Firewall Rules for Ingress TensorFlow Model Serving Traffic

Question

Pulumi · Accepted Answer

When serving a TensorFlow model, it's common to have a server that listens to incoming traffic on a specific port (often port 8501 for the TensorFlow Serving REST API) and processes the requests. To protect and control the access to the model serving server, you need to set up firewall rules that allow incoming traffic to the appropriate port from authorized IP ranges while blocking all other traffic.

To implement firewall rules for controlling ingress TensorFlow Model Serving traffic using Pulumi, we will create a resource representing a firewall rule that allows traffic on the specific port TensorFlow Serving uses. In this example, we will use Google Cloud Platform (GCP) as the cloud provider, though the process would be similar for other providers like AWS or Azure.

We will use the `gcp.compute.Firewall` resource from the Pulumi GCP package to create a firewall rule. This resource manages a set of firewall rules for your GCP project. The firewall rule will specify the allowed incoming connections based on IP ranges (source ranges), protocols, and ports.

Here's a Pulumi program written in Python that sets up these rules:

```python
import pulumi
import pulumi_gcp as gcp

# The configuration of the firewall rule
# We will allow TCP traffic on port 8501 which is commonly used by TensorFlow Serving
# Adjust the source_ranges based on who is allowed to access the model serving server
tensorflow_serving_firewall_rule = gcp.compute.Firewall("tensorflow-serving-firewall",
    network="default",  # Assuming the 'default' network, replace with your specific network if needed
    allows=[
        gcp.compute.FirewallAllowArgs(
            protocol="tcp",
            ports=["8501"],
        )
    ],
    source_ranges=["0.0.0.0/0"],  # WARNING: This allows access from any IP, you should restrict this to known IPs
    description="Allow incoming traffic on TCP port 8501 for TensorFlow Serving"
)

# Export the name of the firewall rule
pulumi.export("firewall_rule_name", tensorflow_serving_firewall_rule.name)
```

In this program, we create a firewall rule named `tensorflow-serving-firewall` which allows TCP traffic on port 8501 from any IP address. In practice, you would want to limit `source_ranges` to specific known IP address ranges to reduce the risk of unauthorized access.

The `network` field is set to `"default"` which means this rule will be applied to the default network in your GCP project. If you are using a different network, make sure to update it accordingly.

Finally, we export the name of the firewall rule so it can be easily identified in the output of the `pulumi up` command.

Please note that using `"0.0.0.0/0"` for `source_ranges` is not recommended for production environments due to security risks. Instead, use specific IP ranges that need access to your TensorFlow model server.