Since the term “microservices” hit the software industry like a bolt of lightning in 2014, technical professionals of all stripes have been analyzing this new architectural style from their own frames of reference. Having lived through the rise and fall of service-oriented architecture, I had the same reaction as many others: How does microservice architecture differ from SOA? The more I learned about the case studies that led to the creation of the term “microservices,” the more I recognized that this question would not capture the essence of this new software movement.
The first thing to recognize about the microservice movement is that it has been empirically defined. Microservice architecture emerged from a common set of patterns evident in companies like Amazon, Netflix, SoundCloud, and Gilt (now part of HBC Digital). Applications at these companies that were monolithic evolved over time into decomposed services that communicated via RESTful APIs and other network-based messaging protocols.
However, the commonalities were not restricted to architectural patterns. The companies at the forefront of microservices also shared a common approach to software development, had similar organizational structures and cultural practices, and shared an affinity for cloud-based infrastructure and automation. Many companies that succeed with microservices have followed a similar progression driven by a desire for development speed and scalability.
The agile progression
In early 2001, a group of software professionals published the Agile Manifesto as a statement of values on how to improve software development. Although the principles stated were not new -- they were a consolidation of ideas from extreme programming, scrum, lean, and more -- the unified voice caught the industry’s attention. Just as microservice architecture is frequently defined in contrast to monolithic architecture, the manifesto differentiates agile software development from “documentation-driven, heavyweight software development processes.” The agile approach sought to remove the overhead and risk of large-scale software development by using smaller work increments, frequent iterations, and prototyping as a means of collaboration with users. The adoption of agile methods in the industry grew consistently following the publication of the manifesto.
The spread of agile methods also led to the popularization of continuous integration (CI) in the software industry, a common practice from extreme programming. CI sought to combine software components as early in the lifecycle as possible in order to minimize the impact of code integration issues. However, many of the early agile adopters found that once they had removed the bottlenecks in the coding, they hit snags in releasing the software. These difficulties were only amplified by the popularization of SaaS as an increasingly preferred deployment option.
To address the need for more frequent software releases, the practice of continuous delivery (CD) started to gain traction in 2006, taking the internal CI concept and applying it to the external view of software deliverables. CD takes scrum’s quality-focused “potentially shippable product increment” literally, defining a deployment pipeline to bring changes to production as quickly as possible. Virtualization and cloud computing removed technological barriers to CD, and new tools emerged to institutionalize CD practices. The combination of agile and CD was improving both the speed of production and the quality of the software produced.
Still, there were bottlenecks. Agile’s primary scope was on the development of software, while CD extended that scope to include production deployment, an operations task. In most organizations, development and operations were consciously divided in both reporting and mission. In 2009, John Allspaw and Paul Hammond from Flickr gave an influential talk at the O’Reilly Velocity conference detailing how they had bridged this gap. From experiences like theirs, the devops movement arose to address this cultural divide.
Organizations found that combining development and operations responsibilities in the same team led to highly effective continuous delivery practices. As collaboration increased between dev and ops, so did empathy. Developers designed solutions that included an operational perspective from the outset, and operations people used an engineering approach to tackle problems that were previously dealt with procedurally. Greater use of automation in day-to-day tasks resulted in greater system stability and resilience. Netflix's Simian Army approach to testing the resilience of production systems is an extreme example of this.
The organizations that followed this "agile progression" -- from addressing software development to deployment to organizational structure -- now had alignment in these areas. Many of these agile pioneers were Web native and provided their software solutions in a single application stack. As the complexity and scale of their businesses increased, they found that this architecture not only became an impediment to new feature delivery, but caused stability issues due to brittleness and lack of scalability. In parallel, several companies -- such as SoundCloud -- discovered that breaking their monolithic applications into discrete, business-focused services was more suitable to their agile delivery methodology and devops culture. This is the true origin of microservice architecture. Microservices are the architectural phase of the agile progression.
In search of agile software architecture
In a 2013 post on his blog “Coding the Architecture,” software architect Simon Brown speculated about what an agile software architecture would look like. He points out that an agile architecture does not naturally emerge from agile development practices. Rather, it must be consciously sought. Note that his description of agile software architecture is a perfect match for microservice architecture (emphases mine):
If we look at the characteristics of an agile software architecture, we tend to think of something that is built using a collection of small, loosely coupled components/services that collaborate together to satisfy an end-goal. This style of architecture provides agility in a number of ways. Small, loosely coupled components/services can be built, modified and tested in isolation, or even ripped out and replaced depending on how requirements change. This style of architecture also lends itself well to a very flexible and adaptable deployment model, since new components/services can be added and scaled if needed.
Companies like Amazon, Netflix, SoundCloud, and Gilt encountered an architectural bottleneck when they reached a certain scale. This barrier motivated them to focus on the architecture, as Brown encourages, and they landed on microservices.
There are important lessons to be gleaned from tracking this agile progression through to its architectural phase. First of all is that agile software development, continuous delivery, devops culture, and microservice architecture are all bound by a common set of goals: to be as responsive as possible to customer needs while maintaining high levels of software quality and system availability. Although these phases evolved in a particular order from the industry perspective, there is no right sequence for an individual organization to follow. For example, Amazon adopted an architecture that forced changes to its organization. By contrast, SoundCloud evaluated its delivery methodology and made changes to its team structure and architecture as a result.
If you are evaluating how you can adopt microservices, it is important to understand where your organization is on the agile progression. Are you an agile shop? If so, who is looking after the architecture of your applications? If not, are you on a path to adopt agile practices? Do you have CD and deployment pipelines in place? What is the relationship between your development and operations teams, and who owns those responsibilities? Weighing the answers to these questions against your primary goals for adopting microservices will help you chart the right course to success that includes incremental wins along the way.
This is the first post in a two-part series from Matt McLarty, co-author of the upcoming book "Microservice Architecture" from O’Reilly Media. This series shares applicable lessons from the evolution of microservices. To learn directly from the early adopters of microservices and to receive a free digital copy of the new book, attend the API360 Microservices Summit in New York on June 16, 2016.
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