We have discussed the unique contributions of the SOA pattern towards establishing and sustaining service-enabled environments and enterprises. The service-oriented architectural pattern has evolved over decades to express and expose any legacy, monolithic, and massive application as a dynamic collection of interdependent services. Services are blessed with interfaces and implementations. Interfaces are the contacting and contracting mechanism for any service-enabled application. There are standards, languages, models, frameworks, platforms, patterns, and a bevy of toolkits to shepherd the service paradigm towards its logical conclusion. Though SOA has done a lot of things for the IT enterprise, there are some issues, drawbacks, and limitations.
The popular SOA style majorly relies on a shared data model with multiple hierarchies. The sharing of databases in SOA tends to create a kind of tight data coupling between services and other system components. This tight coupling comes in the way of bringing forth desired changes in the database. That is, if a few RESTful services are tightly coupled with a backend database and if there is any change mandated and enacted on the database schema, then there is a need for a retesting of services to verify and validate how the services work on the altered schema. This dependency is a bit troublesome for the increasingly automated and dynamic world.
The other challenge is that the services in the SOA style are typically coarse-grained and hence the aspect of reusability is quite a tough affair. Most of the application components of legacy applications are fitted with service-oriented interfaces for enabling discovery, integration, and interactions. At the infrastructure level, there is no dependency problem because these service-enabled application components can literally run anywhere. There is no restriction for co-location. SOA uses a kind of tiered organizational architecture that contains a centralized messaging middleware for service invocation, intermediation, and coordination. But the prickling issue here is that application components need to know the corresponding details of one another in order to initiate and bring the required collaboration, corroboration, and correlation to closure. There are other challenges being associated with the highly matured and stabilized SOA paradigm.
Let us move over to the MSA pattern, which is growing by leaps and bounds. Microservices architecture is the new architectural pattern for defining, designing, developing, deploying, and delivering distributed and enterprise-grade software applications. This fast-emerging and evolving pattern is being positioned as the one for easily and quickly achieving the non-functional requirements such as scalability, availability, and reliability for any software application.
The MSA pattern is for producing fine-grained, loosely coupled, horizontally scalable, independently deployable, interoperable, publicly discoverable, network-accessible, easily manageable, and composable services, which is not only the optimized unit of software construction, but also allows enabling quicker software deployment and delivery. In the past, software companies assembled large teams of engineers to build applications which, over a period of time, became monolithic and unwieldy. Legacy applications are close, bulky, tough to maintain, inflexible, and not modern. We need applications that are adaptive, dynamic, open, easy to modify and enhance, and so on. Having understood the distinct contributions of the MSA pattern, today corporates across the globe are keenly strategizing and planning to embrace this new pattern with clarity and confidence. As a result, enterprise-class cloud, mobile, and embedded applications are being built using the powerful and pioneering MSA pattern.
The growing ecosystem of tools, engines, platforms, and other software infrastructure solutions speeds up the process of producing microservices-centric applications. With the tools-assisted orchestration, microservices are being deftly orchestrated to bring forth versatile applications for business automation, acceleration, and augmentation.
Microservices are built upon a concept known as a bounded context, which leads to a self-contained association between a single service and its data. There is no technology or vendor lock-in as far as the MSA-inspired applications are concerned. Every microservice is being empowered with its own data source, which can be a filesystem, SQL, NoSQL, NewSQL, in-memory cache, and so on. There are API gateway solutions to streamline the end-to-end lifecycle management of microservices. Microservices rely solely on inter-service communication. Each microservice calls another microservice as required to complete its function. Furthermore, called microservices may call other services as needed in a process known as service chaining. Microservices use a non-coordinating API layer over the services composing an application. As Docker containers are emerging as the most appropriate runtime for microservices, the MSA pattern is seeing a lot of traction these days.
Each microservice is being designed as an atomic and self-sufficient piece of software. Implementing an application will often require composing multiple calls to these single responsibility and distributed endpoints. Although synchronous request-response calls are required when the requester expects an immediate response, the integration patterns based on eventing and asynchronous messaging provide maximum scalability and resiliency. The microservices approach is well-aligned to a typical big data deployment.
We can gain the required modularity, extensive parallelism, and cost-effective scaling by deploying services across many commodity hardware servers. Microservices modularity facilitates independent updates/deployments and helps to avoid single points of failure, which can help prevent large-scale outages.
