Every developer strives to make the product development process faster while maintaining flexibility and effective control. Microservices architecture makes this possible, and over the past 7–10 years, it has become a strong alternative to the traditional monolithic approach. Let’s begin by exploring the difference between the two.
The difference between these two approaches to software development is best illustrated with an example. Suppose we have two online stores: one built as a monolith, the other using microservices.
A monolithic online store is a single, indivisible structure that combines all components: databases (product catalog, customer data), cart, order and payment forms. All elements are tightly coupled and reside on the same server.
In a microservices-based system, each component is an independent module that developers can work on separately. Of course, these modules don't have to be hosted on the same server.
Thus, microservices architecture is like a modular building kit where you can easily add new components and scale the application. A monolith, in contrast, is like a solid wall — and scaling it typically means duplicating the entire structure.
It’s also worth noting that microservices are sometimes mistakenly thought of as just a collection of tiny services. That’s not true. For example, the database of a large e-commerce site may contain millions of records and take up tens of gigabytes, yet still be just one module within a microservices-based application.
Let’s compare how microservices and monoliths address the same development needs.
Microservices allow for faster development and more frequent releases thanks to their modularity — updates affect individual modules rather than the whole codebase. With a monolith, you must update the entire platform, which increases testing time and delays releases.
Microservices offer much greater flexibility: each service can use its own programming language, libraries, and data storage technologies. With a monolith, the technology stack is fixed and hard to change, forcing developers to stick with the original tools.
Since each microservice is a standalone unit, developers can be onboarded to specific modules without needing to understand the entire system. In a monolith, new developers must familiarize themselves with the entire application codebase before contributing effectively, making the team more dependent on specific individuals.
The modularity of microservices simplifies optimization, as each module can be tuned separately. In monoliths, optimization is more complex due to tight coupling — changes in one part often affect the entire system.
Microservices, being distributed and potentially deployed on separate servers, make it easier and faster to scale specific components. In monoliths, scaling one part usually means scaling the entire application, which is inefficient.
Thanks to their distributed and modular nature, microservices offer higher fault tolerance. A failure in one module does not affect the whole system. In a monolith, components are tightly connected, and a failure in one part can bring down the entire application.
Microservices clearly offer several advantages. But does that mean monoliths are outdated and should be replaced immediately? Not necessarily — it depends on your current project status.
In fact, switching to microservices isn't always the best move. Distributed systems also come with their own challenges:
Considering all these factors, the switch to microservices should be well-timed. In most early-stage projects, especially those with limited teams or budgets, there's no urgent need to move away from a monolith.
You should consider transitioning to microservices when:
If your project meets even one of these criteria, it's worth exploring microservices. But if your app is relatively small and doesn’t need frequent updates, it might be best to stick with the monolithic approach for now.
Modern development requires a containerization platform. In most cases, developers use Docker to isolate applications from infrastructure, enabling them to run seamlessly both locally and in the cloud.
As the number of containers grows, you need an orchestrator to manage them. The most popular tool is Kubernetes, which integrates well with Docker. Docker also has its own orchestrator: Docker Swarm.
Another essential tool is a load balancer, which evenly distributes network traffic across cloud resources, significantly improving the application's fault tolerance.