Our first (tiny) application of machine learning

Let's get our hands dirty and take a look at our hypothetical web start-up, MLaaS, which sells the service of providing machine learning algorithms via HTTP. With the increasing success of our company, the demand for better infrastructure also increases so that we can serve all incoming web requests successfully. We don't want to allocate too many resources as that would be too costly. On the other hand, we will lose money if we have not reserved enough resources to serve all incoming requests. Now, the question is, when will we hit the limit of our current infrastructure, which we estimated to have a capacity of about 100,000 requests per hour? We would like to know in advance when we have to request additional servers in the cloud to serve all the incoming requests successfully without paying for unused ones.

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