIDIA_T4_16GB",
    "gpu_link": "pcie",
    "gpu_memory": 16
  }
]

Delete Deployments

  • CLI
  • Python SDK
  • JavaScript SDK
gravixlayer deployments delete a7283154-5ab2-42a4-b221-03c61664fa22
Example Output:
Deleting deployment a7283154-5ab2-42a4-b221-03c61664fa22...
Deployment deleted successfully!
Response: {'message': 'deployment deleted successfully', 'status': 'success'}
I