It no longer matters if you’re ready for the cloud, because the tools and techniques increasingly required to do your job are cloud-based.
Cloud is the foundation for everywhere you want to be in 2018, and 2019, and 2020…
For many organizations, the months of 2017 were spent the same way as the months of the previous five years: hand-wringing and worrying about whether they should dip their toes in cloud, if they should dive in, or if they should eschew cloud altogether because of whatever good reason they manufactured. Kicking the can down the road is not a sustainable strategy.
But, we were energized and inspired by working with organizations that were re-inventing hybrid models that consisted of data-here/data-there, compute-here/compute-there, and lift-this, but don’t shift that (and so many more that you can think of).
Cloud adoption isn’t easy, and all organizations have some degree of hem-hawing and second-guessing.
The good news for 2018: It no longer matters.
Adopt a Cloud First Mentality
It no longer matters because the tools and techniques that are increasingly required to do your job are cloud-based. And to use them, a ‘cloud first’ mindset is a necessity:
The data and processing needs from the Internet of Things (IoT) products and devices are massive and constant.
Sure, you can buy-and-build data collectors, but there is also all the sifting, processing, analyzing, and storage dependencies. Even if you’re focused on only 1 of 100 attributes you are collecting today, eventually you will want to correlate the other 99, right?
You don’t have (and should not have) the infrastructure for that. But the cloud does.
The scope and breadth of data needed to feed the engines of AI (artificial intelligence) and ML (machine learning) makes it cost-prohibitive to manage yourself.
Simply copying data to an AI process that lives in the cloud will no longer be viable using ad hoc processes. Your data needs to live in the cloud.
To churn all this collected data, you could conceivably build your own AI clusters and run it on local servers – but now you have idle compute capacity sitting around when you don’t need it.
Whatever Total Cost of Ownership model you used to justify buying and building instead of leasing may not be seeing the big picture.
Servers are dead.
Both in physical and virtual forms. A bold statement, but accurate because the flexibility gained from freeing your applications from the confines of physical and virtual machines by breaking them down at the functional level not only gives you the ability to leverage code across silos – it enables you to reduce your costs by nearly two orders of magnitude.
What’s the likelihood of business continuity or disaster recovery, availability, security, and performance needs being less – or even the same – next year than they were this year?
Wouldn’t it be nice to test the resiliency of your corporate digital assets daily or hourly or even constantly rather than annually, sporadically, or never?
It comes down to this: is your organization in a good position to embrace these changes and capitalize on digital disruption, or will you struggle to move forward to the head of the class?
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About the Author
William Klos is a Senior Architect. William’s career has spanned many aspects of computing and at times has architected solutions from the perspective of data, networking, enterprise, and security – but is primarily an application architect. Most recently, William has provided solutions around Mobility, Cloud, and Big Data architectures, as well as API design and development.