Develop, deploy, and test micro-services using Chalice on Jupyter notebooks

The best of three worlds, Micro-service for system architecture, Chalice for DevOps, and Jupyter Notebook for IDE, is the most effective combination I know today. This post will go over a couple of examples of using the above triple to simplify the otherwise complicated flow of API development, including software development, system deployment, and functionality testing.

Why Micro-services?

Let’s start with the easy decision. Digital systems have become more and more complex and complicated in time. There are tons (if printed) of open source libraries to use, thousands of machine learning models to train or fine-tune, hundreds of cloud-based API and SaaS services to integrate. Today, every modern digital system uses many of the above resources while developing missing pieces to accomplish the functionality it is built to solve. The most popular system architecture today is to use REST APIs and micro-services design. The micro-services design breaks monolithic systems into smaller units of development, deployment, testing, and operation.

Why Chalice?

There are a few options for micro-services management that started with the launch of AWS Lambda in 2015. Since then, other cloud providers added their version with Azure Functions and GCP Cloud Functions, and the various framework matured with them. The main reason for the growing success of serverless services such as Lambda is their…