Putting the pieces together for your own ML pipeline A lot of tutorials I find only cover a portion of an overall working solution. Some may show a Notebook (we’ll get
Human understanding of AI Several years ago I set out to learn more about AI and machine learning (ML) and how I could apply it at my own companies, or at
At DoiT International, we work with a variety of software companies around the globe. We frequently receive requests to solve similar problems from multiple customers. Recently, I witnessed several cases
At DoiT International we work with customers small and large, and from time to time we recognize common issues, especially with some of our larger-scale customers. A recent issue upgrading
Recently I was scheduled for a 1-hour architecture review video chat with a customer who was trying to solve two challenges: alert lag and cloud storage spend. This was a
I’m often asked, “what’s it like to work at DoiT?” Although employed here for just over 7 months, as a previous customer, I feel like I’ve been part of the
Installing multi-cloud Kubernetes on AWS In the first post we explored a preview of Anthos GKE running on AWS, and some of the use cases and functionality it brings to the
Why would anyone want to run GKE on AWS you might ask? That’s a fair question and the reasons may vary company to company. Some common use cases may include:
Pipeline (not the kind we’re talking about here) A popular feature offered by Heroku is their Review Apps solution. It generates a disposable environment and instance of an app during a
Sometimes engineers scour tutorials and articles trying to figure out how to get their app or some component of their stack to work or deploy. One such case recently was
