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AI Use Cases in Enterprise: AWS stack and how to handle it ( money wise)
Do you work with #AWS? Have you ever wondered who is the human behind watching all the AWS Services? No? Aren’t you a bit curious how it all comes to life? It’s been over ten years since I first came to know AWS and such. Every three or so years, I take classes in some form or fashion. They have not changed their font or font size since 2013 for sure; they did change some app names, and they did change some stuff, but in a nutshell, it just keeps growing and growing.
So, my AI use case for any of you who is looking is to make robots to handle all those services ( see below). What is the business value? Imagine you have one ( just one) engineer on average assigned to each of those. Nah? Yeah, it does not scale if you are a startup or short on staff.
I know I have AWS friends, so I will blatantly ask — who and how watches the roadmap from the “customer’s” perspective. What is the justification for so many services that technically could be consolidated ( and billed as one). I mean, it’s not like you should use service A from AWS, service B from GCS, and so on. Wouldn’t you want an all-in-one package with a “low-code no code ease of use and straightforward billing?”.
//Rant over
