Not too long ago a Tweet streamed by in my feed announcing that Android has finally overtaken Windows as the most used operating system on the Internet. That news was rather astonishing to me, especially because Windows had an 80% market share just five years ago.
The lesson learned here is that no matter how well positioned a company may be in its industry, it can never rest on its laurels. One of the biggest drivers of change and disruption in any industry is the emergence of new technologies. Companies who sit on the sidelines and bypass these new technology trends risk becoming the next Blockbuster or Kodak. But what is even scarier is companies that embrace these emerging technologies are able to innovate so quickly, that other companies that are just dipping their toes in the water are being left in the dust. Business agility is the new currency.
These strategic technologies have a few characteristics in common.
- They require massive amounts of infrastructure to process at scale
- They are ingesting and processing petabytes or exabytes of data
- The underlying infrastructure, databases, and middleware are extremely complex to implement in the legacy DIY (do it yourself) model
- The applications that leverage these technologies are elastic in nature
These four characteristics fall into the sweet spot of public clouds. Elastic applications are best suited for on-demand resources. This is a core value proposition of the cloud. Buying excess capacity for unpredictable spikes in demand is something a CIO who wants to keep his job should not be practicing in this day and age. Private cloud advocates will claim that they can provide elasticity at a lower cost and with more control. I can argue against that in another article for another day. But that argument becomes irrelevant when you add the platform’s capabilities and managed services that these cloud providers offer.
Services like Google’s Big Query, AWS’s IoT Gateway, and Azure’s Analysis Services are tremendous accelerators for developers. All of the complex IT plumbing is just there running and scaling on demand. These services are also fully integrated with the platform, thus reducing ugly integration nightmares such as trying to cobble together and manage a dozen different point solutions to do the same job on-prem.
Three Popular Buzzwords: Big Data, Machine Learning, Artificial Intelligence
All of the big three public cloud providers (Amazon, Google, Microsoft) have done an excellent job of providing developers with simple APIs that abstract the complexity involved in installing and integrating all of the underlying technology stacks. Take a look at the complexities in implementing a big data solution.
This is a very complex architecture that is required to meet all of the business, security and regulatory compliance requirements of a typical large enterprise. But what you may not realize is that each icon on this diagram is a managed service. Each managed service is an abstraction of many underlying technologies. A company trying to build this in the DIY model would spend weeks or even months to implement this solution, not to mention a small fortune. Add up all the icons and you quickly see that it would be easy for a company to “go dark” on the business for 12-18 months just getting the infrastructure vendor products ready to write the first line of application code.
That is before we even get to machine learning and artificial intelligence. Previously, a company would need to hire an army of PhDs to implement the underlying technologies and train the models required to teach the systems to learn patterns and discover insights. Once again, the cloud providers are abstracting away all of these complexities and allowing mere mortals to use machine learning and artificial intelligence APIs to create business value. I was at a Google Next conference two years ago and watched a colleague who knew very little about machine learning models train a model in less than 20 lines of code. My jaw hit the ground.
Not only are the cloud providers making the technology simple to consume, but they are greatly reducing the time to market and cost of entry. In industries like genomics and space research, companies are able to perform research that was not even feasible or even possible in the on-prem and DIY model.
The Internet of Things
The Internet of Things introduces a whole new set of technical challenges because of the exabytes of data that need to be processed live outside of our datacenters or clouds. Building your own IoT architecture requires Herculean efforts. Have no fear though. Public cloud platforms have provided a collection of APIs that interface with your devices and provide the necessary ingestion capabilities, security framework, workflow and infrastructure to simplify and streamline your IoT processes. AWS has even partnered with some of the major chipmakers to embed a SDK on a chip for developers to perform process-ing out on the edge.
Here’s another advantage of the cloud. Architects building IoT applications can leverage their existing security, networking and deployment architectures that are the result of previous work building other applications. This is the beauty of what the cloud providers are offering their customers. As companies mature in the cloud and move to the more advanced technology concepts like IoT, intelligent apps, blockchain, and others, they get to build on top of existing investments. Each new managed service comes fully integrated with existing security, logging, and monitoring frameworks.
Where do we go from here?
IoT, 3D printing, robotics, virtual and augmented reality, drones and many other emerging technologies all leverage the cloud in some fashion. All of these technologies produce huge amounts of data or perform various algorithms that crunch and analyze data. The public cloud provides extremely cheap storage. This, coupled with a large collection of managed services help turn innovative ideas into new solutions more cheaply and faster than previously imaginable.
Traditional applications were built off of a list of known requirements that were turned into systems based on prescriptive needs. Tomorrow’s applications will be adaptive, self-managed, self-learning, dynamic, and even unpredictable. Data centers were designed for predictability. Clouds were created for innovation and volatility.
With each new technology comes the need for more compute and storage. Trying to keep up with this demand in the data center will be a losing game. I believe that business agility is the currency of tomorrow. The scales have tipped beyond the days of a central IT team controlling and dictating all of the technologies. To stay in the game IT must become an enabler of emerging strategic technologies if they don’t want their enterprise to be the next case study of a company that went from market leader to extinction. The rate of innovation is so fast that dipping the toe in the water can be a failing strategy. I recommend that companies start actively pursuing meaningful proof of concepts on the technologies that are relevant for their industry. To quote Eric Roth, American screenwriter, “Our lives are defined by opportunities, even the ones we miss.”