Why Python is the Best Programming Language for Microservices?

Microservices is a service-oriented architecture pattern wherein applications are built as a collection of various smallest independent service units.

Python is a high-level programming language that offers active support for integration with various technologies. Python is commonly used for developing websites and software, task automation, data analysis, and data visualization. Since it's relatively easy to learn, Python has been adopted by many non-programmers such as accountants and scientists, for a variety of everyday tasks, like organizing finances. Prototyping in Python is faster and easier when compared to other frameworks and programming languages. It includes powerful substitutes for heavy implementations like Django. Microservices Python ensures compatibility with legacy languages like ASP and PHP, which allow you to create web service front-ends to host Microservices.

With all these benefits, Microservices Python is considered to have an edge over other languages. Developers who implement Microservices Python use a RESTful API approach – a comprehensive way of utilizing web protocols & software to remotely manipulate objects. With this technology, it becomes easier to monitor the application since it is now broken into components. There is a broad range of Python microservices frameworks to choose from for your web application development. Some of them are as follows:

Flask – Most popular Python Micro framework based on Jinja2 and Werkzeug
Falcom – Create smart proxies, cloud APIs, and app back-ends
Bottle – Simple, lightweight, and fast WSGI micro framework
Nameko – Best among the Python Microservices frameworks that allow developers to concentrate on application logic
CherryPy – Mature, Python object-oriented web framework

What is microservice architecture?

It is a software development approach that is used to disintegrate mobile applications into smaller parts. Microservice architecture is rapidly replacing monolithic architecture that is used in heavier, complex applications.

The basic focus of the microservice architecture is to develop cloud-ready apps and simplify the deployment process. The architecture has several built-in programming languages and also uses different data storage techniques.

Avoid the potholes

Thinking of migrating to the microservice architecture? If so, you should look at this presentation about the potholes in the road from monolithic hell and read this series of blog posts about anti-patterns and ways to avoid them.

Assess your architecture

If you have built an application with the microservice architecture then take a look at the Microservices Assessment Platform. The platform assesses what you have built and identifies what needs to be improved. It reduces architectural and organizational risk and maximizes the benefits of microservice architecture.

The process to choose programming languages for microservices

Organizations need to understand that microservices can be implemented with a plethora of frameworks and tools. Hence, it is necessary to employ the best practices while choosing a programming language for microservices. Here are some of the criteria that will help in evaluating the best programming language for microservices.

The language must be independent of deployment and must be highly observable.
It must have a customer-centric approach and according to the changing trends, must support automation.
The structure of the language should be around the business domain.
It must have decentralization of components and must support continuous integration.

Python Microservice Monitoring With Interceptors

Once you have some microservices in the cloud, you want to have visibility into how they're doing. Some things you want to monitor include:

How many requests each microservice is getting
How many requests result in an error, and what type of error they raise
The latency on each request
Exception logs so you can debug later

In conclusion, one of the best things with microservices is that you usually don't have to use the same programming language everywhere. When it comes to maintenance, it's obviously a mess if you have a dozen different programming languages and frameworks, but if you are starting from scratch, use something as simple as possible to get a minimalistic system running. You'll learn a lot more from playing with prototypes than from trying to figure everything out before you start implementing. By all means, make some Python prototypes and see where it leads you. Assuming you plan to run in docker and orchestrate with Kubernetes, you can e.g. use the python: 3.6-slim docker and minikube as a start.