Accessing Storage

NeevCloud provides multiple ways to access your storage, depending on whether you prefer command-line interfaces or browser-based interactive environments.

Default Mount Path

All storage volumes automatically mount at /data on your GPU instance. This standardized path simplifies your workflows:

# Your storage is always available at:
cd /data

# List your data:
ls -lh /data

# Check storage usage:
df -h /data

You don't need to configure mount points or fstab entries—everything is ready to use when your instance starts.

SSH Access

SSH gives you direct terminal access to your GPU instance and its attached storage. This is ideal for running training scripts, managing files, or executing command-line tools.

Connection Syntax

ssh -i /path/to/key-pair-name.pem -p <PORT> root@<IP_ADDRESS>

Example

ssh -i ~/.ssh/neevcloud-key.pem -p 30890 [email protected]

What each parameter means:

• -i /path/to/key-pair-name.pem: Path to your private SSH key file

• -p 30890: SSH port number (you'll get this from your instance details)

• [email protected]: Username and IP address of your instance

Once connected via SSH, you can:

# Navigate to your storage
cd /data

# Upload datasets using scp from your local machine
scp -i ~/.ssh/neevcloud-key.pem -P 30890 dataset.tar.gz [email protected]:/data/

# Download model checkpoints to your local machine
scp -i ~/.ssh/neevcloud-key.pem -P 30890 [email protected]:/data/model_checkpoint.pth ./

# Run your training script
python /data/train.py --config /data/config.yaml

# Check storage usage
df -h /data
du -sh /data/*

Jupyter Notebook Access

Jupyter Notebook provides an interactive browser-based environment perfect for exploratory data analysis, model prototyping, and visualization.

How to Access

1. Navigate to your instance details from the NeevCloud dashboard.

2. Click the "Open Jupyter Notebook" button.

3. Your browser opens a Jupyter environment with /data already accessible.

Working with Your Storage in Jupyter

import os
import pandas as pd

# Your storage is mounted at /data
data_path = '/data'

# List files in your storage
print(os.listdir(data_path))

# Load a dataset from your storage
df = pd.read_csv('/data/training_data.csv')

# Save results back to your storage
model.save('/data/checkpoints/model_epoch_10.h5')

# Check available space
import shutil
total, used, free = shutil.disk_usage('/data')
print(f"Free space: {free // (2**30)} GB")

Use Jupyter Notebook when you:

• Need to visualize data or training metrics.

• Want to interactively explore datasets.

• Need to document your workflow with markdown and code.

Comfy UI Access

Comfy UI is a browser-based interface specifically designed for AI workflows, particularly image generation and processing pipelines.

How to Access

1. Go to your instance details from the NeevCloud dashboard.

2. Click the "Open Comfy UI" button.

3. Your browser launches the Comfy UI environment.

Working with Storage in Comfy UI

• Access your models, datasets, and outputs directly through the UI.

• Your /data directory is available for loading custom models.

• Save generated outputs to /data for persistence.

Use Comfy UI when you:

• Are working with diffusion models or image generation.

• Need a visual workflow builder.

• Want to quickly iterate on AI pipelines without writing code.

Best Practices for Access

Security

• Keep your SSH private keys secure and never share them.

• Use strong key passphrases.

• Rotate keys periodically for production workloads.

File Management

• Organize data in /data with clear directory structures.

• Use descriptive filenames and directory names.

• Clean up temporary files to avoid filling storage.