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The end is near for cloud computing. Or is it?

Cloud computing is a long way from being fully mature, but its obsolescence may already be upon us. Is the cloud’s future really up in the air?

As Peter Levine, a partner at venture capital firm Andreessen Horowitz, puts it, “Everything that’s popular in technology always gets replaced by something else,” be it Microsoft Windows, minicomputers exemplified by Digital Equipment Corp., specialized workstations typified by Sun Microsystems, or, yes, even cloud computing.

As Levine explains it, cloud computing, which he views as the centralization of IT workloads into a small number of super-mega-huge datacenters, is an unsustainable, unworkable, slow-to-respond method. The need for instantaneous information makes the network latency associated with a device-to-datacenter model and the corresponding datacenter-to-device return trip simply too long and therefore unacceptable.

Computing, Levine suggests, will move to a peer mesh of edge devices, migrating away from the centralized cloud model. Consider smart cars. They need to continually exchange information with each other about immediate, hyperlocal traffic conditions. Smart cars need to know that an accident occurred 10 seconds ago a half-mile up the road, that a pedestrian is entering a crosswalk, or that a traffic light is about to turn red. For this to work requires realtime data collection, processing, and sharing with other vehicles in the immediate area. The round-trip processing in the cloud model isn’t even remotely (pun intended) fast enough.

Text messaging is similar in that messages exchanged between people sitting just feet apart are still routed through a distant datacenter. It’s inefficient, slow (in compute terms), and unsustainable. The centralization is needed only for logging and journaling.

The answer, Levine postulates, is pushing processing and intelligence out to the edge, using many-to-many relationships among vehicles for information exchange, along with edge-based processing based on super-powerful machine-learning algorithms. No wonder he describes the self-driving car as “a datacenter on wheels.” Similarly, a drone is a datacenter with wings and a robot is a datacenter with arms and legs. They all need to process data in real time. The latency of the network plus the amount of information needing to travel renders the round-trip on the cloud unsuitable, though that’s still plenty fast enough for a Google search, he says.

The cloud still plays a role; data eventually needs to be stored, after all. That makes this model not fully edge and not fully cloud. It’s perhaps closer to what Cisco dubs “fog computing.” It also speaks to the inevitability of how IoT-driven smart cities must operate, a concept explained to me by Esmeralda Swartz, vice president of strategy and marketing at Ericsson.

There’s a profound irony to this. We started the age of IT (MIS as it was then known) with the IBM mainframe as the centralized place where all programs ran, all processing was done, and all data was stored. That was blown apart by decentralization, driven by the client/server model, Ethernet (or Token Ring or ARCnet), network operating systems (NetWare, VINES, LAN Manager, 3+ Open, Windows for Workgroups, Windows NT, OS/2 Warp, etc.) and early network-aware databases, such as Btrieve. Cloud computing swings the pendulum back to the centralized data model of the past, albeit with a dose of edge processing.

It’s throwing out everything you know and seeing from a paradoxically different perspective — just like the young girl presented on Christmas morning with her great-grandmother’s heirloom wristwatch, only to declare, “A watch that doesn’t need batteries? Gee, what will they think of next!”

You can watch Levine’s presentation “Return to the Edge and the End of Cloud Computing” on YouTube.

No doubt you’ve already thought about this. Where do you think cloud computing is headed? Is this a technology that is ultimately doomed to be superseded by something different, better, faster, and cheaper? What does this mean for you as an application developer? Share your thoughts and fears; we’d like to hear from you.

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Well, latency tends to be lower, rather than higher,  as tech progresses.  However, the "Cloud" defined as, "the centralization of IT workloads", may be a bit self-serving. 

The Cloud is more,  IMHO, about ubiquity, or the virtualization of "place".  That some devices use the ubiquity inherent in the Cloud paradigm to connect directly (locally) in essentially a peer to peer fashion does not negate the fact that the devices are,in fact, part of the Cloud.

The "...need for instantaneous information.." to be processed at the local site (smart car.. drone.. whatever), is really a need for unprocessed data, which is not really "information" and doesn't need to involve remote data centers in real time, but that doesn't mean those same centers are not where the data collected won't end up eventually.

The Cloud provides many paths to the same end. Large centralized data centers coupled with locally connected, and essentially temporary, peer networks are not mutually exclusive.

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The best computing architecture is that of the human body, All data are stored centrally in a brain (a dual processor) which automatically consolidates data to the warehouse of 'experience' overnight whilst you sleep. The most important sensors and actuators (eyes, ears and voice), operating in real time, are very close to the brain. Other remote sensors and actuators have local built-in functionality. (Touch something hot and you react instantly; no need to ask the brain for permission and instructions.)
LIkewise computers. There is room for all elements of this architecture. The cloud is simply a shared, utility 'body' for many brains - though more vulnerable for that reason. If I were legislating for computer policy, I would be designing laws to protect my nation against the vulnerabilities of cloud service centres.
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