In a recently posted article on DZone, “Microservices: Good for Developers’ Mental Health,” Sauce Labs engineer, Simone Pezzano, addresses the link between developer confidence and mental health in today’s new workplace. Pezzano tells the story of his team’s bumpy start on their journey from monolith to microservices. Initially, Pezzano viewed microservices as a scary concept with rapid release cycles and shorter testing times.

Traditionally, monolithic architecture has been used to develop large-scale apps. However, people have realized its drawbacks and limitations over time. Without adapting to modern agile practices and limited flexibility does not allow for a productive development process. Therefore, organizations have been searching for better, more reliable architecture to facilitate the development of large-scale, complex apps with a more productive workflow.

Microservices have an entirely new set of problems due to their distributed service-oriented architecture. As a result, microservice design patterns have surfaced. This post will consider the specific design patterns that can help us build reliable, secure and traceable microservices.

As more companies invest in a cloud native infrastructure, they’re choosing to prioritize their applications as microservices—architecting them into distinct servers. Each component is responsible for one (and only one) feature. For example, you might have Server A responsible for handling billing logic, Server B for handling user interaction and Server C for handling third-party user interactions.

If you’re a dev you’ve no doubt, come across people talking about monolith and microservice application architecture. Perhaps you are involved in designing a new system and have been asked to consider both architectures. The conversations are often regarding how microservices are the successor to monolith architecture, but today I’m going to try and layout why it’s not as simple as one being better than the other.

Service Mesh is an infrastructure layer that has become a common architectural pattern for intra-service transparent communication. By combining Kubernetes a container orchestration framework, you can form a powerful platform for your microservices cluster, addressing the typical technical requirements that occur in highly distributed environments. A service mesh is implemented through a sidecar configuration, or proxy instance, for each service instance.

Microservices have gained a lot of traction in the last few years. Ever since the dawn of time, monolithism – packaging all your modules into one colossal codebase – was the default way to go when building software applications. However, as applications have had to cater to increasing volumes (of millions) of users over the internet over the last decade, scalability and flexibility have become ever more critical.

Many companies have embarked on microservices software projects in an effort to make modernize their suite of technology systems and reap the benefits that can come from deploying such an architecture. In the microservices model, applications are divided into a series of interconnected services based on operational capabilities. Each service supports a distinct set of functionality, effectively acting as a mini-application with its own operational logic, adapters, and even database schema.

Microservices are a popular and modern organizational software engineering practice. The guiding principle of any microservices implementation is to develop an application by dividing its business components into smaller services that can be deployed and operated independently of each other. The separation of concerns between services is defined as “service boundaries.”

In this three-part blog series, we examine the critical role Kubernetes plays in shaping the future of infrastructure, including the rise of containers and Kubernetes. The first in the series covers Next-Generation Application Development. The second covers the Next Frontier: Container Orchestration. And the third covers How Kubernetes Gets Work Done.