Python

Build a Cup Once, Wash it a Thousand Times- Rust vs Python

Recently I became a voracious reader of David Graeber, and in a talk about BS jobs, he gave a great analogy, “you make a cup once, you wash it a thousand times”. This is the essence of the problem with Rust vs Python in 2025 and beyond. Rust is a sturdy cup that is easy to wash. Python is an easy cup to build, but very difficult to wash.

What is FaaS?

Function as a Service (FaaS): Core Building Block of Serverless Technology What is FaaS? Simplest unit of work for building applications, microservices, or event-driven protocols Basic workflow: Input → Logic → Output Characteristics of FaaS Simple and easily understandable Highly scalable Quick response time Popular FaaS Framework: AWS Lambda Can be attached to various services: S3 notifications (e.g., file uploads) SQS (Simple Queue Service) messages Enables building infinitely scalable services with small response times Best Languages for Serverless/FaaS Rust Go Advantages of Modern Compiled Languages for FaaS Speed Safety Optimal deployment characteristics Millisecond response and invocation times Low energy usage Key Considerations for FaaS Development Focus on maintenance over ease of building Optimize for low costs (financial and energy) Consider total cost of service over time Takeaway When developing Function as a Service applications, prioritize long-term efficiency, maintenance, and cost-effectiveness over initial development ease.

The Four Horseman of the Python S-Curve

An s-curve has a slow start, a rapid rise, then a plateau. With Python after years of success, you cannot have more success, and it had a good run. After 30 plus years, four key factors will cause a rift and slowly eat away at the peak of Python adoption. Where Python could be useful in 2030 is using only the Python standard library without packaging, and also in a hosted Jupyter environment for adhoc exploration.

livestream

52 Weeks of Cloud Podcast

Cloud Computing for Data Analysis

Abstract This book is designed to give you a comprehensive view of cloud computing including Big Data and Machine Learning. A variety of learning resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure) using Python. This is a project-based book with extensive hands-on assignments. TOC (Table of Contents) Book Chapter 1: Getting Started Effective Async Technical Discussions Effective Async Technical Project Management Cloud Onboarding Chapter 2: Cloud Computing Foundations

Solving The Cloud Skills Crisis

AWS Certified Cloud Practitioner 2020-Real World & Pragmatic

Become a Cloud DevOps Engineer

Command Line Automation in Python