A practical guide for people who have heard the word “microservices” too many times and finally want to do something about it.
Most software systems don’t start as microservices. They start as a single application that does everything. User login, payments, emails, reports, admin screens, all tangled together like headphone wires in a pocket. That kind of system is called a monolith. It works fine until it doesn’t. Changes become risky, deployments feel like gambling, and one small bug can take down everything.
Microservices are not magic. They are simply smaller applications that each do one job and communicate with others over the network. The mistake beginners make is trying to convert the entire monolith at once. That is how projects quietly die. The correct move is boring and slow: extract one microservice first.
Step one: understand what you already have
Before touching code, you need to understand your monolith at a business level, not a technical one. Forget frameworks and folders for a moment. Ask a simple question: what does this system actually do for users?
Every monolith contains natural boundaries. User management, billing, notifications, inventory, reporting. These are not technical concepts, they are business capabilities. Your first microservice should represent one clear capability that can survive on its own.
Good candidates share three traits. They have clear inputs and outputs, they change frequently or cause pain when changed, and they do not control the entire database. Authentication, email notifications, and file processing are common first picks because they are easy to isolate and rarely need direct access to everything else.
Step two: define the responsibility, not the technology
A microservice is not “a Spring Boot app” or “a Node service.” That thinking leads to messes. A microservice is a responsibility with rules.
For example, instead of saying “I’ll create a User Service,” say “This service owns user creation, login, and password validation. No other part of the system is allowed to change users directly.” That sentence is more important than any code you will write.
Once responsibility is clear, define how other parts of the system will talk to it. For beginners, HTTP with JSON is the safest choice. One endpoint to create a user, one to fetch user data, one to validate credentials. Simple, boring, reliable.
Step three: copy logic first, then remove it
This part feels wrong but works.
Do not delete code from the monolith immediately. First, copy the relevant logic into a new, separate application. Give it its own repository, its own build process, and its own runtime. At this stage, both systems can do the same thing. That duplication is temporary and acceptable.
Once the new service works on its own, change the monolith so that instead of running the old code, it calls the new service over HTTP. It's called Strangler Fit Pattern. If the behavior stays the same, users never notice. That is the goal. Silence.
Only after this works reliably should you remove the old logic from the monolith. If something breaks, you know exactly where to look, which is a luxury in software.
Step four: separate the data carefully
Beginners often trip over databases. A true microservice owns its data. That means no other service should directly read or write its tables.
For your first microservice, you have two realistic options. The safest is giving it its own database, even if it feels redundant. The second is letting it access the existing database but only specific tables, with a clear plan to move them later. What you must not do is allow multiple services to casually share tables. That recreates the monolith, just with more networking bills.
Data duplication across services is normal. Synchronization is handled through APIs or events, not shared schemas.
Step five: deploy it independently
If your new service cannot be deployed without deploying the monolith, you have not created a microservice. You have created a distributed illusion.
Deploy the service separately, even if it runs on the same server at first. Use a different port, a different process, and a different release cycle. The first time you fix a bug in the microservice without touching the monolith, the whole exercise finally makes sense.
Monitoring and logging matter here. When things go wrong, and they will, you need to know which service failed and why. Centralized logs and basic health checks are enough for a first step. No need to summon Kubernetes gods yet.
Step six: repeat slowly, or stop
After your first success, resist the urge to extract everything. Microservices increase operational complexity. If the pain you removed is smaller than the pain you introduced, stop. One or two well-chosen services already deliver most of the benefit.
Microservices are a tool, not a moral upgrade.
Final thoughts
The hardest part of moving from a monolith to microservices is not coding. It is discipline. Clear boundaries, patience, and the willingness to accept temporary duplication are what make the transition survivable.
If you can extract one service cleanly, you can extract more. If you cannot extract one, extracting ten will not save you.
References
These are trustworthy, widely cited, and written by people who have broken real systems before fixing them.
Martin Fowler's Guide to Microservices: The "bible" of this topic. Fowler explains it clearly without the hype. martinfowler.com
Sam Newman's "Building Microservices" - This book is the gold standard. He coined many of the patterns used today.
AWS on Microservices - Practical, "how-to" guides from the people who host most of the world's services.
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