If you haven’t noticed, the Internet of Things (or IoT) is THE new conversation for where business and IT meet. IT leaders and IT vendors alike see a nearly unfathomable set of potential value-added solutions, services and business process improvements that come gathering and analyzing the data streaming out of business applications, “smart” machines and (hopefully smart) people.
Hitachi even see the potential to improve society as a whole through Social Innovation.
It’s the combination of this new “smartness” of the machines plus the ability to analyze all of the information coming from those machines (things) that is creating seemingly endless opportunity. The all-knowing Wikipedia helps define a “smart, connected product” by saying they are “embedded with processors, sensors, software and connectivity that allow data to be exchanged between the product and its environment, manufacturer, operator/user, and other products and systems.” Perhaps there are better definitions out there, but this will do for now.
The idea that that embedded IT capability lets a “thing” exchange data with the world around it is what opens up our minds to the possibilities of IoT. Of course, a huge gap still exists in the usefulness of some of these “smart” things and in the understanding of how we will actually use all that data to make better, more automated decisions.
It’s clear that there is a network effect that adds opportunity for greater value creation. In fact, that same all-knowing Wikipedia entry gives a starting definition of IoT as a “network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.” Again, imperfect maybe, but an interesting starting point for the obvious idea that one smart device is good, but many smart devices together can be great.
The idea that a machine can process, generate and communicate data, tied with the opportunity for that data to be shared with other “smart” devices begins to create a network of shared knowledge and potential automation.
But it all comes back to the data and the ability of the machines – or some engine – to analyze and make that data useful. But first, we must figure out of all the potential data a “smart” machine generates, what do we want to leverage for any new service automation, or to communicate to other machines.
This is where the idea of a digital twin, or asset avatar, comes in to play. As a software representation of the “thing” in question, the available sensor data can be mapped and prioritized. What information CAN this smart-machines provide? Which of that information is actually useful? Map those capabilities into the software model and you can pull/track that data, and then ensure it is properly communicated and analyzed.
In many cases that data will be ingested into a smart IoT Platform (like our very own Lumada) for the tracking, analysis and action to take place. A platform like Lumada, must then be built to, amongst other things a) quickly and easily ingest new asset avatars (digital twins) into the system, and b) scale such that vast amounts assets/data streams can be acted upon in real time.
Of course there’s vast oversimplification going on here, but the fundamentals are: “things” gets smart, communicate data, that data is collected, analyzed and ultimately, acted upon. Ta da: IoT.
Interestingly enough, we in IT have spent ages dealing with (to revisit Wikipedia’s definition) systems “embedded with processors, sensors, software and connectivity…” in the data server. You think that smart toaster or connected camera has processing capabilities? Let me introduce you to our Hitachi Virtual Storage Platform (VSP) storage. Or Hitachi Unified Compute Platform (UCP) converged infrastructure. Etc.
As an industry, we’ve done a fairly horrible job of creating the IT resource management frameworks to collect, analyze and automate these very smart devices. Information sharing across vendors and sketchy uses of APIs have hampered us, but maybe more so, the scalability of the data collection engines and difficulty in knowing what data to collect from the devices themselves has left us with insufficient solutions.
But, there’s hope to be had in leveraging IoT technologies to build the smart data center of things. If a digital twin can be made of a pump, or a grinder or an industrial-strength earth mover, one can surely be created for a VSP F1500 or a UCP HC. In fact, I’d argue that digital twins can bring in software-defined “things” into the conversation, as we can create an avatar of key applications and the important data they collect/generate – though applications themselves don’t have the embedded processors and sensors that make dumb things smart. Sometimes software is smart on its own.
The concept of an asset avatar then will help with the ingest and onboarding of data center of things devices, but it will take the scalability of an IoT Platform, built to support thousands or millions of devices, to breathe new life into IT infrastructure manageability.
Cooling systems, power systems and even security systems all provide important data points that can help get a better understanding of what is really going on in a data center. And, they are all becoming “smarter” by the day.
Why does this interest me so? At Hitachi Vantara (yes, if somehow you missed it, we are now Hitachi Vantara!), we have all of the pieces needed to redefine data center management by leveraging the concepts and technologies that underpin IoT solutions. Heterogenerous IT analytics. Lumada IoT Platform. Smart systems. Pentaho and its ability to blend data and bring in non-traditional data sources that surround the data center. Advanced AI technologies. And the ability to package all of this into a easier-to-deploy appliances.
IoT solutions will have profound impacts in how the world works, be it for our lives as consumers, or businesses lives as part of the industrial internet.
But I also see massive untapped potential to turn that same technology inward: into the data center bringing IT assets, applications and data center infrastructure to life, scaling to meet the needs of the modern data center and enabling automation based on real-time correlation and predictive planning capabilities.
The Data Center of Things is coming.
You heard it here first.
And you've probably heard it here last.
Because the industry, I suspect, will be talking about smart data centers. Data centers that are leveraging AI to drive toward a vision of truly autonomous and self-healing existence.
But we’ll know what’s the heart of a smart data center, and that heartbeat is going to sound a lot like IoT.