15 Best Practices for Building a Microservices Architecture

Microservices are an evolved architectural pattern that involves the design and development of an application as a collection of small, autonomous, loosely coupled services that communicate with each other.

At its elemental level, each individual microservice acts as an application in itself. Structuring applications as a collection of microservices encourages:

That makes managing and maintaining the application as a whole a lot easier.

microservice architecture

A typical microservices framework

These advantages give credence to the wider adoption of microservices by DevOps organizations both large and small. It’s a safe bet that microservices adoption will continue to rise thanks to these advantages—but to maximize the benefit, it’s crucial that you embrace best practices for running resilient distributed systems.

Here are 15 best practices that are fundamental to microservice success. Let’s take a look!

Best practices for microservices architecture

In this article, I group those best practices into categories that reflect the progression of various software development lifecycle (SDLC) phases, starting from the time you begin considering microservices for your next project, to the end of application deployment.

The tips also contain practices specific to new adopters, so you can transition successfully from a monolithic to a microservice framework.

For planning & organizing…

When designing the microservice…

When developing the microservice…

For data storage & management…

service mesh

Service mesh-enabled microservices

For deploying & hosting…

For maintenance & operations…

Microservice architecture transition

Microservices help manage applications better, but the transition to a microservices architecture is complex. The approach of implementing microservices may differ for different use-cases—but these fundamental best practices are universal.

As always, the goal for all microservices is to achieve a framework that is loosely coupled, distributed, and independent while constituting a DevOps model that enables automation and efficiency.

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