Hello, My name is Vasudevan Perumal.
I’m an computer systems generalist, with a some battle scars(aka experience) in Linux distribution engineering, and building systems to provision and manage devices at scale using cloud-native technologies. Right now, I build cloud-native endpoints for robotics systems at Amazon. What is a cloud-native endpoint you might ask?
Cloud-native endpoints are devices that can be deployed from anywhere. They receive their applications and configurations dynamically from the cloud, and can easily be reset or restored. These systems don’t generally require a direct connection to any on-premises resources for usability or management.
To know me better, and what I am about, quick, I think sharing some principles I follow is the best way. Here are some are these principles.
- Always reason from first principles.
- Respect what came before.
- Have strong opinions, but loosely held.
- Be stubborn on the vision, flexible on the approach.
- Iterative improvement, than perfection.
I really love tinkerering and, I never shy away from a problem stating, it’s not my expertise. I try my best to learn any domain, dive deep, and find an holistic answer. The way I do this, is through brute force probing the question, and learning histroically what has been the answer. History is a great informer, of the current problem you have to solve. I do this through search tool(google, the best AI model I have access to etc.), and reading as much documentation I can. With an informed understanding, I then reachout to team members and folks with experience to share my perspective and learn from their experience. Running through this loop a couple of times, as always yielded with a deeper understanding, and answers that are not only correct but when implemented are sustainable for the longer term.
What am I doing now as 04/06/2025? I have been diving deeper in my quest to understand compute systems. This is a field I fell into, I started out to become a network engineer.
I have been learning Rust, and system programming techniques, undertanding Linux internals better, like sockets. Learning async programming in python, and Rust, this topic I have not dabbled with professionally yet.
On the side, I am also working on Project Lamper, as a method to learn new agentic AI technologies. The problem I want to solve is to make the Sys admin job as accessible to non-technical folks as possible. Making the average person, self-sufficient to fix their IT problems on their own. Through an architecture of running SLM(small language models) like Gemma3:1b locally, and the combination of RAG for context augmenation, fine-tuning for context awareness of your system, and finally function calling and local inference. My aim is to take a open ended my computer freezes sometimes, and completely local mechanism for anyone to understand why their computer is behaving in a certain way. The practicality of this solution is yet to tested, hopefully quantization techniques improve exponentially over the years.