Vast.ai Upgrade & Migration

Current State

!

vastai --version 2>/dev/null || echo 'vastai CLI not installed'

pip show vastai 2>/dev/null | grep -E "^(Name|Version)" || echo 'N/A'

Overview

Upgrade the Vast.ai CLI and Python SDK, handle API changes, and migrate between GPU configurations. The CLI is distributed via PyPI as

vastai

cloud.vast.ai/api/v0

Prerequisites

• Current

  vastai

  CLI installed
• Active instances inventory documented
• Backup of any custom scripts using the API

Instructions

Step 1: Check Current Version and Upgrade

# Check installed version
vastai --version
pip show vastai | grep Version

# Upgrade to latest
pip install --upgrade vastai

# Verify upgrade
vastai --version
vastai show user  # Verify auth still works

Step 2: Detect Breaking Changes

# Compare CLI help output before and after upgrade
import subprocess

def get_cli_commands():
    result = subprocess.run(["vastai", "--help"], capture_output=True, text=True)
    commands = set()
    for line in result.stdout.split('\n'):
        stripped = line.strip()
        if stripped and not stripped.startswith('-') and not stripped.startswith('usage'):
            cmd = stripped.split()[0] if stripped.split() else ""
            if cmd.isalpha():
                commands.add(cmd)
    return commands

# Run before and after upgrade to detect removed commands

Step 3: API Version Migration

# The REST API is at v0 — if Vast.ai introduces v1, update base URL
OLD_BASE = "https://cloud.vast.ai/api/v0"
NEW_BASE = "https://console.vast.ai/api/v0"  # Alternative endpoint

# Test both endpoints
import requests
for base in [OLD_BASE, NEW_BASE]:
    try:
        resp = requests.get(f"{base}/users/current",
                           headers={"Authorization": f"Bearer {api_key}"})
        print(f"{base}: {resp.status_code}")
    except Exception as e:
        print(f"{base}: {e}")

Step 4: Docker Image Updates

# Update GPU workload images to latest CUDA
# Old: pytorch/pytorch:1.13-cuda11.7-runtime
# New: pytorch/pytorch:2.2.0-cuda12.1-cudnn8-runtime

# Test new image locally before deploying
docker pull pytorch/pytorch:2.2.0-cuda12.1-cudnn8-runtime
docker run --rm pytorch/pytorch:2.2.0-cuda12.1-cudnn8-runtime python -c "import torch; print(torch.__version__)"

# Verify CUDA compatibility with target GPU hosts
vastai search offers 'cuda_max_good>=12.1 num_gpus=1' --limit 5

Step 5: Post-Upgrade Verification

#!/bin/bash
set -euo pipefail
echo "Post-upgrade verification..."

vastai show user && echo "  Auth: OK"
vastai search offers 'num_gpus=1 rentable=true' --limit 1 --raw | python3 -c "import sys,json; offers=json.load(sys.stdin); print(f'  Search: OK ({len(offers)} offers)')"
vastai show instances && echo "  Instances: OK"

echo "Upgrade verified."

Output

• CLI upgraded to latest version
• Breaking changes identified
• API endpoint compatibility verified
• Docker images updated to latest CUDA
• Post-upgrade verification passed

Error Handling

pip install vastai==0.2.8

vastai set api-key YOUR_KEY

cuda_max_good>=VERSION

Resources

• vastai PyPI
• vast-cli GitHub
• Vast.ai Documentation

Next Steps

For CI/CD integration, see

vastai-ci-integration

Examples

Safe upgrade: Pin the current version in

requirements.txt

CUDA migration: Move from CUDA 11.7 to 12.1 by updating Docker images and filtering offers with

cuda_max_good>=12.1