Platform Engineering

Back in 2017-2018, everyone wanted to be a data scientist. Then reality hits, that they need a data engineer for a successful machine learning project. Things didn’t end there, since they also need a machine learning engineer to create production-ready code. Some people think you only need an MLE and suddenly your ML project would become a reality, sadly the reality begs to differ, because you also need to find someone to deploy and scale it, enter DevOps engineer (who understands ML, this is very important)....

CSV as a file format is very versatile, almost any programs can parse it. The only issue is you can’t use SQL against CSV files directly. This is a major pain point, since using SQL is so much faster than firing up a jupyter notebook and wrangle the data in python, or use Excel and apply transformations until you get desired results. But the question is how do we use SQL against CSV files in the first place....

Platform engineering is all the rage these days. Often, you’ll often hear this term with the keyword DevX. How are they related? Imagine you are working on a microservice backend. You are just starting out, so you don’t have much features to work on yet. But as a PoC, you only need to [fetch data] and [return aggregated price]. You can do microservices on Kubernetes, but you are not familiar with DevOps so you turn to a cloud provider - AWS....