Microservices is one of the increasingly popular architecture patterns next to Service Oriented Architecture (SOA), complemented by DevOps and Cloud. Its evolution has been greatly influenced by the disruptive digital innovation trends in modern business and the evolution of technology in the last few years. We will examine these two catalysts--business demands and technology--in this section.
In this era of digital transformation, enterprises are increasingly adopting technologies as one of the key enablers for radically increasing their revenue and customer base. Enterprises are primarily using social media, mobile, cloud, big data, and Internet of Things (IoT) as vehicles for achieving the disruptive innovations. Using these technologies, enterprises are finding new ways to quickly penetrate the market, which severely pose challenges to the traditional IT delivery mechanisms.
The following graph shows the state of traditional development and microservices against the new enterprise challenges, such as agility, speed of delivery, and scale:
Note
Microservices promises more agility, speed of delivery, and scale compared to traditional monolithic applications.
Gone are the days where businesses invested in large application developments with turnaround times of a few years. Enterprises are no longer interested in developing consolidated applications for managing their end-to-end business functions as they did a few years ago.
The following graph shows the state of traditional monolithic application and microservices in comparison with the turnaround time and cost:
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Microservices provides an approach for developing quick and agile applications, resulting in a lesser overall cost.
Today, for instance, airlines are not investing in rebuilding their core mainframe reservation systems as another monolithic monster. Financial institutions are not rebuilding their core banking systems. Retailers and other industries are not rebuilding heavyweight supply chain management applications, such as their traditional ERP's. Focus has been shifted from building large applications to building quick win, point solutions that cater to the specific needs of the business in the most agile way possible.
Let's take an example of an online retailer running with a legacy monolithic application. If the retailer wants to innovate their sales by offering their products personalized to a customer based on the customer's past shopping preferences and much more, or they want to enlighten customers by offering products to customer based on propensity to buy a product.
In such cases, enterprises want to quickly develop a personalization engine or an offer engine based on their immediate needs, and plug them into their legacy application, as shown here:
As shown in the preceding diagram, rather than investing on rebuilding the Core Legacy System, this will either be done by passing the responses through the new functions, as shown in the diagram marked A, or modifying the Core Legacy System to call out these functions as part of the processing, as shown in the diagram marked B. These functions are typically written as microservices.
This approach gives organizations a plethora of opportunities to quickly try out new functions with lesser cost in an experimental mode. Business can later validate key performance indicators change or replace these implementations if required.
Emerging technologies have made us rethink the way we build software systems. For example, a few decades ago, we couldn't even imagine a distributed application without a two-phase commit. Later, NoSQL databases made us think differently.
Similarly, these kinds of paradigm shifts in technology have reshaped all layers of software architecture.
The emergence of HTML 5, CSS3, and the advancement of mobile applications repositioned user interfaces. Client-side JavaScript frameworks, such as Angular, Ember, React, Backbone, and more, are immensely popular due to their capabilities around responsive and adaptive designs.
With cloud adoptions steamed into the mainstream, Platform as a Services (PaaS) providers, such as Pivotal CF, AWS, Sales Force, IBM Bluemix, Redhat OpenShift, and more, made us rethink the way we build middleware components. The container revolution created by Docker radically influenced the infrastructure space. Container orchestration tools, such as Mesosphere DCOS, made infrastructure management much easier. Serverless added further easiness in application managements.
Integration landscape has also changed with the emerging IntegrationPlatform as a Services (iPaaS), such as Dell Boomi, Informatica, MuleSoft, and more. These tools helped organizations stretch integration boundaries beyond the traditional enterprise.
NoSQL and NewSQL have revolutionized the space of the database. A few years ago, we had only a few popular databases, all based on relational data modeling principles. Today, we have a long list of databases: Hadoop, Cassandra, CouchDB, Neo 4j, and NuoDB, to name a few. Each of these databases addresses certain specific architectural problems.
Application architecture has always been evolving alongside with demanding business requirements and evolution of technologies.
Different architecture approaches and styles, such as mainframes, client server, n-tier, and service oriented were popular at different times. Irrespective of the choice of architecture styles, we always used to build one or the other forms of monolithic architectures. Microservices architecture evolved as a result of modern business demands, such as agility, speed of delivery, emerging technologies, and learning from previous generations of architectures:
Microservices help us break the boundaries of the monolithic application and build a logically independent smaller system of systems, as shown in the preceding diagram.