If you've been in the IT industry for any time at all, you know how analysts and vendors are perpetually in search of the New Shiny Thing:a brand-new super-cool technology that will change everything.
Big data. In-memory analytics. Internet of things. AI and machine learning. Blockchain. Hyperconverged. Flash.
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Gartner does a good job of putting all the New Shiny Things in perspective with their infamous hype curve. Always a bit sobering to those of us who occasionally get swept away with unbridled enthusiasm.
But I'm here to argue that we'll see a lot less attention paid to new shiny things than we've seen in the past.
Why? These new capabilities will simply become integrated features of the IT services we will already be consuming in the cloud.
It's A Connected World
Doing that in the data center can be hard, doing that in a modern cloud seems almost trivial by comparison.
As a first, example, let's start with the internet of things: hanging sensors off just about anything that might be useful.
Well, to be useful, you'll have to gather all that data, reason over it, and act accordingly.
For example, elevators hooked into a field dispatching application. It's the application that matters really, not all the data streaming in.
But what if you were running SaaS field dispatch and your SaaS vendor also had a nifty IoT PaaS service ready to go?
Putting the pieces together becomes almost trivial.
Also notice that IoT gets a whole lot less shiny and glamorous when it's simply a feature of the application you're using.
As another example, let's consider machine learning. Very cool stuff.
But if you sat down and made a list of all the everyday business processes that could potentially benefit from machine learning, it would be almost all of them. The best price and time to place that purchase order. The candidate most likely to succeed in a given role. Managing inventory. On and on.
But if you were running SaaS applications and your vendor simply enhanced your business processes by adding a machine-learning recommendation engine, pre-populated with training data sets -- well, wouldn't that be better?
Machine learning becomes a whole lot less shiny and glamorous when it's simply delivered as a feature of the software you're already using.
Take something as familiar as flash storage. In the data center world, you'd have to put in some serious effort to determine whether it was worth the additional cost. In the cloud world, you simply provision a flash-based instance and can decide quickly in hours vs. weeks.
Unless it's lashed into the systems of record (e.g. ERP, supply chain, financial apps), its appeal as a standalone technology is limited.
If your SaaS/PaaS vendor was already running your core applications, and had easy-to-use blockchain service, no big deal -- simply stitch a few things together.
The shiny, new thing is always there, ready to be used at a moments's notice.
All the mystery goes out of it.
Cloud SaaS and PaaS Models Change How We Look At New Tech
The new, cool things we vendors harp on just become a new feature of the stuff people are already using.
The question becomes less "what is this amazing new tech?" and more like "how can this new feature help me?"
If you're a finance professional, you go to a finance show to understand how and where new features might be applied in your world.
Same if you're in HR, marketing or IT. New, glitzy tech quickly becomes easy-to-use tools in everyone's workbench.
No secret handshake required.
Cloud As A Platform For Business Innovation
All these modern business processes can be easily enhanced and differentiated simply by applying a rich set of cloud services to specific business situations. Pick your target and go.
Done strategically, a shift to a SaaS/PaaS model can help future-proof your business. That's a big statement. And one of the big reasons I work for Oracle.
It's a brave new world we're entering.
And new, shiny things won't be what they once were.
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