Microservices have become the go-to approach for building modern software systems because of 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. Badly designed microservices will lead to confusion, unnecessary complexity, extra overheads, which in turn make your system harder to manage over time. The result? Such are long-term problems: sky-rocketing costs, maintenance headaches, and a system that feels more like a tangled web rather than a streamlined solution.
In this blog, we look into rightsizing microservices and how integrators and disintegrators will be able to help you create an architecture that is not only scalable and efficient but also sustainable. Whether starting off with microservices or improving an existing setup, this article gives you insights on how to avoid common pitfalls and get it right the first time. Let’s build smarter, not harder!
It pays to get the size of your microservices right, since either extreme can cause serious problems: a service that is too large or too small. When services are too big, they start to resemble monoliths, defeating many of the reasons for moving to a microservices architecture. Large services are harder to scale independently, making them less efficient in handling varying workloads. They cause deployment bottlenecks, too-as even the tiniest change may involve redeployment of the whole service. This will imply slower development cycles, more downtime, and loss of that very flexibility microservices are supposed to confer.
On the other hand, too small microservices result in a system that is overly fragmented and complex. This often increases the communication overhead between services, introducing latency, possible performance bottlenecks, and difficulties in management. It could also force teams to deal with complex distributed scenarios, such as managing distributed transactions across many services. These scenarios result in significant overhead for development and operations; guaranteeing consistency and reliability will not be trivial. The balance is important to avoid these pitfalls in order to ensure a system that is not only scalable but also maintainable and efficient.
Breaking down a service into pieces is a crucial decision in microservices architecture; it’s not a decision to be taken lightly. Service disintegration should be guided by clear principles and justified by the concrete needs of your system.
In this section, we’ll discuss six key drivers that will help in determining when and why you need to split a service. The following drivers would set a systematic frame in which disintegration could be done to identify if it serves scalability, maintainability, and performance goals of the architecture. With knowledge of these factors, one will be informed while making a trade-off decision on flexibility and simplicity in order to avoid over-fragmentation pitfalls.
Probably the most common reasons for breaking down a service into smaller pieces are scope and functionality. To this end, central is consideration of the cohesion of the service-how well its various responsibilities are related to one another. A service with high cohesion is related to one single, well-defined purpose, because it makes maintenance easier and the service more understandable. On the other hand, low cohesion suggests that a service is doing unrelated tasks-a factor that contributes to chaos and confusion, making updates or troubleshooting quite difficult. Size is another important factor in making decisions to split a service. While a service continues to grow, testing its deployability and scaling becomes more difficult.
For example, let’s consider a “User Management” service, which is concerned with user registration, authentication, profile updates, and permissions. While these activities are related to each other, they also have distinct purposes. Looking from the perspective of cohesion, we can find that authentication is narrower-it just has to do with the identity of users-whereas profile updates include personal information about the users, and permissions involve the controls on access. So, splitting authentication into its own service keeps the responsibilities clear and cohesion high.
Sizing services in this manner would also allow them to keep under control their size. For example, the “Authentication” service, in this case, can now be independently scaled for any spikes in login without affecting profile or permissions functionality. That way, services would remain focused, manageable, and conformed to principles of scalable microservices architecture.
Another key determinant may be the aspect of code volatility, that is, the frequency or rate at which the source codes are changed. Many services or components facing high volatility require frequent updates on account of new feature additions, bug fixing, and responding to certain business needs. Maintaining them as separate services ensures minimum risk while providing more maintainability.
Consider a service like “Reporting” that would normally produce standard reports but also contains a piece responsible for custom reports. If, for example, the logic of custom reporting often changes due to new requirements by clients, then it will be reasonable to extract it into a separate service. In such a case, it is possible to update the volatile component and independently deploy it without disturbing the stable parts of the system.
The advantages of such separation aren’t small. Independently deployable services mean faster updates without affecting other functionalities. Testing efforts are also confined since the scope is constrained to the particular service. Moreover, the blast radius of a failure can be contained, ensuring that issues in one service cannot bring down the whole system. Controlling code volatility with independent services leads to resilient and flexible architecture.
This separation would greatly help any service that sees extreme highs and lows in terms of scalability. Some services can easily require more resources from one part versus another, so the ability to scale different components independently is crucial.
Consider, for example, a “Notification” service that sends both SMS and Email notifications. Typically, the volume of SMS notifications is very high for services at peak usage, such as promotional campaigns or transactional alerts. You can scale the SMS service to cater to the high traffic by separating SMS and email functionalities into different services while keeping the infrastructure of the email service minimal and cost-effective.
This provides a number of advantages. First, only those components with greater demand, like SMS, need to scale; therefore, unnecessary infrastructure provisioning for the less demanding email service is avoided. Scaling in this manner provides a great performance but also keeps costs down by making your architecture leaner. You will have a responsive, reliable system that does not overload your infrastructure because you managed scalability and throughput by separating services.
Fault tolerance is a critical factor in your system’s reliability, ensuring that an application or some kind of functionality can keep working while a fatal crash occurs. The separation of services according to their fault tolerance requirements facilitates the failover of any failures, which cannot cascade through the whole system in turn.
For example, consider a “Food Delivery” platform that has one service responsible for placing orders and another one for real-time delivery tracking. If these are tightly coupled, and the latter fails-say, because a third-party API is down or just experiencing very high traffic-it might take the former order placement functionality down with it. If they are split into independent services, even when the delivery tracking service goes down, users can still place orders.
It also separates the failure of non-critical components from critical operations, such as placing orders. Such isolation of failures allows the system to remain partially operational, reduces downtime for key features, and enhances user experience by minimizing the impact of outages.
Security is another important aspect when it comes to designing microservices. Components with higher security requirements can be separated into independent services, thus implementing special security measures without affecting other parts of the system.
For instance, within an “E-Commerce” system, payment processing requires higher security access than simple catalog browsing. You can deploy the payment service independently with higher security features such as encryption, tokenization, and more stringent access control, while the catalog browsing service can be deployed with standard security for better performance in safety.
The idea is to segregate sensitive operations with the highest security without overburdening the less critical parts. This would make it easier, for example, to follow other regulatory standards like PCI DSS on the overall system to make it highly secure and manage it more effectively. By isolating high-security components, further protection of user data can be attained and vulnerabilities within the architecture minimized.
Extensibility is about the ability of a service to add new functionality as its context or business needs evolve. A well-structured microservice allows for the introduction of new features or updating existing ones without overhauling the entire system or causing disruptions.
For instance, consider a “Payment” service that covers various payment methods such as credit cards, PayPal, and bank transfers. The new payment options to be introduced while the business grows are cryptocurrency, mobile wallets, or buy-now-pay-later services. You can extend its functionality without rewriting the whole payment service by composing separate components for every payment method. You will have the advantage of adding a new payment option without affecting existing ones, hence the service will be flexible and scalable.
You can also set up the service this way so that it will not be one huge, monolithic component. This is so that adding new methods of payments causes minimal disruption and without constant re-deployments. Extensibility ensures that the system can grow as business needs change, keeping your architecture adaptable and efficient.
While it is often good to break services into smaller, more manageable pieces, there are certainly times when integrating services makes far more sense than separating them. In this section we’ll give guidance and justification on when services should be kept together, or when it may not make as much sense to break a service apart in the first place. Sometimes, this splits a service too early and unnecessarily introduces complexity or overhead that can hurt scaling or even evolution over the long run.
We explore in detail four essential aspects that could help determine whether service integration may be appropriate to carry out a certain task, using factors such as operational complexity, communication overhead, data consistency, and future scalability.
Database transactions are essential to 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.
Consider a service such as “User Registration”, which should provide the functionality of user account creation with a set of default permissions. If this is split into, say, separate services, one for account creation and one for permission management, this would require a distributed transaction to ensure that permissions are only assigned if the account was created. Distributed transactions are notoriously difficult to implement and usually involve advanced coordination mechanisms, making the risk of failure greater.
By integrating these functionalities into one service, you can manage all database operations in a single transaction: either the user account with its permissions will be created successfully or rolled back if something goes wrong. It would keep your data consistent and make the whole system easier.
In the microservices architecture, most of the workflows are distributed across a set of services by using interservice communication. While this allows flexibility and modularity, excessive communication may lead to performance bottlenecks, increased latency, and reduced fault tolerance.
Take, for instance, an order in a “Food Delivery” application. The services involved may have to talk to the order service, the payment service, the restaurant service, and the delivery assignment service. If these services are too decoupled, placing such an order could involve several network calls, increasing the chances of delays or failures. For example, if one single service-the delivery assignment service-goes down, it may block the whole workflow of the order process, and users will not be able to complete their transaction.
This will help the services that are tightly coupled in their workflow-for example, order and delivery assignment services-simplify communication, reduce latency, and improve fault tolerance. This means that even in cases of high workload or partial failures, the system is guaranteed to stay responsive and reliable.
Shared code in microservices, usually maintained through shared libraries, is often considered one way of simplifying development and maintaining consistency. It may introduce some problems with service sizing and independence, though. Changing a shared library requires all the depending services to align with those changes, which disrupts their deployment cycles and introduces dependencies acting against the autonomy of microservices.
A “Customer Management” system can include a number of services-a profile service, loyalty program service, notification service-all using one common library with the logic related to customers’ validation. Such a library should then be updated to implement new rules and such a couple of services will need to realize that update; and not having this done for even a single of those might cause a problem-the consistency of rules would be violated within different components that operate or interact with customers’ data.
In designing services, one should consider whether the code sharing is appropriate for the level of autonomy desired. Where services are highly independent and have separate lifecycles, it may be preferable to duplicate some logic or use service-specific libraries to avoid coupling and preserve flexibility in deployment and scaling.
While good practice in a microservices architecture involves each service having its own database, it brings independence with complicated data relationships. If related data resides in more than one service, it might be difficult to maintain relationships between them. This can bring problems with data integrity and more interservice communication.
For instance, a “Ride-Sharing” platform will have a driver service to manage drivers’ profiles and a ride service to manage trip data. Now, if these services are too fine-grained, storing driver details in one database and trip data in another, operations such as generating the earnings report of any driver or assigning rides to drivers according to their availability will need constant communication between these two services. In this case, unnecessary complexity arises, and often it causes delay when there is heavy traffic.
Here, that may be overkill; it might suffice to merge driver and ride information into a single service operating on a common database. That would have the positive effect of tighter data consistency, less interservice communication, and thus a more responsive system, again underlining the importance of appropriately sizing services based on data relationships.
Sizing a service is a balancing act; the trade-offs between breaking apart services and consolidating them need to be analyzed. While smaller services can provide benefits around scalability and independence, they could add complexity to the system through distributed communication and management. Larger services might simplify the workflows and data relationships at the cost of losing flexibility and autonomy.
This requires close collaboration with business stakeholders to get it right. Business priorities-for instance, around the need for agility, fault tolerance, or cost optimization-inform service-sizing decisions. By doing so, technical architecture meets business objectives while maintaining the system scalable, reliable, and manageable in the long run.
In other words, the right-sizing of microservices is a journey of striking a balance between considerations of disintegration and integration. While the disintegration of services can offer flexibility, scalability, and fault tolerance, for example, it also presents challenges in terms of increased communication complexity and potential data integrity issues. Integration of services offers simplicity but reduces the agility of the system and creates dependencies that make scaling difficult.
The key to getting service granularity right is the trade-offs between the disintegration drivers and the integration drivers. In close collaboration with the business stakeholders, by understanding their priorities and evaluating the needs of each service, you are able to make the right trade-offs that will guarantee a scalable, maintainable, and cost-effective architecture. If done correctly, microservices can offer the advantages promised without the complexities introduced by poor sizing decisions.