1 00:00:04,120 --> 00:00:07,160 Speaker 1: Get in touch with technology with tech Stuff from how 2 00:00:07,200 --> 00:00:14,000 Speaker 1: stuff Works dot com. Hey there, and welcome to tech Stuff. 3 00:00:14,000 --> 00:00:17,520 Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with 4 00:00:17,680 --> 00:00:19,640 Speaker 1: How Stuff Works and I heart radio and a love 5 00:00:19,680 --> 00:00:22,920 Speaker 1: of all things tech, and I am at the IBM 6 00:00:23,040 --> 00:00:27,320 Speaker 1: Think two thousand nineteen conference in San Francisco, California. So 7 00:00:27,520 --> 00:00:30,080 Speaker 1: if the audio sounds a little odd, is because we're 8 00:00:30,120 --> 00:00:35,120 Speaker 1: recording this from my hotel room in rainy San Francisco. 9 00:00:35,200 --> 00:00:37,520 Speaker 1: IBM invited me out here to get a good look 10 00:00:37,560 --> 00:00:39,880 Speaker 1: at the technologies the company has been working on to 11 00:00:40,080 --> 00:00:43,120 Speaker 1: transform the back end of businesses around the world in 12 00:00:43,159 --> 00:00:46,920 Speaker 1: an effort to make those businesses more effective and more powerful. 13 00:00:47,320 --> 00:00:49,960 Speaker 1: And I'm sharing what I found while I was at 14 00:00:50,040 --> 00:00:53,320 Speaker 1: that conference, and in this episode, I'm going to talk 15 00:00:53,360 --> 00:00:57,400 Speaker 1: about cloud computing, which is fitting because of the reigning 16 00:00:57,400 --> 00:01:00,560 Speaker 1: of cats and dogs in San Francisco with in gusts 17 00:01:00,600 --> 00:01:02,920 Speaker 1: of more than forty miles per hour, so it's a 18 00:01:02,920 --> 00:01:07,120 Speaker 1: pretty blustery day for cloud computing. Before I jump into 19 00:01:07,160 --> 00:01:10,200 Speaker 1: what IBM is talking about specifically, I figure it's a 20 00:01:10,240 --> 00:01:13,440 Speaker 1: good idea to do a rundown of what cloud computing is, 21 00:01:13,840 --> 00:01:17,680 Speaker 1: just as a reminder, cloud computing is sort of like 22 00:01:17,880 --> 00:01:21,120 Speaker 1: computing on demand. It's being able to take advantage of 23 00:01:21,160 --> 00:01:25,800 Speaker 1: powerful computers and massive storage over a network connection. Typically, 24 00:01:25,840 --> 00:01:28,360 Speaker 1: the computers that are actually doing all the work are 25 00:01:28,400 --> 00:01:32,360 Speaker 1: in a data center, possibly miles or even countries away. 26 00:01:32,840 --> 00:01:36,200 Speaker 1: The user, whether it's a big company or an average individual, 27 00:01:36,480 --> 00:01:39,160 Speaker 1: interacts with this through some sort of interface. When you 28 00:01:39,240 --> 00:01:43,360 Speaker 1: run an application, that application isn't actually running on your device, 29 00:01:43,400 --> 00:01:47,080 Speaker 1: at least not completely, but rather is running on a 30 00:01:47,120 --> 00:01:50,200 Speaker 1: computer in that cloud system and returning the results to you. 31 00:01:50,960 --> 00:01:53,080 Speaker 1: And it helps to have an example, So I'm going 32 00:01:53,120 --> 00:01:55,400 Speaker 1: to use one that I think helps illustrate what is 33 00:01:55,440 --> 00:01:58,760 Speaker 1: going on and the challenges that are involved with cloud computing. 34 00:01:59,240 --> 00:02:01,880 Speaker 1: Let's take the example of an m m O RPG, 35 00:02:02,240 --> 00:02:06,360 Speaker 1: or a massively multiplayer online role playing game. These are 36 00:02:06,400 --> 00:02:09,440 Speaker 1: games in which you use the game's interface to log 37 00:02:09,480 --> 00:02:12,480 Speaker 1: into a server and connect with the game world before 38 00:02:12,520 --> 00:02:17,040 Speaker 1: you go on your merry way smashing or faces or whatever. 39 00:02:17,080 --> 00:02:20,840 Speaker 1: You're doing your online with hundreds or maybe even thousands 40 00:02:20,960 --> 00:02:24,440 Speaker 1: of other people who are doing similar things and smashing 41 00:02:24,520 --> 00:02:27,360 Speaker 1: orc faces. You can interact with those people. Maybe you 42 00:02:27,400 --> 00:02:30,200 Speaker 1: work with them, maybe you work against them, maybe you 43 00:02:30,280 --> 00:02:33,040 Speaker 1: just bust out some sweet dance moves while you wait 44 00:02:33,080 --> 00:02:36,320 Speaker 1: for a quest to populate. But clearly, all these other 45 00:02:36,360 --> 00:02:40,080 Speaker 1: people aren't on your computer. They're not connecting directly to 46 00:02:40,200 --> 00:02:44,280 Speaker 1: your PC. They're playing the game and controlling characters. But 47 00:02:44,320 --> 00:02:47,560 Speaker 1: those commands couldn't possibly be coming through onto your machine 48 00:02:47,639 --> 00:02:51,720 Speaker 1: unless you're running the world's most powerful supercomputer, because otherwise 49 00:02:51,720 --> 00:02:53,720 Speaker 1: you're gaming rig would just give up if it had 50 00:02:53,760 --> 00:02:57,919 Speaker 1: to handle all of that processing instead. The game running 51 00:02:57,919 --> 00:03:00,320 Speaker 1: on your computer is kind of like a poor role 52 00:03:00,400 --> 00:03:04,320 Speaker 1: into an instance being run on some other machine, specifically 53 00:03:04,720 --> 00:03:07,240 Speaker 1: the server you logged into at the beginning of the game. 54 00:03:07,600 --> 00:03:10,480 Speaker 1: Other players are also logged into the server, and the 55 00:03:10,520 --> 00:03:13,720 Speaker 1: server is keeping track of where everyone is in relation 56 00:03:13,760 --> 00:03:16,840 Speaker 1: to the game world and in relation to other players. 57 00:03:17,360 --> 00:03:20,519 Speaker 1: The server is processing the command streams from each player, 58 00:03:20,560 --> 00:03:23,760 Speaker 1: whether it's a command to get to work, face smashing 59 00:03:24,120 --> 00:03:27,680 Speaker 1: or to do the moonwalk. It's relaying all those commands 60 00:03:27,720 --> 00:03:31,280 Speaker 1: out to the respective client computers so that everyone sees 61 00:03:31,320 --> 00:03:35,600 Speaker 1: the correct respective reactions in the game world. The game 62 00:03:35,600 --> 00:03:38,920 Speaker 1: itself is running in the cloud. Your computer is still 63 00:03:39,000 --> 00:03:43,080 Speaker 1: running some processes to like rendering graphics, for example, but 64 00:03:43,280 --> 00:03:46,480 Speaker 1: much of the rest is offloaded to the distant computer, 65 00:03:46,800 --> 00:03:49,280 Speaker 1: and you can easily imagine some of the challenges that 66 00:03:49,360 --> 00:03:52,520 Speaker 1: come along with this, such as latency. That's the delay 67 00:03:52,640 --> 00:03:55,520 Speaker 1: between when you send the command and when you see 68 00:03:55,520 --> 00:03:59,760 Speaker 1: it executed on screen. Well, latency goes well beyond just gaming. 69 00:03:59,840 --> 00:04:03,360 Speaker 1: It can be in any kind of application. However, that's 70 00:04:03,400 --> 00:04:06,080 Speaker 1: just one challenge. There are a lot more than just that, 71 00:04:06,280 --> 00:04:09,880 Speaker 1: and we'll touch on those now. There are different types 72 00:04:10,160 --> 00:04:12,960 Speaker 1: of cloud computing, and you'll typically hear about it in 73 00:04:13,080 --> 00:04:17,240 Speaker 1: terms of public cloud versus private cloud, and then there's 74 00:04:17,279 --> 00:04:20,880 Speaker 1: the hybrid cloud. So what the heck is the difference. Well, 75 00:04:20,960 --> 00:04:23,880 Speaker 1: let's start with the simplest first. A public cloud is 76 00:04:23,920 --> 00:04:27,520 Speaker 1: a system in which a third party provider is responsible 77 00:04:27,520 --> 00:04:30,640 Speaker 1: for the data centers that you use. You're using someone 78 00:04:30,760 --> 00:04:35,120 Speaker 1: else's computers. In other words, IBM does this, as does Google, 79 00:04:35,400 --> 00:04:39,400 Speaker 1: Amazon and lots of others. Typically, this is a paper 80 00:04:39,520 --> 00:04:42,600 Speaker 1: use model of cloud computing, and that clients pay the 81 00:04:42,640 --> 00:04:47,279 Speaker 1: providers for the use of those computing and storage services. However, 82 00:04:47,480 --> 00:04:50,320 Speaker 1: it also means that the client gives up some of 83 00:04:50,360 --> 00:04:53,640 Speaker 1: that data management to the provider, and there is a 84 00:04:53,640 --> 00:04:56,920 Speaker 1: real concern about data security. The idea that if the 85 00:04:57,000 --> 00:05:00,200 Speaker 1: data isn't under your constant control. There's a day jew 86 00:05:00,279 --> 00:05:02,360 Speaker 1: that could get away from you. Whether or not that 87 00:05:02,400 --> 00:05:06,240 Speaker 1: fear is justified as dependent upon the provider obviously, but 88 00:05:06,360 --> 00:05:10,320 Speaker 1: it's always there. A private cloud is typically defined as 89 00:05:10,320 --> 00:05:13,760 Speaker 1: when a company uses its own data centers and manages 90 00:05:13,800 --> 00:05:16,520 Speaker 1: them to behave the same way a public cloud would, 91 00:05:16,960 --> 00:05:21,360 Speaker 1: but typically there's some added security features, added privacy features. 92 00:05:21,560 --> 00:05:24,159 Speaker 1: They might be working with a third party provider for 93 00:05:24,240 --> 00:05:28,640 Speaker 1: the private cloud software, but they get to maintain the 94 00:05:28,640 --> 00:05:32,279 Speaker 1: whole thing themselves. While private clouds can be hosted on 95 00:05:32,520 --> 00:05:35,560 Speaker 1: site at headquarters, it's also possible to have a private 96 00:05:35,600 --> 00:05:40,200 Speaker 1: hosting environment within a larger cloud provider. In theory, it 97 00:05:40,240 --> 00:05:43,960 Speaker 1: would behave like a public cloud to everyone else. The 98 00:05:44,040 --> 00:05:46,920 Speaker 1: cost for a private cloud approach tends to be a 99 00:05:46,960 --> 00:05:50,560 Speaker 1: flat feed based on the capacity required, and so it 100 00:05:50,680 --> 00:05:54,800 Speaker 1: is a predictable, consistent cost as opposed to the on demand, 101 00:05:54,920 --> 00:05:58,680 Speaker 1: dynamic version with public clouds. A private cloud has its 102 00:05:58,680 --> 00:06:02,880 Speaker 1: own challenges. One, the company owning the private cloud has 103 00:06:02,920 --> 00:06:07,560 Speaker 1: to continually invest in it. It costs money to maintain, manage, 104 00:06:07,600 --> 00:06:10,719 Speaker 1: and operate the cloud. Over time, it becomes necessary to 105 00:06:10,760 --> 00:06:14,120 Speaker 1: replace older computers, and you have to carefully manage the 106 00:06:14,160 --> 00:06:18,159 Speaker 1: information to transfer it over to new systems. Many companies 107 00:06:18,480 --> 00:06:22,320 Speaker 1: use both public and private clouds. Some information may be 108 00:06:22,520 --> 00:06:25,880 Speaker 1: so important, whether because it's mission critical information, or it 109 00:06:25,920 --> 00:06:29,400 Speaker 1: represents personal data of customers, or both that moving to 110 00:06:29,440 --> 00:06:32,520 Speaker 1: a pure public cloud approach is not practical or logical. 111 00:06:33,240 --> 00:06:36,680 Speaker 1: Of course, it's not really that clear cut. It gets 112 00:06:36,880 --> 00:06:40,520 Speaker 1: way messier than that. For one thing, Larger companies rarely 113 00:06:40,560 --> 00:06:43,560 Speaker 1: rely on just one type of cloud computing or storage, 114 00:06:43,960 --> 00:06:46,960 Speaker 1: which leads us to what is called the hybrid cloud. 115 00:06:47,480 --> 00:06:50,960 Speaker 1: I wasn't quite sure what a hybrid cloud really was 116 00:06:51,120 --> 00:06:54,080 Speaker 1: when I was on my way to think two thousand nineteen, 117 00:06:54,160 --> 00:06:57,279 Speaker 1: but fortunately I had a chance to speak with Hillary Hunter, 118 00:06:57,600 --> 00:06:59,880 Speaker 1: an IBM Fellow, which by the way, is the high 119 00:07:00,240 --> 00:07:03,839 Speaker 1: honor IBM grants to top researchers, scientists, engineers, and like. 120 00:07:04,279 --> 00:07:07,120 Speaker 1: And she's also the chief Technology Officer and VP of 121 00:07:07,160 --> 00:07:10,920 Speaker 1: cloud computing and hybrid cloud. I figured if anyone had 122 00:07:10,920 --> 00:07:13,600 Speaker 1: a great definition for hybrid cloud, it would be her. 123 00:07:14,080 --> 00:07:17,120 Speaker 1: Here's what she had to say. I'm here with Hillary 124 00:07:17,200 --> 00:07:22,800 Speaker 1: Hunter and IBM fellow, chief Technology officer expert in all 125 00:07:23,000 --> 00:07:25,360 Speaker 1: things cloud. You were the person I needed to go 126 00:07:25,440 --> 00:07:29,080 Speaker 1: to to ask a very important question. Now, my listeners 127 00:07:29,320 --> 00:07:33,520 Speaker 1: are the general public, and we're just now seeing kind 128 00:07:33,520 --> 00:07:37,760 Speaker 1: of a mainstream understanding of the general concept of cloud computing, 129 00:07:38,160 --> 00:07:40,760 Speaker 1: and then we have to go and complicate matters with 130 00:07:40,840 --> 00:07:44,120 Speaker 1: hybrid cloud. So could you please explain to me what 131 00:07:44,280 --> 00:07:48,520 Speaker 1: the hybrid cloud actually means. Yeah, So, people tend to 132 00:07:48,560 --> 00:07:51,400 Speaker 1: think about the cloud is the place that they store 133 00:07:51,400 --> 00:07:54,800 Speaker 1: their documents or store their pictures. From a consumer perspective 134 00:07:54,840 --> 00:07:58,760 Speaker 1: of your general audience, UM, the cloud is certainly a place, 135 00:07:58,960 --> 00:08:00,480 Speaker 1: you know, with a lot of compute orders in it 136 00:08:00,520 --> 00:08:03,320 Speaker 1: and a lot of storage capacity UM. But from a 137 00:08:03,360 --> 00:08:07,200 Speaker 1: business perspective, from an enterprise perspective, it's also a way 138 00:08:07,200 --> 00:08:10,760 Speaker 1: of doing your software, way of doing your computing UM. 139 00:08:10,800 --> 00:08:13,320 Speaker 1: And when we talk about hybrid cloud, what we're doing 140 00:08:13,440 --> 00:08:16,320 Speaker 1: is taking those capabilities that we refer to as cloud 141 00:08:16,400 --> 00:08:20,840 Speaker 1: native function UM specific software. You'll hear the terms kubernet 142 00:08:20,840 --> 00:08:23,240 Speaker 1: Ease and Docker and other things like that. Those are 143 00:08:23,320 --> 00:08:26,600 Speaker 1: kind of the software pieces that define what it means 144 00:08:26,640 --> 00:08:29,640 Speaker 1: to be using a cloud UM, and with hybrid cloud, 145 00:08:29,640 --> 00:08:32,840 Speaker 1: we're taking that and enabling people to also use that 146 00:08:32,920 --> 00:08:37,320 Speaker 1: same software, that same computing method and capability on their 147 00:08:37,320 --> 00:08:41,800 Speaker 1: premises as well, and so rather than having a traditional 148 00:08:41,840 --> 00:08:44,720 Speaker 1: type of a computer system UM that works in a 149 00:08:44,760 --> 00:08:47,000 Speaker 1: certain way with a certain set of software, you can 150 00:08:47,040 --> 00:08:49,839 Speaker 1: take those same computers or by new computers UM and 151 00:08:50,040 --> 00:08:52,760 Speaker 1: use Docker and kubernet Ees and these other things that 152 00:08:53,360 --> 00:08:56,160 Speaker 1: UM constitute cloud native software programming. And you can use 153 00:08:56,240 --> 00:08:59,600 Speaker 1: that where you are where you're doing business. UM. You know, 154 00:08:59,640 --> 00:09:03,000 Speaker 1: in your storageing and factoring sites. UM. You can use 155 00:09:03,000 --> 00:09:05,520 Speaker 1: that in your traditional enterprise data centers that you're using 156 00:09:05,559 --> 00:09:09,120 Speaker 1: to run your financial operations or other things like that. UM. 157 00:09:09,160 --> 00:09:12,000 Speaker 1: And so you can do your processing of credit card 158 00:09:12,000 --> 00:09:16,280 Speaker 1: transactions UM you know very you know, securely and in 159 00:09:16,320 --> 00:09:18,360 Speaker 1: the location that you want to do it UM, but 160 00:09:18,679 --> 00:09:22,520 Speaker 1: using cloud type of software UM. So hybrid cloud UM 161 00:09:22,600 --> 00:09:25,839 Speaker 1: just refers to using both public clouds, which consumers are 162 00:09:25,880 --> 00:09:29,120 Speaker 1: more familiar with because of their music and their files 163 00:09:29,160 --> 00:09:31,839 Speaker 1: and their pictures and stuff, UM, but also being able 164 00:09:31,880 --> 00:09:35,600 Speaker 1: to use that same underline software that's driving cloud technology 165 00:09:35,800 --> 00:09:38,640 Speaker 1: at your place of business. And obviously that would be 166 00:09:38,800 --> 00:09:45,239 Speaker 1: helpful if you are working with extremely mission critical information, 167 00:09:45,440 --> 00:09:50,960 Speaker 1: or maybe it's the private information of individuals, maybe it's 168 00:09:51,000 --> 00:09:53,880 Speaker 1: a g d p R concerned. It's these sort of 169 00:09:53,920 --> 00:09:56,760 Speaker 1: things that people have to take into account that you 170 00:09:56,840 --> 00:10:01,200 Speaker 1: might not want that data on a third party public cloud. 171 00:10:01,320 --> 00:10:03,200 Speaker 1: Is that correct? Yeah, so that's a good way to 172 00:10:03,240 --> 00:10:05,880 Speaker 1: think about it. There are many reasons, UM, It's not 173 00:10:06,040 --> 00:10:09,320 Speaker 1: just one reason why someone might have a private cloud 174 00:10:09,760 --> 00:10:13,760 Speaker 1: UM and hybrid is that combination of public and private clouds. UM. 175 00:10:14,080 --> 00:10:17,080 Speaker 1: Some of the reasons you mentioned related to data policies. 176 00:10:17,160 --> 00:10:20,520 Speaker 1: Certain countries want certain types of data UM in order 177 00:10:20,600 --> 00:10:25,040 Speaker 1: to protect consumers in particular kept within their countries. UM. 178 00:10:25,080 --> 00:10:27,280 Speaker 1: So some companies will choose to use a public cloud 179 00:10:27,280 --> 00:10:29,960 Speaker 1: provider in their country, or they'll choose to then implement 180 00:10:30,000 --> 00:10:32,600 Speaker 1: their I T implement their software UM in their own 181 00:10:32,679 --> 00:10:34,679 Speaker 1: data center in a cloud way so that that data 182 00:10:34,880 --> 00:10:37,320 Speaker 1: stays within you know, what the government has defined as 183 00:10:37,360 --> 00:10:40,040 Speaker 1: the boundaries. Other things have to do with you know, 184 00:10:40,120 --> 00:10:43,720 Speaker 1: just the process of updating and upgrading what you're doing right, 185 00:10:43,800 --> 00:10:46,480 Speaker 1: so you know, you can take an existing server that 186 00:10:46,520 --> 00:10:49,760 Speaker 1: you already own and you can put UM private cloud 187 00:10:49,760 --> 00:10:54,679 Speaker 1: software on it also and start to create new capabilities 188 00:10:54,720 --> 00:10:57,400 Speaker 1: related to you know, AI or data processing and other 189 00:10:57,480 --> 00:11:00,840 Speaker 1: things like that and mix and intermingled with your existing 190 00:11:00,880 --> 00:11:04,080 Speaker 1: business function. So there's a lot of reasons why people 191 00:11:04,240 --> 00:11:08,359 Speaker 1: end up using private cloud technology. Some of it is geographic, 192 00:11:08,440 --> 00:11:10,960 Speaker 1: some of it's you know, data is concerned. Certainly though 193 00:11:10,960 --> 00:11:13,600 Speaker 1: it's possible in a public cloud to set up very 194 00:11:13,640 --> 00:11:17,080 Speaker 1: secure environments, and so sometimes what people do actually is 195 00:11:17,120 --> 00:11:20,319 Speaker 1: make their own private cloud inside of a public cloud. UM. 196 00:11:20,360 --> 00:11:22,240 Speaker 1: And so that's kind of where this whole story tends 197 00:11:22,240 --> 00:11:25,520 Speaker 1: to get a little complicated and technical. UM. But you know, 198 00:11:25,640 --> 00:11:29,520 Speaker 1: it's not necessarily only security UM. It can be lots 199 00:11:29,520 --> 00:11:31,760 Speaker 1: of policy things are just you know, the computers that 200 00:11:31,800 --> 00:11:34,400 Speaker 1: people already own and moving that forward into a more 201 00:11:34,440 --> 00:11:39,360 Speaker 1: modern software construct. Now you've mentioned security, and you've mentioned 202 00:11:39,440 --> 00:11:43,640 Speaker 1: the complex nature of this this uh, this new landscape 203 00:11:43,720 --> 00:11:46,840 Speaker 1: that we're looking at. I imagine those present certain challenges 204 00:11:46,880 --> 00:11:52,439 Speaker 1: when you're talking about managing the data across these different clouds, 205 00:11:52,440 --> 00:11:55,240 Speaker 1: and perhaps you have an application that needs to pull 206 00:11:55,440 --> 00:12:00,560 Speaker 1: from different clusters and different clouds. So from I understand, 207 00:12:00,600 --> 00:12:04,200 Speaker 1: that's one of those big areas of development at IBM. 208 00:12:04,280 --> 00:12:07,720 Speaker 1: Is that correct? Absolutely? Yeah. So when we're talking about 209 00:12:07,800 --> 00:12:12,040 Speaker 1: cloud based UM workloads, cloud Blace deployment, I kept coming 210 00:12:12,120 --> 00:12:14,320 Speaker 1: back to, you know, what the software side of cloud 211 00:12:14,360 --> 00:12:17,440 Speaker 1: is in addition to kind of the hardware and storage. UM. 212 00:12:17,520 --> 00:12:21,000 Speaker 1: What we're talking about is the ability to quickly create 213 00:12:21,120 --> 00:12:24,200 Speaker 1: function and then deploy that function where you need to 214 00:12:24,240 --> 00:12:27,400 Speaker 1: have it deployed UM to update it in response to 215 00:12:27,600 --> 00:12:31,160 Speaker 1: changes in your business or changes in the software capability UM, 216 00:12:31,240 --> 00:12:35,800 Speaker 1: changes in compliance, changes in regulations UM. So cloud also 217 00:12:35,920 --> 00:12:38,520 Speaker 1: enables you to create function and push it out to 218 00:12:38,760 --> 00:12:43,000 Speaker 1: these different locations UM. And one of the challenges that 219 00:12:43,000 --> 00:12:47,360 Speaker 1: that introduces is how do I then manage multiple clouds? 220 00:12:47,920 --> 00:12:51,240 Speaker 1: How do I know what software is running where? UM? 221 00:12:51,520 --> 00:12:53,960 Speaker 1: Am I spending the amount that I want to spend 222 00:12:54,040 --> 00:12:57,800 Speaker 1: in a certain cloud? UM? Is everything been patched and 223 00:12:57,880 --> 00:13:01,200 Speaker 1: updated according to the latest vulnerabilit ease or according to 224 00:13:01,240 --> 00:13:05,520 Speaker 1: my latest capabilities UM, the latest AI technologies, whatever it 225 00:13:05,600 --> 00:13:08,360 Speaker 1: is that I want to deploy. So we have something 226 00:13:08,400 --> 00:13:11,280 Speaker 1: that we call Multi Cloud Manager UM and i'd be 227 00:13:11,280 --> 00:13:15,079 Speaker 1: as Multi Cloud Manager enables a single dashboard across these 228 00:13:15,120 --> 00:13:18,760 Speaker 1: different clouds, so you can see what's going on, you 229 00:13:18,800 --> 00:13:21,840 Speaker 1: can set policies, you can ensure that you're meeting you know, 230 00:13:21,920 --> 00:13:25,960 Speaker 1: compliance and other constraints UM. And that really then helps 231 00:13:26,000 --> 00:13:29,080 Speaker 1: simplify the fact that the world really is hybrid. It 232 00:13:29,200 --> 00:13:32,240 Speaker 1: isn't just one public cloud sitting somewhere that everyone is 233 00:13:32,360 --> 00:13:36,560 Speaker 1: using people are adopting private cloud because of you know, 234 00:13:36,600 --> 00:13:41,079 Speaker 1: the software advantages, the agility, the new capabilities that that brings. 235 00:13:41,120 --> 00:13:44,520 Speaker 1: So that is the reality. The world is hybrid, and 236 00:13:44,600 --> 00:13:48,600 Speaker 1: so once it's hybrid, we want to simplify the visibility 237 00:13:48,600 --> 00:13:51,320 Speaker 1: to what's going on and simplify the complexity and the 238 00:13:51,360 --> 00:13:54,920 Speaker 1: control of what's going on in this in this hybrid 239 00:13:54,960 --> 00:13:58,680 Speaker 1: cloud era. Gosh, well, Hillary Hunter, I am so thankful 240 00:13:58,840 --> 00:14:00,680 Speaker 1: that I got a chance to speak with you. You've 241 00:14:00,679 --> 00:14:04,120 Speaker 1: really helped clear things up. This was an area that 242 00:14:04,480 --> 00:14:08,160 Speaker 1: I'm very familiar with cloud computing in general, but the 243 00:14:08,240 --> 00:14:10,920 Speaker 1: more I was getting into this new world, and I 244 00:14:10,920 --> 00:14:12,920 Speaker 1: believe this might have been the first time this conference 245 00:14:13,120 --> 00:14:15,120 Speaker 1: the first time I heard the term Kubernetes, and I 246 00:14:15,120 --> 00:14:18,040 Speaker 1: went on a deep rabbit hole around that to get 247 00:14:18,040 --> 00:14:20,920 Speaker 1: an understanding. I feel like I've got a much better 248 00:14:20,960 --> 00:14:23,960 Speaker 1: grasp of that. So thank you so much, absolutely, And 249 00:14:24,000 --> 00:14:27,600 Speaker 1: if you want any more. Description of kubernet is, the 250 00:14:27,640 --> 00:14:29,640 Speaker 1: way I like to think about it is it's sort 251 00:14:29,640 --> 00:14:32,800 Speaker 1: of the orchestra conductor. Right. So those two words we 252 00:14:32,800 --> 00:14:36,040 Speaker 1: were talking about before and in containers and Kubernetes, we 253 00:14:36,040 --> 00:14:39,320 Speaker 1: call kubernet is actually orchestration software for a good reason, 254 00:14:39,360 --> 00:14:42,280 Speaker 1: and that you know, you've got all this stuff and containers, 255 00:14:42,320 --> 00:14:46,080 Speaker 1: that's your cloud workload, and someone's got to coordinate running it, 256 00:14:46,120 --> 00:14:47,920 Speaker 1: and how much of it runs, and kind of how 257 00:14:47,920 --> 00:14:51,200 Speaker 1: loud and quiet it is. And so the orchestra conductor 258 00:14:51,280 --> 00:14:55,400 Speaker 1: is a useful analogy. So Kuberneti is that orchestration orchestration 259 00:14:55,440 --> 00:14:59,120 Speaker 1: layer for the cloud. Fantastic, My listeners know, there's very 260 00:14:59,160 --> 00:15:02,040 Speaker 1: little I love are than an analogy except maybe a pun. 261 00:15:02,200 --> 00:15:04,840 Speaker 1: So I think that's the perfect way to end this interview. 262 00:15:04,840 --> 00:15:07,600 Speaker 1: Thank you so much, thanks for having me pleasure being here. 263 00:15:08,440 --> 00:15:12,360 Speaker 1: This gets more critical the more highly regulated and industry is. 264 00:15:12,560 --> 00:15:15,800 Speaker 1: According to IBM, the average large corporation has about sixty 265 00:15:16,160 --> 00:15:19,160 Speaker 1: of its data in the public cloud and in the 266 00:15:19,200 --> 00:15:22,760 Speaker 1: private cloud, but for more heavily regulated companies, the opposite 267 00:15:22,840 --> 00:15:26,160 Speaker 1: tends to be true. Private clouds might hold six of 268 00:15:26,200 --> 00:15:30,360 Speaker 1: their data and public clouds, So the more regulated the industry, 269 00:15:30,520 --> 00:15:33,400 Speaker 1: the more data ends up in private clouds. For companies 270 00:15:33,440 --> 00:15:36,120 Speaker 1: operating in the European Union, which recently put the g 271 00:15:36,200 --> 00:15:38,600 Speaker 1: d p R rules in place, these sorts of concerns 272 00:15:38,600 --> 00:15:42,440 Speaker 1: are absolutely critical, as violating GDPR rules results in stiff 273 00:15:42,440 --> 00:15:46,680 Speaker 1: financial penalties and restrictions. One other term we should define 274 00:15:47,040 --> 00:15:50,200 Speaker 1: is the edge, not the guy from you too, I'm 275 00:15:50,200 --> 00:15:54,200 Speaker 1: talking about edge computing. This is a somewhat vague term 276 00:15:54,320 --> 00:15:56,800 Speaker 1: and that it can mean different things to different people, 277 00:15:57,080 --> 00:16:00,680 Speaker 1: but in general, the edge is defined as being geographically 278 00:16:00,800 --> 00:16:04,200 Speaker 1: close to the request or the source of data. See. 279 00:16:04,240 --> 00:16:07,800 Speaker 1: Cloud computing has a big limitation, and that is the 280 00:16:07,840 --> 00:16:11,640 Speaker 1: speed of light. That's the fastest anything can go. And 281 00:16:11,680 --> 00:16:15,239 Speaker 1: if you're dependent upon a centralized data center that's hundreds 282 00:16:15,320 --> 00:16:18,560 Speaker 1: or thousands of miles away, your request has to travel 283 00:16:18,680 --> 00:16:20,920 Speaker 1: all the way there, and then the response has to 284 00:16:20,960 --> 00:16:23,760 Speaker 1: travel all the way back, and that can come across 285 00:16:23,920 --> 00:16:28,520 Speaker 1: as latency. Edge computing means building in some computational power 286 00:16:28,680 --> 00:16:31,560 Speaker 1: or features into the devices that connect users to the 287 00:16:31,560 --> 00:16:34,640 Speaker 1: cloud itself. In other words, some of the work gets 288 00:16:34,680 --> 00:16:37,960 Speaker 1: done on the mobile device or the computer or personal 289 00:16:38,000 --> 00:16:41,440 Speaker 1: voice assistant or whatever you're using, as opposed to the 290 00:16:41,480 --> 00:16:44,120 Speaker 1: model where everything just gets sent up to the cloud, 291 00:16:44,280 --> 00:16:47,160 Speaker 1: process there and then sent back again. In our m 292 00:16:47,320 --> 00:16:50,600 Speaker 1: M O RPG example, the graphics rendering may be done 293 00:16:50,640 --> 00:16:54,280 Speaker 1: at the edge on the gamer's own computer. Next, I'm 294 00:16:54,280 --> 00:16:57,000 Speaker 1: going to cover something that was a total enigma to 295 00:16:57,080 --> 00:17:01,480 Speaker 1: me heading into Think two thousand nineteen, which would kubernettes. 296 00:17:02,120 --> 00:17:13,439 Speaker 1: But first, let's take a quick break, all right, I 297 00:17:13,520 --> 00:17:17,760 Speaker 1: need to talk about Kubernetes, and Hillary mentioned this briefly 298 00:17:17,880 --> 00:17:20,879 Speaker 1: in our conversation, but I really wanted to kind of 299 00:17:20,920 --> 00:17:23,600 Speaker 1: get down to it. Those developers out there in the 300 00:17:23,600 --> 00:17:26,159 Speaker 1: audience likely already know what I'm talking about, but I 301 00:17:26,160 --> 00:17:28,479 Speaker 1: gotta be honest with you, guys. I don't think I 302 00:17:28,480 --> 00:17:32,480 Speaker 1: had ever encountered the term before going to Think two 303 00:17:32,480 --> 00:17:35,439 Speaker 1: thousand nineteen, and it took a lot of smiling and 304 00:17:35,480 --> 00:17:37,720 Speaker 1: nodding to cover up the fact that I was frantically 305 00:17:37,800 --> 00:17:41,080 Speaker 1: googling what the heck it was? So, what the heck 306 00:17:41,200 --> 00:17:45,439 Speaker 1: is it? And why is it important? First to understand Kubernetes, 307 00:17:45,520 --> 00:17:47,480 Speaker 1: we actually have to take a step back and talk 308 00:17:47,520 --> 00:17:51,280 Speaker 1: about a concept called virtual machines. Then work our way 309 00:17:51,359 --> 00:17:54,440 Speaker 1: up to containers and stick with me. For though they're 310 00:17:54,440 --> 00:17:57,639 Speaker 1: being madness, yet there is method in it. So a 311 00:17:57,720 --> 00:17:59,920 Speaker 1: virtual machine is kind of what it sounds like. It's 312 00:18:00,000 --> 00:18:04,520 Speaker 1: a simulated, emulated, or otherwise virtual representation of a computer. 313 00:18:05,200 --> 00:18:07,720 Speaker 1: You might create a virtual machine in order to run 314 00:18:07,800 --> 00:18:11,960 Speaker 1: specific software. For example, let's say it's a personal computer, approach. 315 00:18:12,040 --> 00:18:14,560 Speaker 1: You have a Mac computer and you want to run 316 00:18:15,440 --> 00:18:19,040 Speaker 1: virtual Windows machine on your Mac computer so that you 317 00:18:19,080 --> 00:18:22,880 Speaker 1: can run and access Windows based software, or you might 318 00:18:22,960 --> 00:18:26,679 Speaker 1: want a separate virtual machine to run new applications. The 319 00:18:26,760 --> 00:18:30,480 Speaker 1: virtual machine is sequestered from other parts of the computer, 320 00:18:30,600 --> 00:18:33,040 Speaker 1: so it won't affect the other parts of the computer. 321 00:18:33,119 --> 00:18:36,480 Speaker 1: You have a nice development and test environment within which 322 00:18:36,520 --> 00:18:39,120 Speaker 1: you can build, run and break stuff, and it's not 323 00:18:39,160 --> 00:18:42,720 Speaker 1: going to affect everything else on that physical machine. But 324 00:18:42,880 --> 00:18:46,120 Speaker 1: virtual machines are resource hungry and they're not always practical, 325 00:18:46,480 --> 00:18:51,440 Speaker 1: so there's an alternative called containers. Containers are much more 326 00:18:51,800 --> 00:18:56,680 Speaker 1: light than virtual machines, meaning they require far fewer resources. 327 00:18:56,720 --> 00:19:00,000 Speaker 1: They can sequester features, and because of this, they are 328 00:19:00,080 --> 00:19:04,239 Speaker 1: rate for the rapid development and deployment of applications. An 329 00:19:04,280 --> 00:19:08,679 Speaker 1: application might provide numerous services, and each service or feature 330 00:19:08,800 --> 00:19:12,440 Speaker 1: can live inside a container, so while one team of 331 00:19:12,520 --> 00:19:16,080 Speaker 1: developers is working on their specific service, other teams can 332 00:19:16,119 --> 00:19:20,119 Speaker 1: work independently and each service is inside a different container 333 00:19:20,920 --> 00:19:25,119 Speaker 1: as Docker. A particular flavor of containers defines it quote 334 00:19:25,359 --> 00:19:29,760 Speaker 1: package software into standardized units for development, shipment, and deployment. 335 00:19:29,840 --> 00:19:33,080 Speaker 1: A container is a standard unit of software that packages 336 00:19:33,240 --> 00:19:37,399 Speaker 1: upcode and all its dependencies so the application runs quickly 337 00:19:37,600 --> 00:19:41,800 Speaker 1: and reliably from one computing environment to another. A DOCTOR 338 00:19:41,880 --> 00:19:45,639 Speaker 1: container image is a lightweight, stand alone executable package of 339 00:19:45,720 --> 00:19:50,840 Speaker 1: software that includes everything needed to run an application code, runtime, 340 00:19:51,080 --> 00:19:56,119 Speaker 1: system tools, system libraries, and settings end quote. So developers 341 00:19:56,160 --> 00:20:01,040 Speaker 1: can deploy these containers across different clusters of computers, whether 342 00:20:01,119 --> 00:20:06,040 Speaker 1: they're actual physical computers or virtual machines. The applications depend 343 00:20:06,119 --> 00:20:10,480 Speaker 1: upon the services within these containers to present all the information, 344 00:20:10,560 --> 00:20:13,480 Speaker 1: but to manage that you need some sort of strategy 345 00:20:13,480 --> 00:20:18,080 Speaker 1: to oversee the containers. In general, it's called container orchestration. 346 00:20:18,200 --> 00:20:23,040 Speaker 1: It's all about deploying, managing, scaling, and networking containers and 347 00:20:23,119 --> 00:20:27,000 Speaker 1: container based applications, and that's what will bring us to Kubernetes. 348 00:20:27,760 --> 00:20:32,440 Speaker 1: Kubernetes is a container orchestration open source project. You heard 349 00:20:32,520 --> 00:20:36,040 Speaker 1: Hillary describe it as being an actual sort of orchestra 350 00:20:36,280 --> 00:20:40,800 Speaker 1: conductor as an analogy. It's a system that automates deployment 351 00:20:40,840 --> 00:20:44,680 Speaker 1: and management of multi container applications and can do so 352 00:20:44,800 --> 00:20:48,399 Speaker 1: at scale. The project works with Doctor containers, but also 353 00:20:48,600 --> 00:20:51,560 Speaker 1: any other containers that are based on the Open Container 354 00:20:51,640 --> 00:20:56,040 Speaker 1: Initiative or o c I, which standardizes the container format. 355 00:20:56,560 --> 00:21:00,520 Speaker 1: More importantly for this episode, Kubernetes has effectively become the 356 00:21:00,560 --> 00:21:05,680 Speaker 1: standard for application deployment environments and strategies across numerous clouds, 357 00:21:05,720 --> 00:21:08,600 Speaker 1: and it can scale up or down as demand warrants. 358 00:21:09,400 --> 00:21:13,760 Speaker 1: The architecture of Kubernetes depends upon certain abstractions. At the 359 00:21:13,800 --> 00:21:17,320 Speaker 1: top level of abstraction, you have the Kubernetes clusters. These 360 00:21:17,359 --> 00:21:20,200 Speaker 1: refer to the actual machines or virtual machines in the 361 00:21:20,280 --> 00:21:25,560 Speaker 1: Kubernetes systems and the containers managed by Kubernetes. In those clusters, 362 00:21:25,760 --> 00:21:28,600 Speaker 1: the cluster must have a master which is the command 363 00:21:28,600 --> 00:21:31,520 Speaker 1: and control center for the Kubernetes machines. You can actually 364 00:21:31,520 --> 00:21:34,640 Speaker 1: have multiple machines capable of running Master jobs, but only 365 00:21:34,720 --> 00:21:37,840 Speaker 1: one may be active at any given time. Within a 366 00:21:37,920 --> 00:21:42,040 Speaker 1: cluster are nodes, which represent individual physical machines or virtual machines, 367 00:21:42,080 --> 00:21:45,800 Speaker 1: and within the nodes are pods, the most basic objects 368 00:21:45,800 --> 00:21:49,040 Speaker 1: in Kubernetes. A pod is a single instance of a 369 00:21:49,119 --> 00:21:53,560 Speaker 1: process or instance of an application. The containers themselves exist 370 00:21:53,680 --> 00:21:57,400 Speaker 1: within pods, and a pod may have one or more containers, 371 00:21:57,400 --> 00:21:59,240 Speaker 1: but the pod is really the basic unit. To do 372 00:21:59,280 --> 00:22:03,600 Speaker 1: anything meaning full in Kubernetes itself. Now it gets more technical, 373 00:22:03,840 --> 00:22:05,320 Speaker 1: but I think this is enough for us to get 374 00:22:05,480 --> 00:22:07,840 Speaker 1: understanding of the system and the whole point, like I 375 00:22:07,920 --> 00:22:10,760 Speaker 1: mentioned above, is to have a platform for the deployment 376 00:22:10,760 --> 00:22:14,439 Speaker 1: and maintenance of applications that run multiple services. It's a 377 00:22:14,520 --> 00:22:18,680 Speaker 1: dynamic approach that can scale up or down as demand requires. 378 00:22:19,240 --> 00:22:23,240 Speaker 1: Another thing that Kubernetes introduces is the argument for open source. 379 00:22:23,680 --> 00:22:26,560 Speaker 1: I'll talk more about open source in a related podcast, 380 00:22:26,680 --> 00:22:28,840 Speaker 1: but it's a great time to touch on the idea here. 381 00:22:29,400 --> 00:22:32,560 Speaker 1: Open source is an approach to development that is in 382 00:22:32,760 --> 00:22:36,400 Speaker 1: opposition to the proprietary approach that a lot of companies take, 383 00:22:36,680 --> 00:22:40,000 Speaker 1: and the goal of both strategies is ultimately the same 384 00:22:40,040 --> 00:22:43,359 Speaker 1: to develop technology that hopefully works, but the way it 385 00:22:43,440 --> 00:22:47,359 Speaker 1: happens is very different. With a proprietary approach, everything is 386 00:22:47,400 --> 00:22:50,800 Speaker 1: locked down. A company has dedicated developers and engineers, or 387 00:22:51,000 --> 00:22:54,080 Speaker 1: they've contracted with people who are dedicated to a specific project, 388 00:22:54,560 --> 00:22:58,000 Speaker 1: and those people develop the technology, which is typically patented 389 00:22:58,119 --> 00:23:00,760 Speaker 1: or kept as a trade secret. Now this means that 390 00:23:00,760 --> 00:23:02,919 Speaker 1: if anyone else wants to make use of that technology, 391 00:23:02,960 --> 00:23:05,679 Speaker 1: whether it's hardware or software, they have to license it 392 00:23:05,720 --> 00:23:08,080 Speaker 1: from the entity that created the tech in the first place. 393 00:23:08,359 --> 00:23:10,240 Speaker 1: Or they have to figure out a different way to 394 00:23:10,440 --> 00:23:14,640 Speaker 1: essentially accomplish the same result without copying the original design. 395 00:23:15,440 --> 00:23:18,080 Speaker 1: Apple is an example of this approach. They take the 396 00:23:18,080 --> 00:23:22,240 Speaker 1: proprietary approach almost every single time. The company maintains a 397 00:23:22,320 --> 00:23:25,439 Speaker 1: tight control over its own hardware and software. The company 398 00:23:25,520 --> 00:23:28,080 Speaker 1: is famous for this and doesn't tend to look kindly 399 00:23:28,119 --> 00:23:31,199 Speaker 1: on those who attempt to circumvent the proprietary nature of 400 00:23:31,240 --> 00:23:33,760 Speaker 1: Apple's technology. Now, I don't mean to say this is 401 00:23:33,800 --> 00:23:36,840 Speaker 1: the wrong approach for Apple, or that the proprietary approach 402 00:23:36,920 --> 00:23:40,520 Speaker 1: doesn't have merit. It totally does. Apple wants a specific 403 00:23:40,600 --> 00:23:43,719 Speaker 1: experience with its products. It wants to define that experience, 404 00:23:44,160 --> 00:23:46,600 Speaker 1: and it can only really guarantee that if it takes 405 00:23:46,600 --> 00:23:49,959 Speaker 1: such a firm hand in defining what that is all about. 406 00:23:50,359 --> 00:23:52,800 Speaker 1: But at the same time, Apple is dependent upon the 407 00:23:52,880 --> 00:23:56,960 Speaker 1: ingenuity of a relatively small number of developers and innovators. Now, 408 00:23:57,080 --> 00:24:00,240 Speaker 1: let's contrast that with open source, which is a AND's 409 00:24:00,240 --> 00:24:03,800 Speaker 1: parent approach to developing technology. An open source project allows 410 00:24:03,840 --> 00:24:08,000 Speaker 1: anyone to see how the project works. Typically, such projects 411 00:24:08,000 --> 00:24:10,439 Speaker 1: invite people to take tech and play with it, and 412 00:24:10,480 --> 00:24:12,600 Speaker 1: they can add to it or modify it, or otherwise 413 00:24:12,600 --> 00:24:14,240 Speaker 1: try to make it do more than what it could 414 00:24:14,240 --> 00:24:17,359 Speaker 1: do before, or do what it does even better and 415 00:24:17,400 --> 00:24:20,560 Speaker 1: more efficiently. One of the biggest benefits of open source 416 00:24:20,680 --> 00:24:24,200 Speaker 1: is that it encourages innovation from a broad spectrum of developers. 417 00:24:24,520 --> 00:24:26,879 Speaker 1: You don't have to be on a special project team 418 00:24:26,880 --> 00:24:29,840 Speaker 1: in a specific company to contribute your ideas and designs 419 00:24:29,840 --> 00:24:33,560 Speaker 1: to an open source project. Ideally, this results in technology 420 00:24:33,600 --> 00:24:37,000 Speaker 1: that evolves super fast as different people apply their ideas 421 00:24:37,040 --> 00:24:40,120 Speaker 1: to the project, and a project might branch out numerous 422 00:24:40,240 --> 00:24:45,080 Speaker 1: unpredictable ways and shepherded by these open source developers. For IBM, 423 00:24:45,160 --> 00:24:48,000 Speaker 1: perhaps the most important part of going with the open 424 00:24:48,080 --> 00:24:51,040 Speaker 1: source approach is that allows for a standard that can 425 00:24:51,040 --> 00:24:55,119 Speaker 1: apply across numerous systems. It's not proprietary, so it doesn't 426 00:24:55,160 --> 00:24:59,200 Speaker 1: lock anyone into a particular ecosystem. And I'll explain why 427 00:24:59,400 --> 00:25:10,680 Speaker 1: in just a moment, but first let's take another quick break. Okay, 428 00:25:10,720 --> 00:25:13,600 Speaker 1: so why would IBM care if clients can move their 429 00:25:13,640 --> 00:25:17,280 Speaker 1: stuff around other providers? Well, it's because a fear of 430 00:25:17,359 --> 00:25:19,800 Speaker 1: lock in is one of the many reasons that companies 431 00:25:19,840 --> 00:25:23,720 Speaker 1: are reluctant to move more into the cloud, particularly when 432 00:25:23,720 --> 00:25:27,440 Speaker 1: it comes to mission critical applications and data This reluctance 433 00:25:27,520 --> 00:25:30,119 Speaker 1: is understandable for the reasons I mentioned earlier. There's a 434 00:25:30,200 --> 00:25:34,360 Speaker 1: legitimate fear about data security. There's worries about privacy. There's 435 00:25:34,359 --> 00:25:36,119 Speaker 1: the fear that a company might make a decision to 436 00:25:36,160 --> 00:25:38,840 Speaker 1: go with a specific provider and then they get stuck there, 437 00:25:39,200 --> 00:25:42,000 Speaker 1: even if a better deal comes along later. And then 438 00:25:42,119 --> 00:25:45,000 Speaker 1: there's the overall concern that as a company's data and 439 00:25:45,040 --> 00:25:49,480 Speaker 1: computation needs grow more complex, it becomes harder to manage everything, 440 00:25:49,520 --> 00:25:52,399 Speaker 1: and a company might grow itself out of business if 441 00:25:52,440 --> 00:25:57,160 Speaker 1: everything becomes an unmanageable If they have a dozen clouds, 442 00:25:57,200 --> 00:26:00,600 Speaker 1: some private, some public, and their applications are dependent upon 443 00:26:00,720 --> 00:26:03,840 Speaker 1: multiple clouds, and it's getting harder and harder to coordinate 444 00:26:03,880 --> 00:26:07,840 Speaker 1: all that they might not be able to innovate anymore. Now. 445 00:26:07,840 --> 00:26:10,399 Speaker 1: Since one of the big businesses for IBM is to 446 00:26:10,440 --> 00:26:13,600 Speaker 1: sell products that help companies manage their cloud operations, it 447 00:26:13,640 --> 00:26:16,840 Speaker 1: has a strong incentive to encourage companies to move into 448 00:26:16,840 --> 00:26:19,520 Speaker 1: the cloud. So to do that, IBM has to make 449 00:26:19,560 --> 00:26:22,399 Speaker 1: sure that such a move actually makes sense, and it 450 00:26:22,400 --> 00:26:24,840 Speaker 1: has to meet the business needs of clients, has to 451 00:26:24,960 --> 00:26:27,159 Speaker 1: keep their data safe, and it has to avoid the 452 00:26:27,200 --> 00:26:31,160 Speaker 1: pitfalls of vendor lock in. So that's why cloud computing 453 00:26:31,640 --> 00:26:33,639 Speaker 1: is such a big deal to IBM. Not only do 454 00:26:33,720 --> 00:26:36,880 Speaker 1: they have their own cloud computing services, they also offer 455 00:26:36,960 --> 00:26:40,680 Speaker 1: management software to handle activity across numerous clouds, and it's 456 00:26:40,720 --> 00:26:43,840 Speaker 1: an IBM's best interest to support an open source approach 457 00:26:43,880 --> 00:26:47,040 Speaker 1: to discourage lock in and remove those barriers of entry 458 00:26:47,080 --> 00:26:50,040 Speaker 1: to going to the cloud and inspiring rapid innovation in 459 00:26:50,080 --> 00:26:52,600 Speaker 1: the space. One of the things I got to see 460 00:26:52,640 --> 00:26:55,439 Speaker 1: here at Think two thousand nineteen was a demonstration of 461 00:26:55,480 --> 00:26:58,359 Speaker 1: IBMS Multi Cloud Manager tool, and I thought it was 462 00:26:58,359 --> 00:27:01,280 Speaker 1: pretty neat. Company executives owed off how the product lets 463 00:27:01,280 --> 00:27:04,680 Speaker 1: you look at containers across clusters no matter where those 464 00:27:04,680 --> 00:27:07,080 Speaker 1: clusters might be. You could have an application that pulls 465 00:27:07,160 --> 00:27:10,160 Speaker 1: data that lives on Amazon servers, Google servers, and your 466 00:27:10,160 --> 00:27:13,600 Speaker 1: own private servers, and the multi Cloud tool allows developers 467 00:27:13,680 --> 00:27:16,359 Speaker 1: or managers to view and manipulate the containers for that 468 00:27:16,440 --> 00:27:19,600 Speaker 1: application no matter where they might be located. So when 469 00:27:19,640 --> 00:27:22,080 Speaker 1: you consider that these are all very different companies with 470 00:27:22,119 --> 00:27:26,399 Speaker 1: their own hardware, this is pretty impressive. IBM feels that 471 00:27:26,440 --> 00:27:28,960 Speaker 1: cloud computing will take on a growing role in the 472 00:27:29,000 --> 00:27:31,679 Speaker 1: corporate world moving forward, and that the nature of the 473 00:27:31,720 --> 00:27:35,320 Speaker 1: complexity of cloud computing provides opportunity for products like the 474 00:27:35,400 --> 00:27:37,800 Speaker 1: Multi Cloud Manager tool, as well as the chance to 475 00:27:37,840 --> 00:27:42,320 Speaker 1: apply the Watson platform to numerous cloud based processes and applications. 476 00:27:42,560 --> 00:27:45,520 Speaker 1: The company has a strong business incentive to push for 477 00:27:45,560 --> 00:27:49,080 Speaker 1: this future. So what do I think? I think the 478 00:27:49,080 --> 00:27:52,960 Speaker 1: cloud approaches are pretty much the future because it makes 479 00:27:53,000 --> 00:27:55,719 Speaker 1: far more sense to me to use the cloud architecture 480 00:27:55,720 --> 00:28:00,119 Speaker 1: for development, deployment, and ongoing management of business processes. The 481 00:28:00,160 --> 00:28:04,000 Speaker 1: strategy moves away from systems that could become legacy machines, 482 00:28:04,400 --> 00:28:07,360 Speaker 1: that is, obsolete systems that a company has to maintain 483 00:28:07,480 --> 00:28:11,159 Speaker 1: or else risk losing valuable information or software. The cloud, 484 00:28:11,200 --> 00:28:15,280 Speaker 1: whether it's public or private, can be a scalable solution. 485 00:28:15,760 --> 00:28:19,719 Speaker 1: You can continuously add new equipment, you can port information 486 00:28:19,840 --> 00:28:23,280 Speaker 1: to the new equipment. You can sunset the older equipment. 487 00:28:23,320 --> 00:28:26,080 Speaker 1: So as a company grows, it can add more capacity 488 00:28:26,119 --> 00:28:28,960 Speaker 1: and its cloud, either by building it out itself or 489 00:28:29,000 --> 00:28:32,000 Speaker 1: working with a provider like IBM or Google or Amazon 490 00:28:32,160 --> 00:28:35,520 Speaker 1: or Microsoft. Now, to the average person, this might not 491 00:28:35,720 --> 00:28:38,320 Speaker 1: matter that much, at least not until you download the 492 00:28:38,360 --> 00:28:41,080 Speaker 1: latest app from your favorite brand or store or whatever 493 00:28:41,480 --> 00:28:43,840 Speaker 1: and it doesn't work properly because it can't pull the 494 00:28:43,920 --> 00:28:46,600 Speaker 1: data in needs, then you'll care a bit, but you 495 00:28:46,680 --> 00:28:50,280 Speaker 1: might not know the reason behind the app's failure. I 496 00:28:50,280 --> 00:28:53,280 Speaker 1: think the open source approach is likewise an important element 497 00:28:53,320 --> 00:28:56,080 Speaker 1: to this future. A company that goes all in with 498 00:28:56,120 --> 00:28:59,160 Speaker 1: a proprietary strategy might find itself out of luck if 499 00:28:59,200 --> 00:29:03,440 Speaker 1: the provider should experience problems. Imagine putting all your eggs 500 00:29:03,520 --> 00:29:07,160 Speaker 1: in the proprietary basket, and then the company you entrusted 501 00:29:07,360 --> 00:29:09,760 Speaker 1: reveals has been the target of a massive data breach. 502 00:29:10,200 --> 00:29:13,080 Speaker 1: Then imagine as that provider starts to struggle in the 503 00:29:13,120 --> 00:29:16,560 Speaker 1: wake of that revelation and then begins to falter. You'd 504 00:29:16,560 --> 00:29:18,920 Speaker 1: be worried that all your information and all your systems 505 00:29:18,920 --> 00:29:21,200 Speaker 1: were inside the computers of a company that's on the 506 00:29:21,320 --> 00:29:24,720 Speaker 1: verge of falling apart. An open source approach using a 507 00:29:24,720 --> 00:29:27,560 Speaker 1: standardized format, I mean, you'd be free to move your 508 00:29:27,640 --> 00:29:30,880 Speaker 1: data to any provider that used that same standard. So 509 00:29:31,200 --> 00:29:33,760 Speaker 1: I think IBM is on the right track here. Now 510 00:29:33,760 --> 00:29:37,160 Speaker 1: will I ever need to worry about this myself? It 511 00:29:37,320 --> 00:29:40,000 Speaker 1: is doubtful. I haven't received any phone calls from major 512 00:29:40,040 --> 00:29:42,720 Speaker 1: companies asking if I might be their chief information officer. 513 00:29:43,040 --> 00:29:45,840 Speaker 1: But I recognize the importance of the tech and how 514 00:29:45,880 --> 00:29:48,760 Speaker 1: it powers or at least enables a lot of the 515 00:29:48,800 --> 00:29:52,280 Speaker 1: stuff I rely upon on a daily basis, So attending 516 00:29:52,360 --> 00:29:54,960 Speaker 1: Think two thousand nineteen and getting a deeper understanding and 517 00:29:55,000 --> 00:29:58,880 Speaker 1: appreciation of the technology was a pretty cool experience, even 518 00:29:58,920 --> 00:30:01,520 Speaker 1: if some of it was over my head and nearly 519 00:30:01,520 --> 00:30:04,120 Speaker 1: all of it over my pay grade. That wraps up 520 00:30:04,120 --> 00:30:08,160 Speaker 1: this episode of tech Stuff. If you guys have any questions, 521 00:30:08,240 --> 00:30:11,120 Speaker 1: or you have comments, or you have ideas for future episodes, 522 00:30:11,160 --> 00:30:13,680 Speaker 1: send me a message. The address is tech stuff at 523 00:30:13,720 --> 00:30:16,400 Speaker 1: how stuff works dot com, or you can hop on 524 00:30:16,440 --> 00:30:19,480 Speaker 1: over to the web check out text stuff podcast dot com. 525 00:30:19,520 --> 00:30:21,480 Speaker 1: That's our website where we have the archive of all 526 00:30:21,520 --> 00:30:24,360 Speaker 1: of our older shows, plus links to our social media 527 00:30:24,400 --> 00:30:26,160 Speaker 1: so you can get in touch with me there, and 528 00:30:26,200 --> 00:30:29,080 Speaker 1: also a link to our merchandise store. So go check 529 00:30:29,120 --> 00:30:32,080 Speaker 1: that out and I'll talk to you again really soon. 530 00:30:37,600 --> 00:30:40,040 Speaker 1: For more on this and thousands of other topics, is 531 00:30:40,080 --> 00:30:51,080 Speaker 1: it how stuff works dot com.