Identify emerging cloud technologies

- There are traditional cloud technologies and then there are some that sit outside of the traditional technologies. What are we talking about? Emerging cloud technologies starting right now. - [Narrator] You are watching It Pro TV. (upbeat music) - Hello ladies and gentlemen, thank you for tuning into more of the CompTIA Cloud Plus, we are talking, well all things cloud. And in this episode we're going to be talking about some of the offerings that are out there that kind of sit outside of some of those classic cloud offerings that have really been around for 10, 15 years now. And these are some of the emerging technologies. Ronnie, thank you for joining us on. One of the things that I think about is just the prevalence of all things connected to the internet today. And what are we saying clever way to say internet of things, IOT devices. They have become so prevalent that one of the things that I've heard in some of the studies is that by the end of 2025, we're going to have 50 to 60 billion devices connected to ethernet based networks worldwide. That's a lot of devices, that's a lot of sensors, a lot of different things. And hopefully by now you understand what IOT is, but how does that relate to the cloud? - All right, so when we start talking about these things, right? Emerging cloud technologies are technologies that are not traditionally based in terms of what we've already seeing, the infrastructure as a service, the platform as a service, the software as a service, all that, we haven't actually, you know, seen. So when we start talking about it, it kind of falls into three major categories for us. So let's take a look here. There is IOT, just like what Wes was mentioning, this is probably the fastest growing field for every consumer that's out there because of the number of devices that can actually be put in place. So we definitely want to dive in that. We're also going to talk about a term that again, has thrown people into a tizzy here, the idea of serverless and what the heck does that mean? And then lastly of course, the major buzzword and the idea of every sci-fi movie that there ever is artificial intelligence and of course machine learning. So those are three of the major technologies that are emerging. And maybe at this point, as you watch them, they're probably fully baked in in terms of the maturity of them when it comes down to it. So on the internet of things, right, just like what Wes did was describing here, okay, that we now have not only of course the ability to access resources in the cloud, but we can now take devices that we purchase and be to actually put them somewhere and have them report information back into the cloud itself. Then of course we can make decisions based off of that if we want to. Now for us here, this actually includes so many different examples of them wearables such as something like my smartwatch here, right, that I have access to, the cameras that are actually available, like nest cams, that may be out there, climate control, Wes, do you have this in your house where you actually kind of just go, Hey, I want it to be 78 when I get home and you just kind of tap a button? - Oh no, my wife has two steps from wearing tinfoil hat. She doesn't want any of that. - Oh, okay, well- - Thinks Hal's going to come in there and say, I'm sorry Wes, I cannot do that. - It may happen for all I know. So who knows? Yeah, connected cars. Skynet is just right around the corner. - That's right. It's right around the corner. - And smart homes, right? - Yes. - All these are actually kind of some of the different things here, and those sensors and the amount of sensors, right, that are actually put out there, well, all those are actually connecting, reporting back to somewhere. So usually this is going to be some type of cloud that's available, most of the time you might see where they actually just report back to their own service. For example, if you have, let's say a Chrome cast, right, that you're using, even though it's really only supposed to allow you to do something, like I want to broadcast my computer screen onto this TV that's actually right here that we can watch something. Well, it requires an internet connection, well why, when it's only really needing to use wifi, it's 'cause it's sending information somewhere. - That's right. - So in other words, this is actually connecting back to the cloud. Anything you do with Alexa, hopefully I didn't just wake up a device in our room here. - You probably did. - More than likely did just because I actually mentioned the word Alexa. And so you know when you have something like that, right? All this stuff actually connects back into the cloud to give more and more information then that is going to be valuable at some point in time. So you realize that, yeah, the idea, the internet of things, it is super prevalent and it's not going to actually get any less. - You know Ronnie, I want to put this into context for some of the viewers out there that says, oh man, I've got an Alexa device, I've got a Google device. Heck I might even have a Nest device, right? Why do we need the cloud? Well, I want you to understand that what we're not telling you in depth here is the scalability. Imagine having a fleet, right? A fleet of 10,000 vehicles that you need to deliver to and you need things like what is their fuel efficiency? What are their trips, right? What was the time that it took, right? Our driver advocate, if you will, are the drivers taking breaks? And you have to do that at such a large scale. This is where you're going to utilize the power of the cloud, right? We're not just talking about a simple nest device like Ronnie mentioned, connecting back to a server and you subscribe to that service. We're talking tens of thousands of devices, hundreds of thousands, millions of devices, that you could have companies, entire sensor nets that are being, have all of this information and we need to in be able to it, bring that information in it, consume it, and make some kind of sense out of it as well. - Yeah and that's kind of the key behind why this is growing in popularity. You don't actually have to configure any of those devices. You just kind of plan it, make sure it actually has internet connection and it's off and it's ready to go. So in these actually are different examples that we can talk about there, but you'll see more and more of this as it goes on. So anytime you plug in a device that says I need internet access, well that's probably part of the internet of things when it comes down to it. - Now this next technology, Ronnie, is the one that you talked about called serverless. And one of the things that comes to mind, I was kind of laughing as you said that, and it's nothing real funny, but in my mind I'm thinking, well this is definitely, definitely a technology Wes can use 'cause I don't have to worry about crashing the server right? Now, joking aside, that's not a bad thing, right? But there are ways that we don't have to worry about doing things like configuring the servers and stuff, but help us out with a little bit more detail on it. It's not just less servers if you will or not having servers, but it's, there's a little bit more to it than that, right? - Yeah. When it comes down to serverless, it's a misnomer. I mean that's what it really comes down to. So one of the things that really kind of bugs people, and I remember first getting in IT, when I heard the term server, I always thought about the idea of hardware, right? And that that's exactly what we needed was a big piece of hardware. So people would get confused by that and then they'd come to an IT professional like Ronnie and go, what do you mean by server? Well, it's really just something that's running in the background, you know? And then people would get even more confused by this, well, when they actually need the services of a server, okay? They don't really need to touch the server. So somebody decided that the term serverless is the way to go. You still have access to do all the things that you can do normally with a server, but you just don't have any management operation of any of the infrastructure in the background. So don't have to worry about configuring, they don't have to worry about doing anything. The reason why this actually helps, let's say someone that's in development, for example, that may know how to develop and know write code like crazy, okay, maybe the best person on the planet write code. They may not know how to get a server configured in terms of networking, how much resources that they need. They may not have all of that stuff, but the idea of serverless says we can actually build it and have it go as the person continues to work. So the person can just focus in on the development here of maybe new features to an application, extended functionality that they need to continue to just code or optimize the code without having to worry if they're going to overrun the resources that are actually available. Now in the cloud, because we've talked about this before, the idea here of the way that this, that the cloud can be provisioned, we also can actually have it on demand as well, is that it only actually is paid for when we use it. So unlike just turning on, and you can actually do that, you can cause a, you can spend a lot of money, Wes, if I actually just go and launch a VM and just leave it running, I can spend a ton of money, if I forget about it, let's say for a month, it can cost me, okay, if I'm not very careful. But in this type of environment, you don't have to worry about that. It actually only costs you when the code is running itself. So it is a run only on demand. You're only paying for when it's actually being used in that sense. So that is, that means we don't have to manage it, okay? Just like it says no management, we don't have to worry about the operation of it. Somebody that actually needs something like that but still needs all the capabilities that they would normally need, this is probably a very opportune way to be able to use the cloud effectively, keep it cost effective. So examples of this type of service, AWS has a service that they call Lambda, okay? Azure has a service that they call Azure functions and Google has something that they call Google cloud functions. Oh, all those are actually just different examples of some type of technology that you and I would call serverless technology. Don't get in mind that that means that there are no servers running in the background. It means you don't have access to control those servers. There's still servers back there, they're just managing it for you so that you can focus in on what's really important. - Alright, Ronnie, let's go ahead and bring Skynet online here and become self-aware in this next one. Now this is this, this next topic that we're going to talk about is definitely one of the key buzzwords when it comes to cloud computing today, but it's very, very important. So let me set you up with a scenario and Ronnie, maybe you can help me out. So I do have IOT devices, I've got a million of them, right? They're scattered across the United States. They're bringing in telemetry information, bringing in things like pressurized sensors, you name it. But we've now got all of this information. What do we do with it? Wouldn't it be nice to have some kind of system that would have the intelligence to run across all this information and identify key aspects and make that information valuable to us? And what I'm talking about here, Ronnie, is artificial intelligence, - Right? So this again is one of those terms that really scares people, right? Skynet, whatever else that there may be out there, but it's artificial intelligence. So what Wes is talking about is taking all the information that's actually gathered that we can actually have and then being able to make some type of decision about them to produce some insight about them. And that's the key here. Artificial intelligence AI really can actually consume information in theory the same way that the human brain does it okay? So in other words, it's not limited to Wes typing in the commands that it needs, okay? It is not limited to the idea of a particular code that's actually there. It can actually take images, it can actually hear speech patterns. It can then find the patterns that somebody's actually reusing over and over again and then be able to actually say, hey, this sounds like you're trying to describe this and gives you some output, right? Give you some insight into their thinking. You don't know it but if you're using Amazon and now all of a sudden you go and look up a few different things and now the next time you log in you're like, oh look at what they're recommending for me to, well, Amazon's using some type of artificial intelligence because they've now comprehended that Ronnie has been looking at looking for something like this, or Wes has been looking for something like this and then continue on to actually say this because he's spent five minutes on it, say it seems like it's really interesting, so let me move that up in a list of, you know, of other things to be able to put that into place in others, produce insights that may be helpful for me purchasing something in the near future. So it essentially, that's what AI does for us. And we take that million sensor idea, right? We're trying to produce and figure out like what the fuel efficiency is of those trucks or anything like that, or the patterns that are actually moving or are they missing a particular toll booth, you know, that they're going through whatever it might be. The problem is there's so much data it's very difficult for a single programmer to try and write all that. So what they can do is use AI to figure out what those patterns are to produce insights for us that then can be acted on and the acting of that, in other words, the action of that now says take that information that you get from what the AI can develop and apply machine learning to it. Machine learning then can take those insights that we have and make decisions for us to do some type of forecasting we want to in terms of outcomes or behaviors or trends or whatever it might be. But here is the key, Wes. We are not programming them to do it. Okay? So machine learning says, let me take that information and let me run through all the possibility and trends here that we can actually run through and then produce some type of action of, or some type of future prediction based off this. It doesn't mean it's going to be right, it's going to give you a percentage of how right it believes it's going to be, but overall though, that's what machine learning does for us. And I know this sounds a little bit silly, but this past weekend a tennis tournament the Wimbledon was on and they talked about this process working in the background, how they can actually show the spread and the pattern of things like their tennis serves and where they actually ended up hitting all over that court because there's like a 128 cameras around along with like, I dunno, 600 plus sensors that are around. They're taking all that and then based off a single serve, they can actually tell how fast a ball is spinning, how fast it actually moves across the net. And then they produce some insight of this is how he's going to win the point, when giving all those statistics here, all that's based on AI, and then of course, well the idea of machine learnings to produce some type of prediction that's going to end up happening. Well why do we need this? Because data is becoming so much more today, Wes, okay? The very fact is I might be able to handle four pieces of information. The amount of data that we get in five minutes now on the internet is insane. So it actually can overwhelm the human mind. Whereas these based on, you know, well computers, right, they can actually handle a lot more of it, given the idea of human intelligence like features in terms of ai, they can also produce patterns like that as well. So that's the overall goal when we start talking about this stuff, and that is emerging in every technology that's out there in the cloud today. Everybody uses it because it actually is so helpful. You get ran across a bot when you go to a website. That's an AI type of feature that you're actually talking about there and it can continue to actually learn and do those things. So Wes, these types of technologies, they're not only not going away anytime soon, they're becoming more and more of them. So these are just a big three that were at least called out on the CompTIA objectives, but there's probably thousands more that are out in the other. But these are the three that we're focusing on. - All right, there you have it ladies and gentlemen, the emerging technologies and some more of the advanced things that we can do with cloud-based technology. So that's all the time we have for this episode, but we got a lot more to come in the CompTIA Cloud Plus adventure. So stay tuned. - [Narrator] Thank you for watching IT Pro TV.