In this guest post, J. Tyler Rohrer, co-founder of Liquidware Labs, explains how the use of cloud apps can help user solve end user computing scalability issues.
We are about to enter the golden age of end-user computing (EUC), with the concept now blossoming out of the legacy client-server model and into one that is mobile, cloud, and application-centric.
The explosive growth of mobile tablets, phablets, smartphones, ultra-books, laptops, semi-reliable wireless, mobile networks and cheaper, more intelligent storage (coupled with a rise in cloud services and modern apps) is incredible.
There are some niche offerings, like application virtualisation, application layering, VDI, Desktops-as-a-Service, Storage-as-a-Service, and Enterprise Mobility Management (EMM) – but these are incremental.
These still, for certain use cases, bump up against the limits of the laws of physics like that nasty speed of light latency constraint. And not just in network performance terms, but application response times, storage retrieval times but also the very nature of Moore’s law itself.
What’s the problem?
In the past, Moore’s law was an incredible benefit to most modern desktop administrators. We could rest assured that computing power would nearly double every 18 months, while the cost of that compute would be halved.
However, in our rush to throw progressively less expensive yet powerful hardware at most problems, we created an even larger web of intricacy. We created a topology that – while logical – lacked scale.
The tentacles of our client-server networks sprawled. Most user devices were (and still are) incredibly “stateful” – with proprietary configurations, sensitive data, and tuned applications delicately installed on commodity-class hardware.
In a thought, scale got away from us. The larger our deployments got, the more acutely painful the weight of this scale on our operations and systems management became.
Sure, we bought tools that patched the holes, rather than filled them. While somewhat tenable in the campus environment – laptops and mobile “off network” computing was a target for both accidental and malicious data (IP) loss and risk.
Because we had varying user types with different machines, images, applications, printers, and policies, we tended to have a one-to-one relationship with each desktop – or better yet, something that automated remedial tasks.
While these tools boosted productivity somewhat, the lag to buy, image, provision, and deploy a new laptop, desktop or whatever, was still measured in days or hours at best.
And while we mention security above in the context of risks and attacks, the fact the majority of our corporate IP rests on commodity-class hard drives today, that are not backed up upon each write, could be catastrophic.
What we need to work out is how to create and deliver productive and secure workspaces for our end users, while getting scale to work for and not against us.
Stateful computing was a worst-case scenario in the past. A user might need an app, large storage, lots of memory, and – so – we gave it to them. It was cheap and promised to get cheaper. But all that “state” is what we are fighting now.
With the rise cloud apps, very little “state” now resides on devices, particularly where smartphones and tablets are concerned.
For that reason, I think what we shall soon find is the operating system – whether it’s Windows, Android, OS X, iOS, or Linux doesn’t really matter when you reach a truly stateless workspaces.
The “cloud” however ushers in an entirely new way of thinking about client-server computing. Instead of long distance connections, we have a fabric.
The things we need are, or can be, a click away so the idea of having them installed becomes archaic. All this “state” being removed from the device now lives as a service, distributed across this cloud fabric, for use when, where, and as needed.
So it’s the availability of a potential service I might one day need that is the solution.
And with global replication via cloud services, web-scale file systems, and hybrid models – the latency that punished the client-server architectures of old is minimised and architected around.
We see projects like Citrix Workspace Cloud, VMware Project Enzo, Amazon Web Services and Microsoft Azure, metadata rich file systems like Nutanix Medusa, and workspace tools by my company Liquidware Labs all tackling this challenge of wrangling scale back into Pandora’s box on both large and individual user levels.
We are all very, very close. While the combination of these technologies will be relegated to specific use cases for the next few years – we will see convergence of x86, cloud, and mobile into single platforms.
And while we will continue to have rich and robust local processing, graphics, input, and display technologies at our fingertips our “state” will live in clouds.