Local Kubernetes With Kind
Reading about architecture is one thing, but actually seeing a cluster run is where it sticks. In the third chapter of Big Data on Kubernetes, Neylson Crepalde moves from theory to practice.
Reading about architecture is one thing, but actually seeing a cluster run is where it sticks. In the third chapter of Big Data on Kubernetes, Neylson Crepalde moves from theory to practice.
In the last post, we talked about the “brain and muscles” of a Kubernetes cluster. But how do we actually tell that brain what to do? We use Objects.
If you want to run big data workloads on Kubernetes, you have to understand how the system is actually put together. It’s not just “magic magic cloud stuff”—it’s a carefully coordinated cluster of machines.
We are living in a world where data is basically everywhere. From your phone to social media and every single online purchase, the amount of info we generate is staggering. But here’s the thing: just having data isn’t enough. You have to be able to process it, and that’s where things get complicated.