Introduction
Microservices have become the go-to approach for building modern software systems thanks to their promise of scalability, flexibility, and faster development. But behind the hype lies a critical truth: microservices can create more problems than they solve if not planned and sized correctly. Poorly designed microservices can lead to confusion, unnecessary complexity, and extra overhead, making your system harder to manage over time. The result? Long-term issues like skyrocketing costs, maintenance headaches, and a system that feels more like a tangled web than a streamlined solution.
In this blog, we’ll dive into the concept of right-sizing microservices and explore how integrators and disintegrators can help you design an architecture that is scalable, efficient, and sustainable. Whether you’re just starting with microservices or looking to improve an existing setup, this article will give you the insights you need to avoid common pitfalls and get it right from the start. Let’s build smarter, not harder!
Importance of Correct Sizing

Getting the size of your microservices right is essential because both extremes — too large or too small — can lead to significant problems. When microservices are too large, they resemble monoliths, undermining the benefits of adopting a microservices architecture. Large services are harder to scale independently, making them less efficient in handling varying workloads. They also create deployment bottlenecks, as even small changes might require redeploying the entire service. This can lead to slower development cycles, increased downtime, and the loss of flexibility that microservices are supposed to provide.
On the other hand, too small microservices can result in an overly fragmented and complex system. This often increases communication overhead between services, leading to higher latency, potential performance bottlenecks, and difficulties in management. Such fragmentation can also force teams to deal with complex distributed scenarios, such as managing distributed transactions across multiple services. These scenarios add significant development and operational overhead, as ensuring consistency and reliability becomes a non-trivial challenge. Striking the right balance is critical to avoid these pitfalls and ensure a system that is not only scalable but also maintainable and efficient.
Service Disintegrators

Breaking down a service into smaller pieces is a critical decision in microservices architecture, and it’s not one to take lightly. Service disintegration should be guided by clear principles and justified by the specific needs of your system.
In this section, we’ll explore six key drivers that help determine when and why you should split a service. These drivers provide a structured framework to evaluate the need for disintegration and ensure it aligns with your architecture’s scalability, maintainability, and performance goals. By understanding these factors, you can make informed decisions that balance flexibility and simplicity, avoiding the pitfalls of over-fragmentation.
Service Scope and Function
One of the most common reasons to break a service into smaller parts is its scope and functionality. A key aspect of this is evaluating the service’s cohesion — how well its responsibilities are related to each other. A highly cohesive service focuses on a single, well-defined purpose, making it easier to maintain and understand. On the other hand, low cohesion indicates that a service is handling unrelated tasks, which can lead to confusion and make updates or troubleshooting more difficult. Size also plays a crucial role in deciding whether a service should be split. If a service grows too large, it becomes harder to test, deploy, and scale effectively.
For example, consider a “User Management” service that handles user registration, authentication, profile updates, and permissions. These tasks are all related but serve distinct purposes. By analyzing cohesion, we can see that authentication (focused solely on verifying user identity) is separate in function from profile updates (which involve personal user details) or permissions (related to access controls). Splitting authentication into its own service ensures high cohesion and keeps the responsibilities clear.
Correctly sizing services in this way also helps manage their size. The “Authentication” service, for instance, can now be scaled independently to handle login spikes without affecting profile or permissions functionality. This approach ensures that services are focused, manageable, and aligned with the principles of a scalable microservices architecture.
Code Volatility
Another key factor in determining whether to break a service into smaller parts is code volatility — the rate at which the source code changes. Services or components with high volatility often need frequent updates to add features, fix bugs, or respond to business needs. Keeping these components as independent services can reduce risks and improve maintainability.
For instance, consider a “Reporting” service that generates standard reports but also includes a component for custom report generation. If the custom reporting logic changes frequently to meet new client demands, it would make sense to extract this into a separate service. This way, the volatile component can be updated and deployed independently without affecting the stable parts of the system.
The benefits of such separation are significant. Independently deployable services mean faster updates without impacting other functionalities. Testing efforts are more focused, as the scope is limited to the specific service. Moreover, the blast radius of a failure is reduced, ensuring that issues in one service (e.g., custom reports) do not disrupt the overall system. Managing code volatility through independent services leads to a more resilient and flexible architecture.
Scalability and Throughput
When a service experiences extreme variations in scalability requirements, separating its components can significantly improve efficiency. Different parts of a service may have varying demands on resources, and splitting them allows you to scale each component independently based on its specific needs.
For example, consider a “Notification” service that sends both SMS and Email notifications. Let’s assume that SMS notifications typically generate much higher traffic than emails, especially during peak usage periods, such as promotional campaigns or transactional alerts. By separating SMS and email functionalities into distinct services, you can scale the SMS service to handle the high traffic while keeping the email service infrastructure minimal and cost-effective.
This approach offers several advantages. Only the components with higher demand — like SMS — are scaled, reducing unnecessary infrastructure provisioning for the less-demanding email service. This targeted scaling not only ensures optimal performance but also minimizes costs, making your architecture more efficient. By managing scalability and throughput through service separation, you can maintain a responsive, reliable system without overburdening your infrastructure.
Fault Tolerance
Fault tolerance is a critical factor in ensuring the reliability of your system. It refers to the ability of an application or specific functionality to continue operating even when a fatal crash occurs. Separating services based on their fault tolerance requirements helps isolate failures, preventing them from cascading across the entire system.
For example, consider a “Food Delivery” platform that has a service for placing orders and another for real-time delivery tracking. If these are tightly coupled and the delivery tracking component fails (e.g., due to a third-party API outage or high traffic), it could potentially bring down the order placement functionality as well. By separating these into independent services, users can still place orders even if the delivery tracking service experiences issues.
This separation ensures that critical operations, like order placement, continue functioning despite failures in non-critical components. Isolating such failures helps maintain a partially operational system, reduces downtime for key features, and improves user experience by minimizing the impact of outages.
Security
Security is a crucial consideration when designing microservices. Components with higher security requirements can be separated into independent services to implement specialized security measures without impacting other parts of the system.
For instance, in an “E-Commerce” platform, payment processing demands stricter security protocols compared to general catalog browsing. By separating the payment service, you can deploy it independently with advanced security features such as encryption, tokenization, and stricter access controls. Meanwhile, the catalog browsing service can operate with standard security measures, optimizing performance while maintaining safety.
This separation ensures that sensitive operations are protected with the highest level of security without overburdening less critical components. It also simplifies compliance with regulatory standards like PCI DSS for payments, making the overall system more secure and manageable. By isolating high-security components, you can better safeguard user data and reduce potential vulnerabilities in your architecture.
Extensibility
Extensibility refers to the ability to add new functionality to a service as its context or business needs evolve. A well-structured microservice allows you to introduce new features or update existing ones without overhauling the entire system or causing disruptions.
For example, consider a “Payment” service that handles various payment methods such as credit cards, PayPal, and bank transfers. As the business grows, you might need to introduce additional payment options like cryptocurrency, mobile wallets, or buy-now-pay-later services. Instead of reworking the entire payment service, you can extend its functionality by creating separate components for each payment method. This allows you to add new payment options without impacting existing ones, keeping the service flexible and scalable.
By structuring the service this way, you avoid turning it into a large, monolithic component. New payment methods can be added with minimal disruption and without requiring frequent redeployments. Extensibility ensures that the system can grow as business needs change, keeping your architecture adaptable and efficient.
Service Integrators

While breaking services apart into smaller, more manageable pieces is often beneficial, there are cases where it makes more sense to integrate services rather than separate them. In this section, we will provide guidance and justification for when to keep services together, or when it might be better not to break a service apart in the first place. Sometimes, splitting a service too early can introduce unnecessary complexity or overhead, making it harder to scale, maintain, or even evolve over time.
We’ll explore four key aspects that help determine when service integration is the best approach, including factors such as operational complexity, communication overhead, data consistency, and future scalability.
Database Transactions
Database transactions are crucial for maintaining data integrity when multiple operations need to succeed or fail as a single unit of work. Keeping related functionalities within the same service can simplify this process, avoiding the complexity and challenges of distributed transactions when multiple services are involved.
For instance, consider a “User Registration” service that handles creating user accounts and assigning default permissions. If these functionalities are split into separate services — one for account creation and another for permission management — ensuring that permissions are assigned only when the account is successfully created would require a distributed transaction. Distributed transactions are notoriously complex to implement, requiring advanced coordination mechanisms and increasing the risk of failure.
By combining these functionalities into a single service, you can manage all database operations within a single transaction. This ensures that the user account and associated permissions are either both successfully created or rolled back together, maintaining data integrity and simplifying the overall system.
Workflow and Choreography
In microservices architectures, workflows often involve multiple services working together through interservice communication. While this enables flexibility and modularity, excessive communication can lead to performance bottlenecks, increased latency, and reduced fault tolerance.
For instance, in a “Food Delivery” application, the order service might need to communicate with the payment service, the restaurant service, and the delivery assignment service. If these services are too decoupled, placing an order might require several network calls, increasing the chances of delays or failures. For example, if the delivery assignment service experiences an outage, it could block the entire order workflow, preventing users from completing their transactions.
Consolidating services that are tightly coupled in their workflow — such as the order and delivery assignment services — can simplify communication, reduce latency, and improve fault tolerance. This approach ensures that the system remains responsive and reliable even under high workloads or partial failures.
Shared Code
Shared code in microservices, typically managed through shared libraries, is often seen as a way to streamline development and maintain consistency. However, it can introduce challenges when it comes to service sizing and independence. When a shared library is updated, all dependent services need to align with the changes, which can disrupt their deployment cycles and create dependencies that counteract the autonomy of microservices.
For example, imagine a “Customer Management” system where multiple services — such as a profile service, loyalty program service, and notification service — use a shared library for customer validation logic. If the library is updated to include new validation rules, all these services must integrate the update. If one service lags in updating, it can lead to inconsistencies in how customer data is validated across the system.
When designing services, it’s important to evaluate whether shared code aligns with the desired level of autonomy. For highly independent services with distinct lifecycles, duplicating certain logic or adopting service-specific libraries might be preferable to avoid unnecessary coupling and to maintain flexibility in deployment and scaling.
Data Relationships
In a microservices architecture, the practice of having each service manage its own database ensures independence but complicates data relationships. When related data is distributed across services, maintaining relationships can become challenging, leading to potential data integrity issues and increased interservice communication.
For example, consider a “Ride-Sharing” platform. Suppose there is a driver service managing driver profiles and a ride service managing trip data. If these services are too granular, storing driver details in one database and trip data in another, operations like generating a driver’s earnings report or assigning rides based on availability require constant communication between the two services. This adds unnecessary complexity and can lead to delays, especially under high traffic conditions.
In this scenario, consolidating the driver and ride data into a single service with a shared database might simplify the architecture. This approach would ensure tighter data consistency, reduce the need for interservice communication, and improve the overall system’s responsiveness, highlighting the importance of appropriately sizing services based on data relationships.
Finding the Right Balance

Determining the optimal size for a service is a balancing act that requires analyzing trade-offs between breaking services apart and consolidating them. While smaller services offer benefits like scalability and independence, they can introduce complexity through distributed communication and management. Conversely, larger services simplify workflows and data relationships but may sacrifice flexibility and autonomy.
To find the right balance, it’s crucial to collaborate closely with business stakeholders. Understanding business priorities, such as the need for agility, fault tolerance, or cost optimization, helps inform decisions on service sizing. The goal is to align technical architecture with business objectives while ensuring the system remains scalable, reliable, and manageable over the long term.
Conclusion
In conclusion, the journey to right-sizing microservices is a nuanced process that involves carefully balancing disintegration and integration factors. While disintegrating services can provide advantages such as flexibility, scalability, and fault tolerance, it also introduces challenges like increased communication complexity and potential data integrity issues. On the other hand, integrating services offers simplicity but can reduce the system’s agility and create dependencies that hinder scaling.
Analyzing the trade-offs between disintegration drivers and integration drivers is the secret to getting service granularity right. By collaborating closely with business stakeholders, understanding their priorities, and evaluating the specific needs of each service, you can strike the right balance that ensures a scalable, maintainable, and cost-effective architecture. With the right approach, microservices can provide the benefits they promise without the complexities that come from poor sizing decisions.