Store, Serve, Scale: Unlock AI Pipelines with Nebula Block Object Storage

Whether you're fine-tuning a language model or powering real-time inference, the backbone of any scalable AI pipeline is efficient, accessible storage. With Nebula Block’s S3-compatible Object Storage, you get the flexibility and control to move faster—from experimentation to production—without touching heavy infrastructure.

🔹 Store: Foundation for Your ML Workflows

Nebula Block lets you host everything from model checkpoints to training datasets and pipeline assets in a secure, encrypted storage layer:

• Fully compatible with S3 tools like boto3, AWS CLI, and Cyberduck
• Supports public and private buckets
• Works seamlessly with fine-tuned models, RAG pipelines, and multimodal stacks

🔹 Serve: Turn Stored Models into APIs

Once stored, your models can be deployed to GPU-backed runtimes or serverless endpoints in minutes. Nebula Block supports:

• Instant mounting from Object Storage to inference containers
• OpenAI-compatible APIs for serving LLMs
• Support for vLLM, DeepSeek, Claude, Llama.cpp, and more

🔹 Scale: Build Beyond Single Use Cases

With Nebula Block’s modular design, you can go from single deployment to full-stack AI systems:

• Train and fine-tune on A100/H100/H200 GPUs
• Feed documents into RAG frameworks like LangChain or LlamaIndex
• Serve thousands of requests with automatic scaling and per-second billing

It’s not just object storage—it’s the connective tissue of your AI infrastructure.

How to store with Nebula Block?

• Navigate to Object Storage
• Select "Continue Creating Object Storage"

• Select "Ownership", set the "Label", "Storage Type" and "Location"

• "Create" and the Dashboard will show information like this:

• Select "Buckets", set the Name and "Create"

Note: You can set the privacy status of the Buckets. When public, objects can be accessed directly via permanent URL. When private, you must generate a time-limited download link.

Step-by-Step: Use Nebula Block Object Storage (S3-compatible)

Nebula Block’s Object Storage is fully S3-compatible, meaning you can easily upload, store, and manage files — just like using AWS S3, but with simpler pricing and faster setup. To interact with Object Storage using Python, follow these steps:

1. Locate Your Access Information

From the dashboard:

• Endpoint (Hostname): e.g., s3-us-east.nebulablock.com
• Access Key / Secret Key: Copy from your “S3 Credentials” section
• Bucket Name (automatically created when you set up storage)

2. Connect Using Python (boto3)

• Install dependencies

pip install boto3 python-dotenv

• Create a .envfile in your working directory:

NEBULA_ACCESS_KEY=YOUR_ACCESS_KEY  #Use the Access Key from the Details page.
NEBULA_SECRET_KEY=YOUR_SECRET_KEY  #Use the Secret Key from the Details page.
NEBULA_ENDPOINT=YOUR_ENDPOINT_URL  #Use the Hostname from the Details page.
NEBULA_REGION=YOUR_REGION          #Optional, default None.
NEBULA_BUCKET=YOUR_BUCKET_NAME

• For a full working script, check out our Upload/Download File Demo.
• Run the Code

python your_script_name.py

Make sure to have the boto3 and python-dotenv libraries installed and your .env file properly configured with your Nebula Block credentials.

3. Tips for Usage

• Public access: If the object is public, it can be accessed via a permanent URL.
• Private access: You’ll need to generate a signed (temporary) download link using the Nebula API (coming soon).
• Use Cases:
  • Host fine-tuned LLMs or checkpoints
  • Store datasets for inference pipelines
  • Feed documents into a RAG system (like LangChain, LlamaIndex)
• Pricing:
  • Storage: Free
  • Outgoing Traffic: $0.01 per GB

Use Cases

• Host your fine-tuned LLMs and load them into Nebula GPU endpoints
• Serve assets for AI inference, apps, or data pipelines
• Store training datasets, logs, or large files securely
• Integrate directly into tools like LangChain, LlamaIndex, etc.

Why This Is Game-Changing

Nebula Block's architecture is optimized for speed, flexibility, and cost-efficiency:

Final Thoughts

You’ve fine-tuned the model — now serve it like a pro. With Nebula Block, your weights in object storage are just one API call away from real-time inference. Host models like code, mount like data, and serve at GPU speed — without touching infra today.

Next Steps

Sign up and explore now.

🔍 Learn more: Visit our blog and documents for more insights or schedule a demo to optimize your search solutions.

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