Drowning in the Data of Things


DrowningSign

If you saw the news coming out of Cisco Live Berlin, you probably noticed that Internet of Things (IoT) was in every other announcement. I wrote about the impact of the new Digital Ceiling initiative already, but I think that IoT is a bit deeper than that. The other thing that seems to go hand in hand with discussion of IoT is big data. And for most of us, that big data is going to be a big problem.

Seen And Not Heard

Internet of Things is about dumb devices getting smart. Think Flowers for Algernon. Only now, instead of them just being smarter they are also going to be very talkative too. The amount of data that these devices used to hold captive will be unleashed on something. We assume that the data is going to be sent to a central collection point or polled from the device by an API call or a program that is mining the data for another party. But do you know who isn’t going to be getting that data? Us.

IoT devices are going to be talking to providers and data collection systems and, in a lot of cases, each other. But they aren’t going to be talking directly to end users or IT staff. That’s because IoT is about making devices intelligent enough to start making their own decisions about things. Remember when SDN came out and everyone started talking about networks making determinations about forwarding paths and topology changes without human inputs? Remember David Meyer talking about network fragility?

Now imagine that’s not the network any more. Imagine it’s everything. Devices talking to other devices and making decisions without human inputs. IoT gives machines the ability to make a limited amount of decisions based on data inputs. Factory floor running a bit too hot for the milling machines to keep up? Talk to the environmental controls and tell it to lower the temperature by two degrees for the next four hours. Is the shelf in the fridge where the milk is stored getting close to the empty milk jug weight? Order more milk. Did a new movie come out on Netflix that meets your viewing guidelines? Add that movie to the queue and have the TV turn on when your phone enters the house geofence.

Think about those processes for moment. All of them are fairly easy conditional statements. If this, then do that. But conditional statements aren’t cut and dried. They require knowledge of constraints and combinations. And all that knowledge comes from data.

More Data, More Problems

All of that data needs to be collected somehow. That means transport networks are going to be stressed now that there are ten times more devices chatting on them. And a good chunk of those devices, especially in the consumer space, are going to be wireless. Hope your wireless network is ready for that challenge. That data is going to be transported to some data sink somewhere. As much as we would like to hope that it’s a collector on our network, the odds are much better that it’s an off-site collector. That means your WAN is about to be stressed too.

How about storing that data? If you are lucky enough to have an onsite collection system you’d better start buying drives for it now. This is a huge amount of data. Nimble Storage has been collecting analytics data from their storage arrays for a while now. Every four hours they collect more data than there are stars in the Milky Way. Makes you wonder where they keep it? And how long are they going to keep that data? Just like the crap in your attic that you swear you’re going to get around to using one day, big data and analytics platforms will keep every shred of information you want to keep for as long you want to have it taking up drive space.

And what about security? Yeah, that’s an even scarier thought. Realize that many of the breaches we’ve read about in the past months have been hackers having access to systems for extended periods of time and only getting caught after they have exfiltrated data from the system. Think about what might happen if a huge data sink is sitting around unprotected. Sure, terabytes worth of data may be noticed if someone tries to smuggle it out of the DLP device. But all it takes is a quick SQL query against the users tables for social security numbers, a program to transpose those numbers into letters to evade the DLP scanner, and you can just email the file to yourself. Script a change from letters back to numbers and you’ve got a gold mine that someone left unlocked and lying around. We may be concentrating on securing the data in flight right now, but even the best armored car does no good if you leave the bank vault door open.


Tom’s Take

This whole thing isn’t rain clouds and doom and gloom. IoT and Big Data represent a huge challenge for modern systems planning. We have the ability to unlock insight from devices that couldn’t tell us their secrets before. But we have to know how deep that pool will be before we dive in. We have to understand what these devices represent before we connect them. We don’t want our thermostats DDoSing our home networks any more than we want the milling machines on the factory floor coming to life and trying to find Sarah Connor. But the challenges we have with transporting, storing, and securing the data from IoT devices is no different than trying to program on punch cards or figure out how to download emails from across the country. Technology will give us the key to solve those challenges. Assuming we can keep our head above water.

 

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One thought on “Drowning in the Data of Things

  1. Pingback: Worth Reading: Drowning in the Data of Things - 'net work

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