Scaling cloud infrastructure is one of those super buzzwordy phrases, so in this video I break it down in a way that actually makes sense—and then we build it for real. I start by defining infrastructure (hardware, storage, networking) and what “cloud infrastructure” really means: virtualizing those resources so you can change what you’re using on the fly. Scaling is simply dialing resources up when demand spikes (more CPU, more memory, more storage) and dialing them back down when traffic drops so you’re not paying for a bunch of unused capacity. Then I walk through deploying a simple Dockerized Python Flask app from GitHub onto IBM Cloud infrastructure using Red Hat OpenShift. I fork the repo so I can own the code and change it later, create a project in the OpenShift developer console, import from GitHub, and make sure there’s a public route so the app is accessible on the internet. After that, we get to the real problem: engineers tend to overprovision because predicting resource needs is hard. That’s why I bring in IBM Turbonomic—an optimization tool that proposes (and can automate) actions like resizing vCPU and memory based on actual utilization, so your app performs well at the lowest possible cost.