The Rise of Microservices

Large companies, especially those running massive online services, were looking for better ways to handle growth and reliability. Thankfully, many early adopters of microservices began sharing their experiences and lessons learned.

At first, most of these companies used monolithic applications—large systems where all parts of the software were tightly connected. This worked well in the beginning and often helped them grow fast from a business point of view.

However, as these systems became bigger, they also became harder to maintain, update, and scale. Even the most powerful servers could not keep up with the demand. This limitation, known as vertical scaling, means trying to make a single machine stronger and faster, which has limits.

To solve this, developers started to split their applications into smaller, independent parts. Each part could be deployed, updated, and scaled on its own. This new method is called horizontal scaling, where you run several smaller copies of a service on different servers. A load balancer then distributes user requests among them.

In the cloud, this scaling can seem almost unlimited—you can add more virtual servers whenever you need, as long as your software is designed to handle many copies.

During that time, several open-source tools appeared, making microservices easier to build and manage. Let’s look at some key examples:

Spring Cloud simplified complex features like service discovery, configuration management, and monitoring, helping developers build distributed systems faster.
Docker introduced containers, allowing developers to package applications with all their dependencies. This made it much easier to run the same software on any computer—from a developer’s laptop to a cloud server.
But running containers manually isn’t enough for production. You also need systems that make sure containers stay online, restart when they fail, and scale when needed.
This led to the creation of container orchestrators such as Apache Mesos, Docker Swarm, Amazon ECS, HashiCorp Nomad, and especially Kubernetes. Kubernetes, created by Google and released in 2015, quickly became the standard. It was later donated to the Cloud Native Computing Foundation (CNCF). Today, almost every cloud provider supports it.
A few years later, a new idea called a service mesh appeared. A service mesh adds extra tools that help microservices communicate securely and reliably. It works together with an orchestrator like Kubernetes, reducing the amount of code developers need to manage network concerns such as retries, security, and load balancing.

What Exactly Is a Microservice?

A microservice architecture breaks a large application into a set of smaller, independent services. This design has two main benefits:

Faster development and deployment – each service can be updated or released separately.
Easier scaling – you can adjust only the parts of the system that need more resources.

A microservice is an independent software unit that can be updated, replaced, or scaled without affecting others. To achieve this autonomy, each microservice must follow some basic principles:

No shared data: Microservices should not access the same database tables. Each one manages its own data.
Clear communication: They communicate through well-defined APIs or messages, often asynchronously. APIs must be stable, documented, and versioned carefully.
Separate runtime: Each microservice runs as its own process, often inside a Docker container.
Stateless design: Requests should not depend on any saved session data. This allows any instance of the service to handle any request.

These features make it possible to deploy each microservice on different servers rather than running everything on one big machine. When demand increases, you can simply add more instances of a single service instead of scaling the whole system. Cloud platforms can even scale services automatically, which is hard to do with a traditional monolithic app.

How Small Should a Microservice Be?

There’s no strict rule, but here are two simple guidelines:

A microservice should be small enough for one developer to fully understand.
But it should also be large enough to perform a clear business function efficiently, without creating too many communication delays or data inconsistencies.

For example, in an online bookstore:

One microservice might handle user accounts.
Another one could manage book inventory.
A third could process orders and payments.

Each service focuses on one main responsibility and communicates with others through APIs or messages.

Wrapping Up: Why Microservices Matter

In short, microservice architecture is a way of designing software by dividing a big system into smaller, independent parts. The goal is to make development faster, deployment easier, and scaling smoother.

By following these principles, teams can build systems that are more flexible, reliable, and ready to grow.