Chapters
Learn how you can use an isolated environment in Azure to safely deploy AI models like ChatGPT, Meta Llama, Mistral, and those available on Hugging Face.
Many of us want to tap into the potential of artificial intelligence but are concerned about data privacy. An isolated environment is an ideal solution that combines the flexibility of AI with a high level of security.
What is an Isolated Environment?
An isolated environment is a technology that allows applications and AI models to run in a space that’s separated from the rest of the network and systems. In Azure, tools like Azure Virtual Network (VNet) and virtualization services enable us to ensure that large language models (LLMs) operate within a secure, enclosed area.
Why use an isolated environment?
- Data Security: Using an isolated environment limits access to your company’s sensitive data. Communication between ChatGPT and the rest of your infrastructure can be tightly controlled.
- Complete Control: With an isolated environment, you have control over all processes occurring within, including network configuration, authorization, and activity logging.
- Compliance: Many industries, especially those bound by strict regulations, require data processing within compliant environments. Azure offers a range of tools to help you meet these requirements.
Example Use Case
Imagine a consulting firm that wants to improve its internal client communications using ChatGPT. By leveraging an isolated environment in Azure, they can deploy a model that helps their team generate meeting summaries and client recommendations, without worrying about exposing personal or sensitive information.
Step-by-step guide: setting up resources in Azure
There are two main scenarios. For those who already have configured resources, we’ll skip this part, as users familiar with Azure likely have Resource Groups in place. For a completely new Azure account, simply add a payment method, select a subscription, and you’re ready to go.
Once your payment method and subscription are added, go to Azure Resources and log in to your account. You’ll see the resource screen. If it looks different, a prompt at the top should allow you to switch views.
Click the “+ New hub” button, select a name for your hub, choose a subscription, and most settings should auto-configure. Click Next, then Create. Be patient, as setting up resources may take a few moments.
After the resources are set up, you’ll be redirected to AI Studio within your hub.
Navigate to Playgrounds > Chat. Once the interface loads, on the left side next to the deployment field, click “Create new deployment.” You’ll see a screen where you can select a model—here, we’ll use the GPT-4o-mini. Choose it from the list and click “Confirm.”
Be patient again as resources load, and then confirm Deploy. (You can customize the model, but today we’ll keep things simple.)
Return to Playgrounds > Chat, where you can select and configure your model with system messages, additional data dimensions, and parameters like Temperature to control how often the model generates imaginative responses.
Your model is now ready to use, you can proceed with some additional steps of configuration to ensure secure access.
Setting up an isolated environment in Azure
- Virtual Machines or Containers: Run ChatGPT in a container or on a virtual machine within the VNet. Additionally, you can set up a Network Security Group (NSG) to restrict network traffic.
- Use Private Endpoints: Secure access to services by using Private Link, which ensures safe communication between Azure resources.
Conclusion
Using an isolated environment in Azure is a fantastic way to secure AI model usage, such as ChatGPT. If your company is interested in AI’s potential but values data protection, this solution is worth considering.
Feel free to reach out with any questions about this technology or for assistance with its implementation. We’re here to help!
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