1. Filtering Traffic to Cloudflare-hosted ML Services


    To filter traffic to Cloudflare-hosted Machine Learning (ML) services, you would typically utilize a combination of DNS settings, firewall rules, access policies, and possibly load balancing if you want to distribute your traffic across different origins. Cloudflare provides several options to manage and filter traffic, ensuring that only legitimate and intended traffic reaches your ML services. In the context of Pulumi, these configurations can be managed as code, allowing you to deploy and update your traffic routing and security settings in a reproducible way.

    Below is a Python program using Pulumi to set up traffic filtering for ML services hosted behind Cloudflare.

    1. DNS Configuration: We will set up a DNS record for your ML service to ensure that all traffic goes through Cloudflare.

    2. Cloudflare Filter & Firewall Rules: We will create a Cloudflare filter to define the pattern that matches traffic to be moderated, and then apply firewall rules that use this filter to allow, challenge, or block traffic based on the pattern.

    3. Access Rules: We may also set up access rules to further restrict who can access the ML services, based on IP addresses, geolocation, or other factors.

    Here is a Pulumi program that illustrates how these Cloudflare resources could be configured:

    import pulumi import pulumi_cloudflare as cloudflare # Parameters (These would usually come from configuration or environment variables) zone_id = "your-cloudflare-zone-id" # Replace with your Cloudflare Zone ID dns_name = "ml-service.yourdomain.com" # Replace with the domain of your ML service # DNS record for the ML service pointing to Cloudflare ml_dns_record = cloudflare.Record("ml-dns-record", zone_id=zone_id, name=dns_name, type="A", value="IP_ADDRESS_OF_YOUR_ORIGIN", # Replace with the IP address of your origin server proxied=True # Traffic will flow through Cloudflare ) # Filter configuration for traffic to your ML service ml_traffic_filter = cloudflare.Filter("ml-traffic-filter", zone_id=zone_id, expression="(http.request.uri.path ~ \"^/api/v1/ml\")", # Example: Filter traffic to the ML API path paused=False, description="Filter for ML Service API" ) # Firewall rule to challenge traffic not matching the filter criteria for your ML service ml_firewall_rule = cloudflare.FirewallRule("ml-firewall-rule", zone_id=zone_id, filter_id=ml_traffic_filter.id, action="challenge", # Challenge the request (CAPTCHA). Options: ["block", "challenge", "allow", "js_challenge"] description="Challenge traffic to ML Service API" ) # Access rule to restrict traffic by IP address (optional) ml_access_rule = cloudflare.AccessRule("ml-access-rule", zone_id=zone_id, configuration={ "target": "ip", # Type of rule, for example, it can be "ip", "ip_range", or "asn" "value": "" # Specific IP to allow or block }, mode="whitelist", # Options: ["whitelist", "block"] notes="Only allow this specific IP to access the ML service" ) # Export the DNS and Firewall Rule IDs pulumi.export("dns_record_id", ml_dns_record.id) pulumi.export("firewall_rule_id", ml_firewall_rule.id)


    • We start by importing the necessary Pulumi modules (pulumi and pulumi_cloudflare).
    • We define zone_id and dns_name which you need to replace with your specific Cloudflare zone ID and ML service DNS name.
    • The ml_dns_record resource creates a DNS A record that points to your ML service's IP address and ensures the traffic is proxied through Cloudflare.
    • Next, ml_traffic_filter defines the pattern for the traffic that needs to be filtered. In this case, it's setup to filter traffic aimed at the /api/v1/ml path.
    • The ml_firewall_rule applies the filter created above to challenge traffic. You can change the action to "block", "allow", or "js_challenge" based on your needs.
    • (Optional) The ml_access_rule shows how you can further restrict access to the ML services, by allowing only specific IP addresses.
    • Finally, we export the IDs of the DNS and Firewall Rule resources, so you know they have been created and can reference them if necessary.

    Make sure to replace placeholder values such as your-cloudflare-zone-id, ml-service.yourdomain.com, and IP_ADDRESS_OF_YOUR_ORIGIN with actual values to reflect your infrastructure correctly.