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There are many fine examples of how a well-executed cloud computing strategy has helped businesses rapidly deploy new systems and accelerate innovative digital transformation initiatives.
On the other hand, and before basking in their glory, we should also be mindful of an indisputable truth - not every workload (or workforce) is designed and ready to best exploit it.
But it's hard to not get drawn into the spin. With the promise of massively cost-effective compute grunt and an unlimited supply of visualised goodness, why not take the plunge?
Why persist in building and maintaining your own high-performance applications when specialised or hyper-scale providers have the savvy and scale do it better, faster and cheaper? Simple economics, right?
Well, perhaps that's true for cloud-native applications built from the ground-up and architected to exploit cool stuff like auto-scaling, DevOps and continuous delivery.
However, and as many organisations can attest, the promise of cloud services as a quick fix for decades of accumulated legacies is also extremely tempting. Especially for those monolithic application "skeletons" we'd just love to house in someone else's closet.
But however well-intentioned our cloud motives, a badly planned and uninformed strategy can have dire consequences for business. Ironically, it's the very nature of cloud models that bite the hardest when scant attention is given to whether it's actually the right approach for certain workloads and use-cases.
Watch out for after-sale 'sticker shock'
Go ahead and migrate that behemoth analytics application to the public cloud, but get ready for a financial wake-up, shake-up or take-down. Memory intensive applications like these require some serious memory horsepower, meaning the organisation could end up having to use the largest and most expensive virtualised instances.
In such cases it might be more cost-effective to acquire and maintain on-premise commodity kit, understanding of course (especially as prices continue to fall), that eventually there'll be public cloud financial "sweet-spot".
This, however, isn't a one-off exercise. As good as organisations need to be at determining which cloud-model is fit for purpose, more attention should be given to continuously exploiting financial nuances and opportunities as they arise across multiple providers - perhaps using brokerage and arbitrage models.
Don't let the dogs out
If you think you'll have giddy sub-second response times by migrating every system to the cloud, think again. Application performance problems can be the death-knoll of many a cloud service, especially those that demand low-latency and throughput.
While housing that old, but trusted SQL database and transactional workhorse in a new-fangled cloud-hosted container might seem like a good idea, it might actually run like a dog in the cloud - especially if careful consideration isn't paid into the performance implications of geographic location and network connectivity.
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