1. Using Cloudflare Rules to Throttle Access to AI Applications


    To throttle access to AI applications using Cloudflare, you can leverage the cloudflare.RateLimit resource from the Cloudflare Pulumi package. This resource allows you to create rules that specify how many requests can be made to certain endpoints or URL patterns within a set time frame. When this limit is exceeded, Cloudflare blocks further requests for a certain time or challenges them with CAPTCHAs or JavaScript computations, depending on the configured action.

    Here's a detailed explanation of how this can be done:

    1. Rate Limiting Resource: You use the cloudflare.RateLimit resource to define the conditions under which the rate limiting will be applied. This includes defining the URL pattern to match incoming requests, the number of requests to be allowed within a certain period (in seconds), and the action to take when the limit is exceeded.

    2. Threshold and Period: These are critical aspects of rate limiting and define the limit and the window of time for which this limit is considered. For example, if the threshold is 1000 and the period is 60, that means you're allowing 1000 requests per minute to your application.

    3. Action: When the threshold is exceeded, an action is taken. This can be a 'simulate' action which is effectively a no-op (useful for testing), a 'challenge' action which makes the requester complete a CAPTCHA, a 'js_challenge' action which makes the requester complete a JavaScript computation, or a 'ban' which blocks access for the timeout period.

    4. Match Request: Here, you can specify what types of requests are counted towards the rate limit. For example, you might only want to throttle POST requests or requests with certain headers.

    Now, let's write the Pulumi program:

    import pulumi import pulumi_cloudflare as cloudflare # Assuming that you have previously set up a Cloudflare Provider and have your Zone ID. # Replace the placeholder below with your actual Zone ID. zone_id = 'your-zone-id-here' # Define a Cloudflare Rate Limit rule rate_limit = cloudflare.RateLimit('ai-app-rate-limit', zone_id=zone_id, threshold=100, # Number of requests to allow per period before taking action period=1, # The period of time (in seconds) to evaluate the request count action={ 'mode': 'simulate', # Action to enforce when the threshold is exceeded, options are: simulate, challenge, js_challenge, ban. 'timeout': 60, # The time (in seconds) to enforce the action 'response': { 'content_type': 'text/plain', # The content type of the response if the action is set to simulate. 'body': 'The request limit has been exceeded!' # The body message of the response if the action is set to simulate. } }, match={ 'request': { 'methods': ['GET', 'POST'], # Methods to apply rate limiting 'schemes': ['HTTP', 'HTTPS'], # Schemes to apply rate limiting 'url_pattern': '*/ai-application-endpoint' # URL pattern to match the incoming requests that should be limited } } ) # Export the ID of the rate limit rule so it can be obtained from the stack output. pulumi.export('rate_limit_id', rate_limit.id)

    In the program above:

    • We create a rate limit rule for a fictitious endpoint '*/ai-application-endpoint' under your Cloudflare-managed domain.
    • We've set the rate limit to 100 requests per second, and the action to 'simulate' with an explanatory body message. This is a safe way to start as it lets you observe the effect without impacting your users.
    • We've chosen to apply this rate limit to both GET and POST requests and to both HTTP and HTTPS schemes.

    You can adjust the threshold, period, action, and match parameters according to your specific use case needs.

    Remember to replace 'your-zone-id-here' with your actual Cloudflare Zone ID and adjust the 'url_pattern' to match the specific endpoint of your AI application you wish to protect. Once you deploy this Pulumi program, the rate limiting rule will be active for your Cloudflare zone, helping to throttle access according to the settings you've defined.