Markizano.NET

In response to a LinkedIn post I came across (If you are part of the AWS Certification & Training ). I hit the character limit 😅, so extending on that here. DevOps Automation DevOps has been trying to automate itself out of its role since its inception. That was the whole point of the role in the first place and yet still many orgs are facing: Totally custom setups and never-ending edge cases. Operational dysfunction. Multiple disjointed tools that perform the same functions. Development teams operating in silos that don't conform to the federated guidance DevOps is attempting to implement. Incomplete monitoring systems or multiple monitoring tools that don't cross communicate. Incredibly ever complex logs with vague descriptions as to what actually went wrong. Office politics where confusion exists around role and responsibility when the pipeline breaks. Current Challenges Many orgs are still: In the phase of getting away from monolithic apps into micr...

Regarding: ChatGPT's recent release of Codex I can see so many ways in which this can go right and wrong and in between. Ways it can go right: Vibe Coding : Developers are starting to learn how to incorporate and use LLM's with coding software. This whole "vibe coding" movement is another tool, not a replacement to writing code. There are far too many edge cases and problems with Vibe Coding that warrants a skilled developer to be able to troubleshoot issues and offer a creative hand where LLM's cannot provide. Developer Workflow : I've seen where folks are starting to learn how to spoon feed the LLM a prompt about a specific context, let it work on that context, review the changes, then work on the next context as completion runs along. This isn't new. I've seen devs plan out their functions before filling the body of them with the operations they should consume. This results in more efficient development and hence the reason why TDD ( Test Drive...

The messed up part about AI that nobody's talking about is how it slows down senior engineers. While it may be great at "Hello world" and simple algorithms, many times, senior engineers are way past this, and don't really need help building boiler plate code because it just doesn't scale. I find myself more often than not, fighting with AI in some cases rather than using it to write stuff for me that I need done quickly. From custom algorithms or complex situations where scale, multiple contexts or hidden details about how computers and coding works that you don't gain from the RactJS tutorials, even design patterns that are gained from learning other languages cannot be captured and implemented by AI just yet (learn how C and C++ works and then tell me you know how to code properly in JavaScript) to its inability to write in Angular vs ReactJS or even use a different language other than Python for a product solution. We all know JavaScript and Python are not...