With the advent of DevOps and “you build it, you own it”, the tech stack has evolved a lot for the modern startup. There are hundreds of dev tools launched in the last decade which have completely changed how developers manage their workloads. Recently, We evaluated this landscape very thoroughly at RunX and here is our opinionated guide.

Cloud: GCP

You can’t go wrong with any of the 3 big clouds (AWS, Azure, GCP). All of them have the full feature set needed by a company of any scale. There are still a couple of factors which might affect your decision:

An opinionated setup guide for your next python project

Python is one of the fastest growing programming languages. It’s tooling is evolving fast to catch up. I have been writing python for over 10 years now and sometimes it’s hard to keep up with all the new tooling out there. Recently, I had an opportunity (and time) to evaluate some of these new tools and I am impressed by the activity in this space. Here is my current (June 2020) ideal python project setup.


Dependency Management: pipenv

Dependency management in python is very hard and complex. In the past, I have used pip-tools with virtualenv to manage (very unsuccessfully) dependencies and env…

Most common reasons why biases get introduced in ML models

Whether you like it or not, the impact of machine learning on your life is growing very rapidly. Machine learning algorithms determine whether you would get the mortgage for your dream home, or if your resume would be shortlisted for your next job. It is also changing our workforce rapidly. Robots are taking over warehouses and factories, and self driving cars are threatening to disrupt the jobs of millions of professional drivers across the world. Even law enforcement agencies are increasingly using machine learning to screen for potential criminal leads and assess risks.

By Lenny Kuhne on Unsplash

Unfortunately, all these advancements in technology may…

Nitin Aggarwal

CTO/Co-Founder @ RunX. IITD CS. Previously Google, Lyft, Stripe. Interested in systems, dev productivity, ML.

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