MicroServices Will Drive Tomorrow’s Technology Innovation Ecosystems  

By Jon Nordmark

When Amazon created its virtual assistant Alexa, the retail giant didn’t do all of it in-house. In part, it identified three relatively unknown startups. One had no venture capital funding, a second one had raised a few million dollars from unknown investors, and a third had raised venture. Each had developed voice technologies which Amazon could repurpose for their pending personal digital assistant and other voice initiatives on the drawing boards. The result: a product that’s driving a revolution in voice technology.

Like Amazon’s Echo/Alexa, great products often fuse together multiple technologies — multiple point solutions. For example, the Amazon Go stores are famous for their “sensor fusion” technologies. That kind of modular approach to innovative software development is easier now, thanks to a new breed of “microservices” popping up. Microservices allow large companies to drag-n-drop various software APIs together to get one fast, nimble solution.

Modular is the future

By 2022, 90% of all new apps will feature microservices architectures that improve the ability to design, update, debug and leverage third-party code. Furthermore, about 35% of all those production apps will be cloud-native, according to research firm IDC. This growth will lead to “hyper agile apps”, which are new, internally-generated apps.  They’re modular, distributed, continuously updated and they leverage cloud-native technologies such as containers and serverless computing.

Amazon already operates that way— far beyond its Alexa example. As Dave Gray, points out in his book, Connected Company, you can go to any page on Amazon.com, and in the background it may have 300 custom microservices, bundled together to optimize the shopping experience. Each of those 300 microservices, described as independent but loosely coupled pods by Gray , are all replaceable by new, better-performing services.

Small self-contained teams that operate similarly to pods, or microservices, own these technical pods. McKinsey writes that organizations of the future will not operate as hierarchical machines; rather, they will need to be agile, like a living organism which adapts quickly to changing competitive landscapes.

Faster, flexible, customized

Microservices are not necessarily a completely new approach to software engineering. They cobble together successful and proven concepts, such as agile software development, continuous delivery (CD), service-oriented architectures and API-first design. But by moving to modular from monolithic, you can dramatically speed up deployment cycles for new software, foster innovation and ownership, and improve maintainability and scalability of software applications.  

As a result, you get systems that are highly decentralized in terms of data management, development, deployment and operations. You get flexibility, as you can change, upgrade, and replace pods without affecting other components. Each component, meanwhile, is designed for a set of capabilities and certain levels of complexity.  As a whole, microservice architectures allow for enormous customization and the freedom to choose the best tools for each problem.

Most retailers, most media companies, can’t invest $30 billion in R&D as Amazon does today. Correct? In fact, adding a single software developer can be a big decision for some $100 million companies. But, in this digital-age, lack of capital (or lack of human resources) shouldn’t be an obstacle to innovating faster and more effectively.

My company, Iterate.ai has bet big on microservices to help companies of all sizes innovate faster and at an affordable cost. We built an entire technology workflow around this kind of modular architecture.

Iterate forges new ground

To demonstrate, our microservice tool — Interplay — allows companies to prototype new digital technologies 6 to 15 times faster by using an architecture composed of pre-wrapped APIs from independent startups, APIs from enterprise applications and a lot of independently written AI modules. Consequently, any of those independent nodes can be drag-and-dropped onto a digital workbench. In fact, they can immediately work together — as a working prototype. It’s like an enterprise version of Scratch which kids use to learn software development. The result: chatbots that include natural language processed (NLP) language vocabularies, customized to individual brands, that produce inbound and outbound automated text capabilities. Video aggregation tools.  NLP-driven FAQs for websites. Automated sales assistants for specialty products. Voice bots driven by custom NLP languages. To build these, Interplay uses pre-wrapped and connected APIs. They are placed in sequences like game pieces on a board.

Two of Iterate.ai’s large customers even discovered that Interplay’s prototypes can be ported into production. This removes the need to rely heavily on IT resources to integrate inventive new technologies.

Iterate.ai’s Interplay is among a number of new microservices entering the fray — ones like Kuberneties, Google Cloud Functions, and Goa — serving a variety of technical needs

Likewise, companies taking advantage of Iterate’s Interplay are moving quickly toward IDC’s 9th prediction — that new tools and platforms, plus agile methods, will facilitate lots of code reuse and allow a new breed of less-technical, creative developers to emerge — and that this will create an explosion of digital innovation

The world is changing…

Undoubtedly, their proliferation underscores how innovation is changing. No longer does one company create linear tech stacks hosted on-premise. Instead, the best solutions involve the cloud and a combination of enterprise and startup technologies. Great ideas hide out inside small, unknown startups. Oftentimes, combining multiple point solutions from these startups uncovers the secret.

In summary, just as companies are have evolved to become agile organizations that embrace quick changes and action-based leadership, we predict that technology architecture will follow suit —  they’ll become more modular, and startup technologies will become more drag-n-drop.