As software solutions continue to evolve and grow in size and complexity, the effort required to manage, maintain and update them increases. To address this issue, a modular and manageable approach to software development is required. Microservices architecture provides a solution by breaking down applications into smaller, independent services that can be managed and deployed individually.
Commonly used in distributed and large-scale systems, this architectural pattern is favored for its scalability, flexibility and suitability for systems that require rapid change and innovation. Continuous delivery, high scalability, agility and modularity are all shiny buzzwords associated with microservices, but they don’t tell the whole story. While microservices offer a number of benefits, it is important to remember that there are also challenges to this approach.
What are microservices, anyway?
The term “microservice” was introduced in 2005 by Peter Rogers, founder of Resource Oriented Computing. He used “micro-web-services” to describe more flexible and more service-oriented software architecture.
The microservices architecture is an approach to the development of software as a series of small services that can be deployed independently of each other. The basic principle of microservices, the division of software components into modular units, is nothing new, but rather based on the principle of Service Oriented Architecture (SOA) which came into use in the late 1990s. The microservice architecture is commonly considered an evolution of SOA because its services are more differentiated and run independently.
In a monolithic architecture, everything is implemented as a single, tightly coupled unit, with all components in a single code base. In contrast, a microservices architecture decomposes the application into an unlimited number of small, loosely linked services. Each of these services is responsible for one specific aspect of business.
Microservices are not just a technical approach. They are also an organizational approach. Conway’s law states that “Organizations which design systems […] are constrained to produce designs which are copies of the communication structures of these organizations.” In terms of that, it makes sense that there is also a need for a change in the organizational structure when implementing microservices.
Microservices are therefore, as already mentioned, a strong modularization concept. Microservices can communicate with each other via an application programming interface (API) that supports loose coupling. Traditional monolithic structures suffer from a tight coupling between its components, introducing high dependencies between modules. Each of those separate Microservices can be deployed and tested independently. As they communicate using the same protocols it doesn’t matter which technology they use in their implementation. The individual microservices can, for example, be programmed in different languages.
Why do we want a microservices architecture?
In an ideal world microservices help you…
Unlike vertical scaling, also known as scaling up, where more resources are added to a single node in the system, there are no limits (from a hardware perspective) to horizontal scaling. Horizontal scaling, also known as scaling out, involves adding more nodes to the system, such as adding more servers to a cluster. An important advantage of horizontal scalability is the ability to increase capacity during operation.
The strong modularization makes the software easily accessible. A microservice is used for a single task and is designed to perform that task in the most effective way possible. A single service is easier to maintain and can be easily replaced. The modularization logic also makes it easier to build in redundancy, services can be duplicated very effortlessly. In addition, the individual components can be easily reused and developed further.
… create loose coupling.
Since the services communicate via an API, they are ideally only loosely coupled. Loosely coupled in this context refers to a system in which the individual microservices are designed to operate independently and do not have a tight dependency on each other. Separating the application into individual services prevents undesired dependencies.
An independent deployment allows frequent releases while the rest of the application remains available. This means that they can be modified, tested and put into production independently of each other. The individual microservices can be developed and maintained independently by business-oriented, cross-functional teams. Ideally, the teams should manage their products throughout their entire lifecycle. Following Amazon’s guiding principle „You build it, you run it”.
…be technology independent.
As mentioned above, microservices can be implemented in a technology independent way. Thus, they can be built in a way that suits their task best. Development teams in varying expert areas can use the language that suits their needs (e.g.: AI related parts of the application are implemented in python, C++ is used for critical real-time services).
Ideally, each microservice has its own database, decentralizing responsibility and allowing updates to be made on an individual basis. In addition, distributing the services to independent databases avoids the problem of a Single Point of Failure (SPoF).
Are the benefits of microservices architecture overstated?
Microservices can help you scale and increase the availability of your system, but if you can’t effectively manage and coordinate the communication between services, it can lead to increased complexity. One of the main challenges is effectively managing and coordinating the communication between microservices, as it can lead to an increase in complexity.
The availability of the whole system decreases with the creation of more microservices . If we assume a 99% availability for a monolith, the availability of a system of microservices is reduced with each additional component that also has a 99% availability; to determine the availability of the whole system, the availability of the individual components are multiplied.
It is easier to debug and test a single microservice compared to a monolith because they are smaller and more manageable. However, debugging multiple microservices in a system can be challenging because it can be difficult to understand which microservice is performing a particular task. In contrast, observing the behavior of the system as a whole is relatively straightforward with a monolithic architecture. Debugging microservices can be a complex and time-consuming process because it requires a more nuanced understanding of how each component interacts.
So what is the best way to test such a complex system? Netflix, for example, implements chaos testing involving planned failures of its own services to test its systems’ ability to handle unexpected and faulty conditions. Another more conventional method would be integration testing which involves testing the interactions between microservices by creating test scenarios that simulate real-world interactions between them. The disadvantage of this method, however, is the lack of knowledge about what happens when one or more services fail. Depending on the specific requirements and characteristics of the microservices and the system as a whole, it may be helpful to combine several testing approaches.
The communication between different microservices should be decreased to a minimum thus only if they need functionalities of other microservices. If the communication between microservices frequently becomes a hindrance, it may indicate underlying architectural issues. A common problem with tightly coupled microservices is that changes in one microservice can have a domino effect on other microservices, leading to unexpected behavior and failures. Another issue is the over-reliance on synchronous communication between microservices, which can lead to deadlocks and slowdowns.
Managing the entire system can be complex, especially if the organization lacks technical expertise. In such cases, utilizing cloud providers like AWS or Azure can be a viable solution, though it may result in increased cost. Additionally, the implementation of a fail-safe API is crucial, but can be a complex task.
Another challenge is the independent deployment of microservices, which increases the operational overhead, testing challenges, and the need for specialized technical expertise. This can result in a higher level of complexity in the overall system. The decentralization of services can also increase the attack surface, making it more difficult to secure the system.
In the ideal microservices world each microservices has its own database. In reality, it is difficult to keep the data of the services separate with data that is needed by multiple microservices. This contradicts the approach of splitting the data into separate databases. A compromise needs to be found between how to split the data into separate databases and how to maintain data consistency.
For the use of microservices additional skill is needed such as knowledge about Kubernetes, Container, Logging or CI/CD Pipelines compared to monolithic applications. For smaller applications, a monolithic approach is more advantageous due to lower overhead in setting up and maintaining the system, as well as simpler and easier testing and deployment processes.
- Be clear about why you want to do microservices. Is it because everyone else is doing it or because you need it? A microservice should not be the goal in itself, it can be more of a way to get to your goal.
- Consider whether your application is too small. Microservices only make sense when your application reaches a certain size. Below that, the overhead of microservices is far too big.
- If it is not possible to divide the project into small parts without creating a large number of dependencies, then you should leave it.
- See if your organization has the ability to break down the structures to make microservices work and has the capacity to maintain the infrastructure needed for microservices.
- Think about testing the whole system – We already know from monolithic applications that testing is crucial. However, it is equally important that the interactions between microservices can be tested effectively. Automated testing provides you assurance in the reliability and functionality of your system.
- Consider whether there is a need for scaling to that extent. For a website with constant traffic or no spikes, it is possible to work well with monolithic systems as there is no need to scale resources quickly “on the fly.”
The question of when to prefer microservices over a monolithic system is a complex one that requires an understanding of the drawbacks and benefits of both approaches. There are certain guiding rules or criteria that can help determine when it makes sense to adopt microservices, such as the size and complexity of the system, the need for increased scalability and resilience, and the skills and resources available to manage and maintain the architecture. Understanding these factors can help organizations make informed decisions about whether to adopt microservices and how to implement them effectively.
What does the future hold for microservices?
Monitoring the health and performance of microservices can be a complex task and is likely to be a central area of interest in the future. The serverless computing approach is also expected to gain traction in the microservices space, as organizations do not have to worry about the underlying infrastructure. Finally, I would like to mention the ways in which artificial intelligence could improve microservices in the future. It is conceivable that AI algorithms could be used to improve the resilience of microservices through AI monitoring and management. Alternatively, the use of AI could be to improve communication between individual microservices. As these technologies continue to develop, it is likely that more and more new applications will emerge.
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