At the onset, “Microservices” sounds like yet another term on the long list of software architecture styles. Many experts consider it as lightweight or fine-grained SOA. Though it is not entirely a new idea, Microservices seem to have peaked in popularity in recent years, what with numerous blogs, articles and conferences evangelizing the benefits of building software systems in this style. The coming together of trends like Cloud, DevOps and Continuous Delivery has contributed to this popularity. Netflix, in particular, has been the poster boy of Microservices architectural model.
Nevertheless, Microservices deserves its place as a separate architectural style which while leveraging from earlier styles has a certain novelty. The fundamental idea behind Microservices is to develop systems as set of fine grained, independent and collaborating services which run in their own process space and communicate with lightweight mechanisms like HTTP. The stress is on services to be small and they can evolve over time.
In order to better understand the concept of microservices, let’s start by comparing them with traditional monolithic systems. Let’s consider an E-commerce store which sells products online. Customers can browse through the catalog for the product of their choice and give orders. The store verifies the inventory, takes the payment and then ships the order. The figure below demonstrates a sample E-commerce store.
The online store consists of many components like the UI which helps customers with the interaction. Besides, the UI there are other components for organizing the product catalog, order processing, taking care of any deals or discounts and managing the customer’s account. The business domain shares resources like Product, Order and Deals which are persisted in a Relational Database. The customers may access the store using a desktop browser or a mobile device.
Despite being a modularly designed system, the application is still monolithic. In the Java world the application would be deployed as a WAR file on a Web Server like Tomcat. The monolithic architecture has its own benefits:
- Simple to develop as most of the IDEs and development tools are tailored for developing monolithic applications.
- Ease of testing as only one application has to be launched.
- Deployment friendly as in most cases a single file or directory has to be deployed on a server.
Till the monolithic application is simple everything seems normal from the outside. However, when the application starts getting complex in terms of scale or functionality, the handicaps become apparent. Some of the undesired shortcomings of a monolithic application are as following:
- A large monolithic system becomes unmanageable when it comes to bug fixes or new features.
- Even a single line of code change leads to a significant cycle time for deploying on production environment. The entire application has to be rebuilt and redeployed even if one module gets changed.
- The entry barrier is high for trial and adoption of new technologies. It is difficult for different modules to use different technologies.
- It is not possible to scale different modules differently. This can be a huge headache as monolithic architectures don’t scale to support large, long lived applications.
This is where the book, “The Art of Scalability” comes as a big help. It describes other architectural styles that do scale. It describes scalability model on the basis of a three dimensional scale cube.
The X-axis scaling is the easiest way of scaling an application. It requires running multiple identical copies of the application behind a load balancer. In many cases it can provide good improvement in capacity and availability of an application without any refactoring.
In case of Z-axis scaling each server runs an identical copy of application. It sounds similar to X-axis scaling but the crucial difference is that each server is responsible for only a subset of the data. Requests are routed to appropriate server based on some intelligent mechanism. A common way is to route on the basis of the primary key of the entity being accessed, i.e. sharding. This technique for scaling is similar to X-axis scaling as it improves the application’s capacity and availability. However, none of these approaches does a good job of easing the development and application complexity. This is where the Y-axis scaling helps.
Y-axis scaling or functional decomposition is the 3rd dimension to scaling. We have seen that Z-axis splits things that are similar. On the other hand, Y-axis scaling splits things that are different. It divides a monolithic application into a set of services. Each service corresponds to a related functionality like catalog, order management, etc. How to split a system into services? It is not as easy as it appears to be. One way could be to split by verb or use case. For e.g., UI for compare products use case could be a separate service.
Another approach could be to split on the basis of nouns or system resources. This service takes ownership of all operations of an entity/resource. For e.g., there could be a separate catalog service which manages the catalog of products.
This leads to another interesting question. How big should a service really be? One school of thought recommends each service should have only a small set of responsibilities. As per Uncle Martin, services should be designed using the Single Responsibility Principle (SRP). The SRP suggests that a class should only have one reason to change. It makes great sense to apply the SRP to service design as well.
Another way of addressing this is to design services just like Unix utilities. Unix provides a large number of utilities such as grep, cat, ls and find. Each utility does exactly one thing, often exceptionally well, and can be combined with other utilities using a shell script to perform complex tasks. While designing services, try to model them on Unix utilities so that they perform a single function.
Some people argue that the lines of code (10 – 100 LOC) could be a benchmark for service size. I am not sure if it is a good talisman, what with many languages being more verbose than others. For e.g., Java is quite verbose as compared to Scala. An interesting take is that a microservice size should be such that an entire microservice can be developed from scratch by a scrum team in one sprint.
In all these interesting and diverse viewpoints, it should be remembered that the goal is to create a scalable system without any problems associated with monolithic architecture. It is perfectly fine to have some services which are very tiny while others are substantially larger.
On applying the Y-axis decomposition to the example monolithic application, we would get the following microservices based system:
As you can see after splitting the monolithic architecture, there are different frontend services addressing a specific UI need and interacting with multiple backend services. One such example is of the Catalog UI service which communicates with both the Catalog service and Product service. The backend services encompass the same logical modules which we had seen earlier in the monolithic system.
Benefits of Microservices
The microservices based architecture has numerous benefits and some of them can be found below:
- The small size of microservice leads to ease of development and maintenance.
- Multiple developers and teams can deliver relatively independently of each other.
- Each microservice can be deployed independently of other services. If there is a change in a particular service then only that service need be deployed. Other services are unaffected. This in turn leads to easy transition to continuous deployment.
- This architectural pattern leads to truly scalable systems. Each service can be scaled independently of other services.
- The microservice architecture helps in troubleshooting. For example, a memory leak in one service only affects that service. Other services will continue to run normally.
- Microservice architecture leads to a true polyglot model of development. Different services can deploy different technology stacks as per their needs. This gives a lot of flexibility to experiment with various tools and technologies. The small nature of these services makes the task of rewriting the service possible without much effort.
Drawbacks of Microservices
No technology is a silver bullet and microservice architecture is no exception. Let’s look at some challenges with this model.
- There is added complexity of dealing with a distributed system. Each service would be a separate process and inter-process communication mechanism is required for message exchange amongst services. There are lots of remote procedure calls, REST APIs or messaging to glue components together across different processes and servers. We have to consider various challenges like network latency, fault tolerance, message serialization, unreliable networks, asynchronicity, versioning, varying loads within our application tiers etc.
- Microservices are more likely to communicate with each other in an asynchronous manner. This helps in decompose work into genuinely separate independent tasks which can happen out of order at different times. Things start getting complex with the need for managing correlation IDs and distributed transactions to tie various actions together.
- Different test strategies are required as asynchronous communication and dynamic message loads make it much harder to test systems. Services have to be tested both in isolation and their interactions also have to be tested.
- Since there are many moving parts, the complexity is shifted towards orchestration. To manage this a PaaS-like technology such as Pivotal Cloud Foundry is required.
- Careful planning required for features spanning multiple services.
- Substantial DevOps skills are required as different services may use different tools. The developers need to be involved in operations also.
I am sure with all the aspects mentioned above you must be wondering whether you should start splitting your legacy monolithic architectures into microservices or in fact start any fresh system with this architectural style. The answer as in most cases is – “It Depends!” There are some organizations like Netflix, Amazon, The Guardian, etc. who have pioneered this architectural style and demonstrated that it can give tremendous benefits.
Success with microservices depends a lot on how well you componentize your system. If the components do not compose cleanly, then all you are doing is shifting complexity from inside a component to the connections between components. Not only that, it also moves complexity to a place that’s less explicit and harder to control.
The success of using microservices depends on the complexity of the system you’re contemplating. This approach introduces its own set of complexities like continuous deployment, monitoring, dealing with failure, eventual consistency, and other factors that a distributed system introduces. These complexities can be handled but its extra effort. So, I would say if you can manage to keep your system simple, then you may not need microservices. If your system runs the risk of becoming a complex one then you can certainly think about microservices.