How to build a scalable microservice architecture?

The speed, reliability and functionality requirements of modern applications exceed the standards of traditional system design. Microservices are becoming the foundation of modern applications, enabling flexible, error-proof and easy-to-develop technology environments. This often raises questions about how to design such an architecture that is highly scalable, stable and future-proof. This publication will help you learn the techniques, principles and tools that will enable you to build a complex microservices architecture. If you are interested, here you will find everything you need to know about this solution.

What is the microservice architecture?

Microservice architecture is a style of designing IT systems in which an application is divided into smaller, independent components called microservices. Each microservice is responsible for one specific business function and can be developed, implemented, and scaled independently of other parts of the system. Unlike traditional monoliths, microservices allow for greater flexibility, faster development, and easier maintenance of applications over time.

Feature	Monolith	Microservices
Scalability	Difficult, must scale the entire app	Easy, scale only required services
Team Development	Shared codebase, hard to collaborate	Independent development by multiple teams
Deployment	Single large application	Independent deployments per service
Error Handling	One failure can break everything	Failures are isolated within a single service

Advantages of microservice architecture

Service Scalability

One of the greatest advantages of microservice architecture is the ability to scale microservices independently. This means that instead of scaling the entire application, we can increase computing power only where the load is actually high - for example, in a microservice responsible for payments or logins. This approach improves overall system performance and optimizes resource utilization. Combined with techniques such as horizontal scaling and auto-scaling, this allows for stability even during peak traffic.

Technological Flexibility

With microservices, each team can choose the most appropriate programming language, framework, and database for a specific context. This allows them to create independent services that can leverage the latest solutions without impacting other components. This is a significant advantage over monolithic architecture, where a single technological decision impacts the entire project.

Independent Service Deployment

Microservice architecture allows for deploying services. This meaning that new features or fixes can be implemented for just one microservice - without the need to restart or interfere with other services. This, in turn, significantly reduces the risk of production errors and speeds up change implementation time. In an environment based on CI/CD pipelines, this capability is invaluable.

Fault Tolerance

In the event of a failure of one microservice - for example, the one responsible for payment processing - the rest of the system can continue to operate uninterrupted. This is because each service instance operates independently, and the system is distributed. Furthermore, patterns such as circuit breakers and tools for service discovery and load balancing enable rapid traffic switching to available service instances and maintain system stability.

scaling microservices

Better Data Management

Because each microservice can have its own database, the problems associated with a single central database and shared schemas are eliminated. This approach promotes clear data ownership, precisely defined within service boundaries, and supports data consistency within a service. In complex systems where multiple services must collaborate, this approach enables scalable and flexible data management.

Optimized Communication Between Services

Microservices communicate using well-defined APIs, promoting loose coupling and architectural transparency. Depending on your needs, you can use both asynchronous communication patterns (e.g., Kafka, RabbitMQ) and synchronous inter-service communication (e.g., REST, gRPC). Separating communication into asynchronous and synchronous enables the design of high-performance and resilient systems, especially when the system must handle multiple requests from different sources.

Better Team Organization

Microservices can be designed according to business capabilities principles - each service is responsible for specific business logic, allowing it to be assigned to a single team. This allows teams to develop features independently, without conflicts stemming from a shared code base.

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When is it worth scaling microservices?

Multiple microservices are best suited for situations where the application is complex and requires high flexibility and scalability. Here are specific scenarios:

Large web applications with multiple functions, such as banking systems, streaming services, e-commerce applications, or social networking sites. In such projects, a single application can span multiple services - for example, separate microservices for shopping cart management, payments, product recommendations, and user login. Separating these functions allows for high performance and precise data and traffic management.
High-traffic systems requiring dynamic scaling of microservices - e.g., food ordering applications, cryptocurrency exchanges, or reservation systems. In such cases, microservices work with load balancing and auto-scaling mechanisms to maintain optimal performance even with thousands of simultaneous users.
Projects with large development teams, where many people work on different services simultaneously. Microservice architecture allows for clear division of code into separate services, minimizing conflicts and facilitating continuous integration. Each team can develop and test a service without impacting other parts of the system.
Scaling and deployment flexibility are essential, especially in cloud-based environments. Microservices enable independent deployment, providing vast opportunities for experimentation, A/B testing, and responding to changing market needs. Combined with continuous deployment, we gain rapid response times and complete control over product development.

Limitations of the monolith

Traditional monolithic architecture works well for simple applications, but quickly becomes problematic as the system grows. Increasing functionality means increasing dependencies and code that is difficult to understand, maintain, and develop.

Each change can require compiling, testing, and deploying the entire system, even if it concerns just a single function. This significantly increases the time it takes to implement new features and increases the risk of errors.

Over time, a phenomenon called "monolithic hell" emerges, where the business logic of different modules begins to become intertwined, the lines of responsibility blur, and attempts to separate code lead to even greater chaos.

Service boundaries are also lacking, preventing the implementation of strategies such as service discovery, asynchronous communication, and distributed tracing, which are standard in modern microservice architectures.

Does your company need microservices?

Microservices aren't a solution for everyone – implementing them involves additional costs, complexity, and demands on the team and infrastructure.

Consider a microservice architecture only if:

the application has extensive logic and you plan to develop it further,
the development team is large enough to maintain multiple microservices,
you anticipate rapid user growth or heavy network traffic,
you prioritize high availability, fault tolerance, and resource utilization.

However, if:

you're creating a simple MVP application,
the team consists of several people,
you don't anticipate the need for dynamic scaling,

then it's worth starting with a monolith. Monolithic is easier to implement and cheaper to maintain, and if necessary, you can transition to microservices over time - slicing the system gradually, according to your business domain and actual needs.

service oriented architecture

Key Principles for Designing a Microservice Architecture

Service Independence and Autonomy

The fundamental principle of any well-designed microservice architecture is component autonomy. Each microservice should be created as a unit:

that can deploy services independently - without impacting other modules,
that has its own, clearly defined business logic,
that manages its data independently, preferably through its own database.

Such autonomous services promote system scalability and resilience, and thanks to well-defined service boundaries, it is possible to precisely map microservices to the actual business domain. The result is a flexible and highly scalable system that can evolve without the risk of destabilizing the entire application.

Bounded Context

The concept of context boundaries comes from the Domain-Driven Design (DDD) methodology and is crucial when designing microservices. Defining which data and functionality should belong to one service and which to another helps avoid situations where data or logic are haphazardly shared.

These boundaries not only support loose coupling between services but also ensure data ownership and improve data consistency within a single microservice. Clear contexts make it easier to maintain code, make changes, and manage distributed transactions when services need to interact.

APIs and Service Communication

Inter-service communication is the heart of every microservice architecture. Well-designed interfaces ensure system clarity, resilience, and performance. The most commonly used approaches:

REST API - ideal for simple HTTP requests, well-known and widely supported.
gRPC - more efficient than REST, used for communication between services requiring high throughput and low latency.
Asynchronous messaging - for example, using Kafka, RabbitMQ, or NATS. This allows for the construction of event-driven architectures in which communication occurs in the background and does not block service operation.

The use of asynchronous communication patterns reduces errors and improves fault tolerance, as microservices can operate independently even when other service instances are temporarily unavailable. Combined with service discovery and load balancing tools, this ensures optimal performance even in highly complex environments.

Choosing the Right Technology and Tools

Programming Languages

One of the advantages of microservices is that you can use different technologies in different components. Depending on your team's needs and competencies, you can choose:

Java (Spring Boot) – reliable, with a large enterprise ecosystem.
Node.js (Express, NestJS) – ideal for rapid API and backend service development.
Go (Golang) – a great choice for high-performance services.
Python (FastAPI, Django) – simple and fast deployment.

This allows you to build multiple microservices optimized for different needs and not be limited to a single technology stack.

Databases and Data Storage

A good practice in microservice architecture is to assign a dedicated database to each service. This ensures:

better isolation,
ensure data consistency within the service,
avoidance of so-called "cloud bloat." "shared database antipattern."

Sample approaches:

PostgreSQL / MySQL – for traditional relational data.
MongoDB / Cassandra – for high volatility and scalability.
Redis – for storing frequently accessed data, sessions, and caching.

This approach simplifies data management, enables transaction management within a service, and improves system health.

Containerization Tools

To fully utilize the potential of microservices, it's worth using modern deployment and management tools:

Docker – a standard for application containerization, enabling easy launching of multiple instances of each service.
Kubernetes (K8s) – a container orchestration platform that supports automatic scaling, disaster recovery, and service mesh.
Helm – a Kubernetes configuration management tool that accelerates microservice deployment and supports complex deployment strategies.

Combined with monitoring and CICD pipelines, these tools provide the foundation for building modern, complex microservice architectures.

microservice architecture

Communication Between Microservices

Synchronous vs. Asynchronous Communication

In modern microservices architecture, effective communication between services is absolutely crucial. It can be achieved in two main ways:

Synchronous communication – for example, using a REST API: one service directly calls another service and waits for its response. This model is simple, but can lead to overload, especially in the case of multiple requests.
Asynchronous communication – involves sending messages using queuing systems (e.g., Kafka, RabbitMQ). Service A sends a message, which is later received by service B. This makes the services less dependent on each other (loose coupling) and more resilient to failures.

Advantages:

higher fault tolerance,
better resource utilization,
the ability to scale without blocking services (scaling microservices effectively),
more flexible inter-service communication.

In the case of complex systems, asynchronous communication patterns are used, such as publish/subscribe or event sourcing, which support event-driven architectures and allow the system to dynamically respond to events.

REST, gRPC, GraphQL

The choice of communication protocol depends on the business and technical requirements of a given microservice:

REST – a classic solution based on HTTP and JSON. It works well when communication is simple and does not require high performance.
gRPC – a binary protocol based on HTTP/2, ideal for internal communication between multiple services where low response time and high throughput are required.
GraphQL – allows clients to retrieve exactly the data they need. It is suitable for applications with complex user interfaces, where optimizing data volume is crucial.

Message Brokers: RabbitMQ and Kafka

RabbitMQ – an AMQP-based queuing system, ideal for simple scenarios requiring queues with acknowledgement of receipt. It facilitates asynchronous messaging between microservices and can be used in conjunction with retry and fallback mechanisms.

Apache Kafka – the best choice for large, scalable data streams. It enables reliable data transfer between different services, supports distributed tracing, and event history storage. It is ideal for environments with large data volumes and high bandwidth requirements.

Authentication and Authorization

OAuth 2.0 and OpenID Connect

In a microservice environment, consistent and centralized access control is essential. Therefore, the following standards are recommended:

OAuth 2.0 – for managing access to resources,
OpenID Connect – for user authentication and creating secure sessions.

With the help of tools such as Keycloak, Auth0, or AWS Cognito, it is possible to easily implement Single Sign-On (SSO) and security delegation between services.

Security Delegation in Service Architecture

The use of JWT tokens allows for secure transfer of user data between services without the need for each verification with a central system. This increases speed and reduces network traffic while maintaining security.

Scalability and Load Balancing

Load Balancer and Service Mesh

For systems based on multiple microservices, traffic management and load balancing are essential:

Load balancer (e.g., NGINX, HAProxy) – distributes traffic between service instances, avoiding overloading a single point and ensuring optimal performance.

Service mesh (e.g., Istio, Linkerd) – an extension that offers intelligent routing, retry, monitoring, distributed tracing, encryption (mTLS), and service discovery. It allows for dynamic and programmable traffic management between services.

With a service mesh, you can control which backend services respond to specific requests and how to respond in the event of overload or failure.

Horizontal vs. Vertical Scaling

Horizontal scaling involves adding new instances of the same microservice. This is the preferred method for scaling microservices, especially in cloud environments, as it provides greater flexibility and resilience to overloads.

Vertical scaling – increasing the resources (CPU, RAM) of a single instance. While it can be useful when infrastructure constraints exist, it has its limits and is not suitable for highly loaded systems.

Stateless vs. Stateful Services

In microservice architecture, we distinguish between two types of services:

Stateless services – they do not store data between requests. Ideal for horizontal scaling, as each service instance can handle any user request without having to track their session. This facilitates load balancing and the seamless deployment of multiple microservices.

Stateful services – they maintain a session or information about the user's state. Examples include shopping carts or applications requiring authorization. Their implementation requires the use of sticky sessions, external state stores, or session caching.

It is good practice to design services as stateless whenever possible – this significantly improves the scalability and resilience of the system.

scalable architecture

State Storage: Databases and Caches

To ensure data consistency and improve data management, the following are recommended:

Databases (PostgreSQL, MongoDB) – for storing user data and critical information.

Redis / Memcached – for storing frequently accessed data, sessions, and temporary data.

Each separate service should have database, which ensures data isolation, avoids locking errors, and supports transaction management within a single entity.

Monitoring and Logging

Prometheus – collects metrics from services and systems, enabling performance analysis.

Grafana – presents data from Prometheus in the form of easy-to-read dashboards and charts.

ELK Stack (Elasticsearch, Logstash, Kibana) – enables central logging, error analysis, and anomaly detection.

Regular monitoring directly impacts system health, allows you to identify potential threats, and optimize resource consumption.

CI/CD in Microservices

Pipelines for Multiple Services

Instead of a single, powerful deployment process, microservices use separate CI/CD pipelines for each service. This allows you to:

develop, test, and deploy services independently,
increase teamwork speed,
reduce deployment errors in other services.

Tools worth considering:

GitLab CI/CD
GitHub Actions
Argo CD – especially in Kubernetes environments.

DevOps and Containerization

Docker – a containerization standard that allows services to be launched in isolated environments.

Kubernetes – automates the deployment, scaling, and management of multiple services. It supports auto-scaling, self-healing, and service restarts in the event of failures.

Helm and Configuration Management

Helm charts enable fast and consistent deployment of microservices in a K8s environment. They facilitate updates, rollouts, and the creation of test and production environments. All this ensures stable and flexible management of even the most complex microservice architectures.

Database Scalability in Microservice Architectures

Each microservice should have its own database – this is the foundation for separation of responsibilities and system resilience. Data separation prevents errors and conflicts, enabling more effective data consistency and transaction management.

CQRS and Event Sourcing

CQRS (Command Query Responsibility Segregation) – separates read and write logic, improving performance and scalability.

Event Sourcing – every change in the system is recorded as an event. Particularly useful in environments with high audit and change history requirements, e.g. fintech.

Build the Future with Microservices

Implementing a microservice architecture is not just a trend, but a response to the real needs of modern systems – flexibility, error tolerance, easier management, and the ability to independently develop individual components.

As we've shown in this guide, an effective approach requires knowledge of best practices, the careful selection of technologies, and experience in areas such as inter-service communication, load balancing, distributed tracing, CI/CD pipelines, and data consistency.

If you're wondering how to take your project to the next level, Railwaymen is a technology partner who can help you design and implement comprehensive, scalable microservice-based solutions. Our team specializes in developing dedicated backend systems, distributed architecture, and cloud deployments using tools such as Docker, Kubernetes, Kafka, and GraphQL.

Let's talk with us about Microservices Architecture

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