1 00:00:00,000 --> 00:00:04,000 Speaker 1: So it's Tech Tuesday with Mike Dubuski, ABC News reporter 2 00:00:04,320 --> 00:00:08,039 Speaker 1: and tech Maven out of New York. Mike, good morning, 3 00:00:08,160 --> 00:00:09,200 Speaker 1: Thank you for joining us. 4 00:00:09,440 --> 00:00:10,920 Speaker 2: Yeah, good morning. How are you all right? 5 00:00:11,680 --> 00:00:16,800 Speaker 1: The big news is the AWS meltdown, and it is 6 00:00:17,000 --> 00:00:21,680 Speaker 1: absolutely enormous. And so here's my first question. Because they 7 00:00:22,400 --> 00:00:25,959 Speaker 1: are known. I think they're the world's biggest company that 8 00:00:26,079 --> 00:00:28,760 Speaker 1: does cloud computing. 9 00:00:28,920 --> 00:00:29,200 Speaker 2: They are. 10 00:00:29,680 --> 00:00:33,480 Speaker 1: And you know, I'm very confused because I thought your 11 00:00:33,479 --> 00:00:36,840 Speaker 1: information in the clouds were in the clouds and that's 12 00:00:36,880 --> 00:00:38,760 Speaker 1: not how it works, is it. And if you could 13 00:00:38,800 --> 00:00:43,839 Speaker 1: explain how this actually works and then what happened and 14 00:00:43,880 --> 00:00:45,480 Speaker 1: what's going on right now? Yeah? 15 00:00:45,520 --> 00:00:48,080 Speaker 2: Sure. So if you're a small business, let's say you 16 00:00:48,080 --> 00:00:50,640 Speaker 2: want to open a cafe in downtown Los Angeles or 17 00:00:50,680 --> 00:00:54,000 Speaker 2: what have you, it doesn't really make economic sense for 18 00:00:54,120 --> 00:00:57,600 Speaker 2: you to spin up like a computer server to run 19 00:00:57,640 --> 00:01:00,760 Speaker 2: your payroll or to run your payments processing or whatever 20 00:01:00,880 --> 00:01:03,800 Speaker 2: else it is you do online. It kind of makes 21 00:01:03,880 --> 00:01:06,680 Speaker 2: more economic sense for a lot of companies to outsource 22 00:01:06,760 --> 00:01:09,480 Speaker 2: that work to someone who knows what they're doing, you know, 23 00:01:09,520 --> 00:01:12,840 Speaker 2: a Microsoft or a Google, or in this case, an Amazon, 24 00:01:12,880 --> 00:01:17,720 Speaker 2: which accounts for the largest chunk of the cloud computing service. 25 00:01:18,360 --> 00:01:20,800 Speaker 2: This is a service that works, you know, ninety nine 26 00:01:20,840 --> 00:01:23,160 Speaker 2: percent of the time. The reason that Amazon accounts for 27 00:01:23,200 --> 00:01:25,959 Speaker 2: about thirty seven percent of this market and Google and 28 00:01:26,040 --> 00:01:28,920 Speaker 2: Microsoft account for another third of it goes back to 29 00:01:28,959 --> 00:01:32,280 Speaker 2: the idea that they run really robust systems that don't 30 00:01:32,280 --> 00:01:35,520 Speaker 2: go down ninety nine percent of the time. Well, yesterday, 31 00:01:35,560 --> 00:01:38,080 Speaker 2: in the case of Amazon, we saw that one percent 32 00:01:38,120 --> 00:01:41,480 Speaker 2: of the time crop up when an issue with specifically 33 00:01:41,520 --> 00:01:45,560 Speaker 2: their DNS cropped up. This is a domain name service. Basically, 34 00:01:45,600 --> 00:01:47,560 Speaker 2: to make a very technical thing kind of simple, it 35 00:01:47,640 --> 00:01:50,640 Speaker 2: is a piece of technology that translates human language into 36 00:01:50,680 --> 00:01:53,160 Speaker 2: something that a computer can understand. It's what you type 37 00:01:53,200 --> 00:01:56,080 Speaker 2: into a web browser being translated into an IP address. 38 00:01:56,440 --> 00:01:58,800 Speaker 2: So that is the sort of nature of the problem. 39 00:01:58,800 --> 00:02:00,640 Speaker 2: We don't know specifically what went wrong with it, but 40 00:02:00,720 --> 00:02:03,320 Speaker 2: that's what went down, and it created these sort of 41 00:02:03,400 --> 00:02:06,520 Speaker 2: knock on effects throughout the day. Because Amazon Web Services 42 00:02:06,880 --> 00:02:09,280 Speaker 2: is so big and it hosts so many different you know, 43 00:02:09,360 --> 00:02:12,480 Speaker 2: servers and technologies out there, you break one thing, it 44 00:02:12,520 --> 00:02:14,640 Speaker 2: actually ends up breaking like four or five things. So 45 00:02:14,680 --> 00:02:16,600 Speaker 2: there was like a kind of knock on effect of 46 00:02:16,760 --> 00:02:19,919 Speaker 2: whack a mole situation going on where Amazon engineers fix 47 00:02:20,000 --> 00:02:23,000 Speaker 2: the main problem pretty quickly and then you know, realize 48 00:02:23,040 --> 00:02:26,320 Speaker 2: these later problems down the line. The good news is 49 00:02:26,360 --> 00:02:28,600 Speaker 2: that most things are resolved at this point. A quick 50 00:02:28,639 --> 00:02:30,840 Speaker 2: look at down detector right now finds that most of 51 00:02:30,880 --> 00:02:34,200 Speaker 2: the major players who are experiencing issues yesterday among them 52 00:02:34,280 --> 00:02:39,440 Speaker 2: then Moost, Snapchat, Microsoft three sixty five, Google It excuse 53 00:02:39,480 --> 00:02:41,880 Speaker 2: me a zoom, I should say not Google, but like, 54 00:02:41,960 --> 00:02:44,880 Speaker 2: these are all systems that are now running relatively normally, 55 00:02:45,000 --> 00:02:47,400 Speaker 2: and you know the people are somewhat back to normal. 56 00:02:47,480 --> 00:02:50,639 Speaker 2: You're a Starbucks order on the app should work this morning. 57 00:02:50,919 --> 00:02:53,800 Speaker 1: Now, when you say thirty percent of the market that 58 00:02:53,880 --> 00:02:57,080 Speaker 1: Amazon has, is that just the American market? Are we 59 00:02:57,120 --> 00:02:58,480 Speaker 1: talking internationally and it's. 60 00:02:58,400 --> 00:03:00,440 Speaker 2: The global market and those to it. 61 00:03:00,520 --> 00:03:00,720 Speaker 1: Yeah. 62 00:03:00,840 --> 00:03:02,680 Speaker 2: I was talking to a friend of mine who is 63 00:03:02,720 --> 00:03:05,560 Speaker 2: a tech journalist in the UK, and they actually experienced 64 00:03:05,600 --> 00:03:07,840 Speaker 2: this in a much more acute way because they're ahead 65 00:03:07,840 --> 00:03:11,359 Speaker 2: of us. This outage actually happened for you guys kind 66 00:03:11,360 --> 00:03:12,919 Speaker 2: of in the overnight hours. For us here on the 67 00:03:12,960 --> 00:03:15,840 Speaker 2: East coast, it was just after three am, and most 68 00:03:15,840 --> 00:03:17,720 Speaker 2: of America is asleep at that point, so the sort 69 00:03:17,720 --> 00:03:20,440 Speaker 2: of initial wave of problems were only noticed by people 70 00:03:20,480 --> 00:03:22,720 Speaker 2: who were up at that time. Of course, we started 71 00:03:22,760 --> 00:03:25,280 Speaker 2: to see more reports trickle in, you know, nine o'clock, 72 00:03:25,320 --> 00:03:27,280 Speaker 2: ten o'clock as people go to work and figure out, 73 00:03:27,480 --> 00:03:29,160 Speaker 2: you know, hey, this thing I had access to, I 74 00:03:29,200 --> 00:03:31,600 Speaker 2: don't have access to anymore. Well, in the UK, that 75 00:03:31,720 --> 00:03:34,960 Speaker 2: hit their government systems, right, the website that controls their 76 00:03:35,040 --> 00:03:38,520 Speaker 2: equivalent of the IRS went down in part because of this, 77 00:03:39,000 --> 00:03:42,120 Speaker 2: So you know, it really does underscore exactly how much 78 00:03:42,200 --> 00:03:45,440 Speaker 2: influence Amazon has in this particular market. We saw similar 79 00:03:45,480 --> 00:03:48,360 Speaker 2: stories come out of continental Europe and beyond in Australia 80 00:03:48,400 --> 00:03:48,720 Speaker 2: as well. 81 00:03:49,760 --> 00:03:53,240 Speaker 1: I mean, it is astounding how big this is. Now, 82 00:03:54,120 --> 00:03:59,320 Speaker 1: if I'm not mistaken, this AWS accounts for more money 83 00:03:59,400 --> 00:04:02,400 Speaker 1: and more pro than the retail end of Amazon itself. 84 00:04:02,440 --> 00:04:03,160 Speaker 1: Do I have that right? 85 00:04:04,040 --> 00:04:04,360 Speaker 2: It does. 86 00:04:04,520 --> 00:04:04,720 Speaker 1: Yeah. 87 00:04:04,800 --> 00:04:08,120 Speaker 2: We often think of Amazon as like this e commerce website, 88 00:04:08,120 --> 00:04:09,920 Speaker 2: that's where they make their money. Of course, that's the 89 00:04:09,920 --> 00:04:13,000 Speaker 2: public facing component of their business. But when you actually 90 00:04:13,000 --> 00:04:16,360 Speaker 2: look at their profits, the majority of them come from AWS, 91 00:04:16,440 --> 00:04:19,440 Speaker 2: come from this cloud computing service. Amazon is a cloud 92 00:04:19,440 --> 00:04:22,240 Speaker 2: computing company before it's an e commerce retailer. That's the 93 00:04:22,720 --> 00:04:25,400 Speaker 2: long and short of it. And you know that again 94 00:04:25,520 --> 00:04:27,520 Speaker 2: is something I don't think a lot of people understand 95 00:04:27,520 --> 00:04:28,240 Speaker 2: it's really important. 96 00:04:28,240 --> 00:04:34,960 Speaker 1: Episode now, this cloud servicing, it has to do with 97 00:04:35,080 --> 00:04:42,400 Speaker 1: these massive forms of computers that keep my information, your 98 00:04:42,400 --> 00:04:47,800 Speaker 1: information's process things. I'm almost thinking that the world of 99 00:04:47,880 --> 00:04:52,760 Speaker 1: computing is growing far much quicker than their ability than 100 00:04:53,240 --> 00:04:56,040 Speaker 1: people like a WS or companies to deal with it 101 00:04:56,760 --> 00:04:58,760 Speaker 1: and the amount of energy that it takes. You want 102 00:04:58,800 --> 00:04:59,440 Speaker 1: to talk about that. 103 00:05:00,000 --> 00:05:02,760 Speaker 2: So yeah, So I think that there are certainly protocols 104 00:05:02,760 --> 00:05:05,240 Speaker 2: that companies like Amazon can implement to make sure that 105 00:05:05,279 --> 00:05:08,400 Speaker 2: they're not shipping out faulty code that breaks things like 106 00:05:08,440 --> 00:05:11,240 Speaker 2: we saw yesterday, or maybe they raise the standards in 107 00:05:11,360 --> 00:05:14,120 Speaker 2: the coding for you know, how they deal with third 108 00:05:14,120 --> 00:05:17,200 Speaker 2: parties and what have you. We also, in recent years 109 00:05:17,240 --> 00:05:20,240 Speaker 2: have seen generative artificial intelligence play a bigger role in 110 00:05:20,279 --> 00:05:23,120 Speaker 2: sort of like entry level coding, in fact taking the 111 00:05:23,200 --> 00:05:27,520 Speaker 2: place of entry level coders at many tech companies. However, 112 00:05:27,680 --> 00:05:30,520 Speaker 2: humans are imperfect, right, They're going to ship out improper 113 00:05:30,560 --> 00:05:33,159 Speaker 2: code every once in a while, and so is generative 114 00:05:33,240 --> 00:05:35,599 Speaker 2: artificial intelligence. Despite the fact that we talk about it 115 00:05:35,600 --> 00:05:38,920 Speaker 2: all the time as this transformative technology, it's still pretty 116 00:05:38,960 --> 00:05:41,680 Speaker 2: bad at a lot of things and hallucinates and makes 117 00:05:41,720 --> 00:05:44,599 Speaker 2: mistakes frequently, and that means that in the same way 118 00:05:44,600 --> 00:05:46,800 Speaker 2: that you come across a typo in the newspaper every 119 00:05:46,800 --> 00:05:49,680 Speaker 2: once in a while, or your order at Starbucks is incorrect, 120 00:05:50,080 --> 00:05:53,800 Speaker 2: you're going to see, you know, disruptions like this. This, unfortunately, 121 00:05:53,960 --> 00:05:55,920 Speaker 2: is just a way of life right now. As we said, 122 00:05:56,160 --> 00:05:58,560 Speaker 2: this is not unusual. We did not see the stock 123 00:05:58,600 --> 00:06:01,640 Speaker 2: price of Amazon move yet yesterday in any sort of 124 00:06:01,720 --> 00:06:05,320 Speaker 2: dramatic way, despite all the dysfunctionality that people were seeing 125 00:06:05,360 --> 00:06:07,839 Speaker 2: on the ground. Meeting investors were not spooked by this, 126 00:06:07,960 --> 00:06:10,359 Speaker 2: perhaps thinking that this is part of just the normal 127 00:06:10,400 --> 00:06:13,040 Speaker 2: course of business. It is frustrating, no doubt, but it 128 00:06:13,080 --> 00:06:16,160 Speaker 2: is not unusual. I do think the big takeaway here 129 00:06:16,200 --> 00:06:18,440 Speaker 2: has to come with their market power, right We talked 130 00:06:18,440 --> 00:06:21,320 Speaker 2: about this a little bit before the break. Amazon accounts 131 00:06:21,320 --> 00:06:24,839 Speaker 2: for about thirty seven percent of the cloud computing market. 132 00:06:24,880 --> 00:06:28,159 Speaker 2: Another third goes to just two companies, Microsoft and Google. 133 00:06:28,520 --> 00:06:30,719 Speaker 2: We've centralized a lot of power in the hands of 134 00:06:30,800 --> 00:06:33,520 Speaker 2: just a few companies, and when something goes wrong, it's 135 00:06:33,520 --> 00:06:36,760 Speaker 2: going to have big ripple effects, an outsized effect. When 136 00:06:36,920 --> 00:06:39,440 Speaker 2: you know, a flaw crops up like this DNS problem 137 00:06:39,440 --> 00:06:41,400 Speaker 2: did yesterday, do they know. 138 00:06:42,440 --> 00:06:45,800 Speaker 1: What caused it. Was it just a glitch in the system? 139 00:06:46,200 --> 00:06:49,600 Speaker 2: Yeah, or okay, it was not a cyber attack, I 140 00:06:49,600 --> 00:06:51,760 Speaker 2: think is the important thing to say. Amazon came out 141 00:06:51,839 --> 00:06:54,080 Speaker 2: very quickly, you know, at the beginning of yesterday and said, 142 00:06:54,120 --> 00:06:56,040 Speaker 2: this is a tech issue. This isn't you know, any 143 00:06:56,080 --> 00:06:59,240 Speaker 2: nefarious actors or foreign governments or anything like that. This 144 00:06:59,360 --> 00:07:02,280 Speaker 2: is just something went wrong, frankly, and we don't know 145 00:07:02,320 --> 00:07:05,120 Speaker 2: the specific nature of what went wrong, but we know 146 00:07:05,200 --> 00:07:08,800 Speaker 2: it has to do with their domain name service. This 147 00:07:08,880 --> 00:07:13,200 Speaker 2: is again a technology that translates you know, human language 148 00:07:13,440 --> 00:07:16,559 Speaker 2: KFI dot com, ABC news dot com for example, into 149 00:07:16,600 --> 00:07:19,320 Speaker 2: something that a computer can understand, into an IP address 150 00:07:19,360 --> 00:07:21,880 Speaker 2: or an Internet protocol basically a big string of numbers 151 00:07:21,880 --> 00:07:24,000 Speaker 2: that tells the computer where to go on the internet, 152 00:07:24,040 --> 00:07:26,640 Speaker 2: where to direct your request. That is what went wrong. 153 00:07:27,360 --> 00:07:29,520 Speaker 2: And then obviously, you know, you break one thing in 154 00:07:29,520 --> 00:07:31,080 Speaker 2: the morning and it actually ends up breaking like four 155 00:07:31,160 --> 00:07:33,120 Speaker 2: or five other things. So you saw this kind of 156 00:07:33,120 --> 00:07:35,120 Speaker 2: play out over the course of the day. And in fact, 157 00:07:35,200 --> 00:07:38,280 Speaker 2: right now we're actually seeing, according to down Detector, some 158 00:07:38,440 --> 00:07:42,400 Speaker 2: things related to Amazon Web services start to report more problems. 159 00:07:42,640 --> 00:07:44,360 Speaker 2: I think we're just going to be dealing with this 160 00:07:44,480 --> 00:07:46,800 Speaker 2: for the next you know, few hours, at least the 161 00:07:46,840 --> 00:07:50,600 Speaker 2: next few days, perhaps as Amazon continues to figure out, 162 00:07:50,720 --> 00:07:53,920 Speaker 2: you know, the long tail effect of this large break 163 00:07:54,080 --> 00:07:54,840 Speaker 2: yesterday morning. 164 00:07:55,200 --> 00:07:57,360 Speaker 1: All right, So let's say I'm a business and I 165 00:07:57,480 --> 00:08:00,520 Speaker 1: rely on AWS to keep my business going, and I 166 00:08:00,560 --> 00:08:05,440 Speaker 1: can prove that this outage cost me money. Do I 167 00:08:05,560 --> 00:08:09,040 Speaker 1: have any chance? Do I have any mechanism of making 168 00:08:09,120 --> 00:08:11,880 Speaker 1: a claim and saying, hey, I want my three hundred dollars, 169 00:08:11,920 --> 00:08:14,880 Speaker 1: I want my ten thousand dollars that you cost me. 170 00:08:15,520 --> 00:08:17,760 Speaker 2: You know, that's a really good question. We have not 171 00:08:17,840 --> 00:08:20,680 Speaker 2: really heard anything on that front. You know. I think 172 00:08:20,760 --> 00:08:24,280 Speaker 2: that a point against that type of class action lawsuit 173 00:08:24,320 --> 00:08:26,320 Speaker 2: or that legal action would be the fact that, like 174 00:08:26,400 --> 00:08:29,200 Speaker 2: this happens to everyone, and this happens somewhat frequently. 175 00:08:29,280 --> 00:08:29,440 Speaker 1: Right. 176 00:08:29,480 --> 00:08:32,560 Speaker 2: Amazon Web Services itself went down in a very similar 177 00:08:32,559 --> 00:08:34,600 Speaker 2: way back in twenty twenty three, and in twenty twenty one, 178 00:08:34,679 --> 00:08:37,480 Speaker 2: and in twenty twenty. Microsoft and Google have dealt with this. 179 00:08:37,679 --> 00:08:41,880 Speaker 2: We talked about crowd Strike earlier, which is that cybersecurity 180 00:08:41,880 --> 00:08:44,400 Speaker 2: outfit that shipped a faulty bit of code. You know, 181 00:08:45,080 --> 00:08:47,240 Speaker 2: this is going to happen to some degree or another. 182 00:08:47,360 --> 00:08:50,280 Speaker 2: I think the lesson that those businesses can take here 183 00:08:50,760 --> 00:08:53,720 Speaker 2: has more to do with diversification, right, instead of putting 184 00:08:53,720 --> 00:08:57,160 Speaker 2: all your eggs, you'r all your cloud computing into you 185 00:08:57,160 --> 00:08:59,720 Speaker 2: know aws. Maybe you put like two eggs into that 186 00:08:59,760 --> 00:09:02,160 Speaker 2: bad and then two eggs into the Google basket, and 187 00:09:02,160 --> 00:09:05,320 Speaker 2: then maybe another one into you know, a smaller How 188 00:09:05,320 --> 00:09:05,839 Speaker 2: do you do that? 189 00:09:05,880 --> 00:09:07,600 Speaker 1: How do you do that with one business? 190 00:09:08,400 --> 00:09:10,280 Speaker 2: It's very easy. I mean, let's let's go back to 191 00:09:10,360 --> 00:09:12,880 Speaker 2: like the cafe example that we were talking about earlier. 192 00:09:13,200 --> 00:09:16,400 Speaker 2: You know, you do different things online with your small business. 193 00:09:16,400 --> 00:09:19,520 Speaker 2: Some is payments processing, some as payroll, some as you know, 194 00:09:19,640 --> 00:09:22,760 Speaker 2: menus or ordering or whatever it happens to be. Well, okay, 195 00:09:22,880 --> 00:09:25,720 Speaker 2: one feature can be hosted on this service, another future 196 00:09:25,720 --> 00:09:28,800 Speaker 2: can be hosted over here. Does that increase your costs? Well, 197 00:09:28,800 --> 00:09:30,320 Speaker 2: you gotta have to You're gonna have to answer that 198 00:09:30,360 --> 00:09:34,320 Speaker 2: for yourself. But like that's a way to guard against, 199 00:09:34,440 --> 00:09:37,400 Speaker 2: you know, your entire business going offline if one of 200 00:09:37,440 --> 00:09:39,440 Speaker 2: these major companies sees a disruption. 201 00:09:39,960 --> 00:09:43,319 Speaker 1: Fair enough, Mike, thank you. That was a terrific way 202 00:09:43,360 --> 00:09:46,120 Speaker 1: of explaining this to us. We'll talk again next week. 203 00:09:46,280 --> 00:09:46,679 Speaker 2: Sounds good. 204 00:09:46,760 --> 00:09:48,720 Speaker 1: Take care, I have a good one. ABC News reporter 205 00:09:48,920 --> 00:09:51,560 Speaker 1: Mike Dubusky. Boy, he knows this stuff, doesn't he. Okay,