Azure OpenAI
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Let's connect a python app in one virtual private network with an Azure OpenAI model configured with private endpoint in another virtual private network. You will use the Azure CLI to create these virtual networks and resources.
Each company’s network is private, isolated, and doesn't expose ports. To learn how end-to-end trust is established, please read: “”
Run the following commands to install Ockam Command and enroll with the Ockam Orchestrator. This step creates a Project in Ockam Orchestrator.
Then run the following commands:
If everything runs as expected, you'll see the answer to the question: "What is Ockham's Razor?".
In a typical production setup an administrator or provisioning pipeline generates enrollment tickets and gives them to nodes that are being provisioned. In our example, the run function is acting on your behalf as the administrator of the Ockam project.
First, the ai_corp/run.sh
script creates a network to host the application exposing the Azure OpenAI Service Endpoint
Network Infrastructure:
Azure OpenAI Service Configuration:
We set up a private endpoint for secure access:
OpenAI Model Deployment:
We retrieve the API key for authentication.
We create an environment file (.env.azure) containing:
The Azure OpenAI endpoint URL.
The API key for authentication.
Virtual Machine Deployment:
Replaces SERVICE_NAME and TICKET placeholders.
Place it in the configured VNet/subnet.
Generate SSH keys for access.
Inject the processed Ockam setup script as custom data.
The default Network Security Group (NSG) is configured with basic rules: inbound SSH access (port 22), internal virtual network communication, Azure Load Balancer access, and a final deny rule for all other inbound traffic. For outbound, it allows virtual network and internet traffic, with a final deny rule for all other outbound traffic.
Ensure your Azure Subscription has access to deploy the "gpt-4o-mini" model (version: 2024-07-18). You may need to request quota/access for this model through the Azure Portal if not already enabled for your subscription.
First, the health_corp/run.sh
script creates a network to host the client.py
application which will connect to the Azure OpenAI model:
Network Infrastructure Setup:
VM Deployment and Ockam Setup:
${SERVICE_NAME} with the configured service name.
${TICKET} with the provided enrollment ticket.
Use latest RHEL 8 LVM Gen2 image.
Generate SSH keys automatically.
Inject the processed Ockam setup script as custom data.
Client Application Deployment:
We wait for VM to be accessible.
Transfers client.py to the VM.
Copies .env.azure configuration file containing OpenAI credentials.
Install Python 3.9 and pip.
Install the OpenAI SDK.
Client Application Operation:
The client.py application:
Sends queries to the model.
We connected a Python application in one virtual network with an application serving an Azure OpenAI model in another virtual network over an end-to-end encrypted portal.
Sensitive business data coming from the Azure OpenAI model is only accessible to AI Corp. and Health Corp. All data is encrypted with strong forward secrecy as it moves through the Internet. The communication channel is mutually authenticated and authorized. Keys and credentials are automatically rotated. Access to connect with the model API can be easily revoked.
Health Corp. does not get unfettered access to AI Corp.'s network. It gets access only to run API queries to the Azure OpenAI service. AI Corp. does not get unfettered access to Health Corp.'s network. It gets access only to respond to queries over a TCP connection. AI Corp. cannot initiate connections.
All access controls are secure-by-default. Only project members, with valid credentials, can connect with each other. NATs are traversed using a relay and outgoing TCP connections. AI Corp. or Health Corp. don't expose any listening endpoints on the Internet. Their Azure virtual networks are completely closed and protected from any attacks from the Internet through Network Security Groups (NSGs) that only allow essential communications.
To delete all Azure resources:
for Ockam and pick a subscription plan through the guided workflow
This example requires Bash, Git, Curl, and the Azure CLI. Please set up these tools for your operating system. In particular you need to with az login
.
The script, that you ran above, and its are full of comments and meant to be read. The example setup is only a few simple steps, so please take some time to read and explore.
The calls the which invokes the to create an new identity, sign into Ockam Orchestrator, set up a new Ockam project, make you the administrator of this project, and get a project membership credential.
The run function then The tickets are valid for 60 minutes. Each ticket can be redeemed only once and assigns to its redeemer. The is meant for the Ockam node that will run in AI Corp.’s network. The is meant for the Ockam node that will run in Health Corp.’s network.
The run function passes the enrollment tickets as variables of the run scripts provisioning and .
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using credentials from .env.azure.
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