Wes Miller, Research VP at Directions on Microsoft, joins Corey on Screaming in the Cloud to discuss the various intricacies and pitfalls of Microsoft licensing. Wes and Corey discuss what it’s like to work closely with a company like Microsoft in your day-to-day career, while also looking out for the best interest of your mutual customers. Wes explains his history of working both at and with Microsoft, and the changes he’s seen to their business models and the impact that has on their customers. About WesWes Miller analyzes and writes about Microsoft security, identity, and systems management technologies, as well as Microsoft product licensing.Before joining Directions on Microsoft in 2010, Wes was a product manager and development manager for several Austin, TX, start-ups, including Winternals Software, acquired by Microsoft in 2006. Prior to that, Wes spent seven years at Microsoft working as a program manager in the Windows Core Operating System and MSN divisions.Wes received a B.A. in psychology from the University of Alaska Fairbanks.Links Referenced: Directions on Microsoft Website: https://www.directionsonmicrosoft.com/ Twitter: https://twitter.com/getwired LinkedIn: https://www.linkedin.com/in/wmiller/ Directions on Microsoft Training: https://www.directionsonmicrosoft.com/training TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: Welcome to Screaming in the Cloud, I’m Corey Quinn. So, I write a newsletter called Last Week in AWS, which has always felt like it’s flying a little bit too close to the sun just because having AWSes name in the title of what I do feels like it’s playing with copyright fire. It’s nice periodically to talk to someone—again—who is in a similar boat. Wes Miller is a Research VP at Directions on Microsoft. To be clear, Directions on Microsoft is an analyst firm that talks primarily about Microsoft licensing and is not, in fact, part of Microsoft itself. Have I disclaimed that appropriately, Wes?Wes: You have. You have. And in fact, the company, when it was first born, was actually called Microsoft Directions. And they had a reasonably good relationship with Microsoft at the time and Microsoft cordially asked them, “Hey, could you at least reverse that so it corrects it in terms of trademark.” So yes, we’re blessed in that regard. Something you probably would never get away with now, but that was 30 years ago.Corey: [laugh]. And now it sounds like it might as well be a product. So, I have to ask, just because the way I think of you is, you are the folks to talk to, full stop, when you have a question about anything that touches on Microsoft licensing. Is that an accurate depiction of what it is you folks do or is that just my particular corner of the world and strange equivalence that gets me there?Wes: That is our parts of the Venn diagram intersecting because that’s what I spend a lot of time talking about and thinking about because I teach that with our company founder, Rob Horwitz. But we also spend an inordinate amount of time taking what Microsoft is talking about shipping, maybe servicing, and help customers understand really, as we say, the ‘So, what?’ What does this mean to me as a customer? Should I be using this? Should I be waiting? Should I upgrade? Should I stay? Those sorts of things.So, there’s a whole roadmapping side. And then we have a [laugh]—because licensing doesn’t end with a license, we have a whole side of negotiation that we spend a lot of time, we have a dedicated team that focuses on helping enterprise agreement customers get the most successful deal for their organization, basically, every three years.Corey: We do exactly that with AWS ourselves. I have to ask before we dive into this. In the early days, I felt like I had a much better relationship with Microsoft. Scott Guthrie, the head of Azure, was on this show. A number of very highly placed Microsoft folks were here. And over the years, they more or less have stopped talking to me.And that leaves me in a position where all I can see is their actions and their broad public statements without getting any nuance or context around any of it. And I don’t know if this is just a commentary on human nature or me in particular, but I tend to always assume the worst when things like that happen. So, my approach to Microsoft has grown increasingly cynical over the years as a result. That said, I don’t actually have an axe to grind with them from any other perspective than as a customer, and occasionally that feels like ‘victim’ for a variety of different things. What’s your take on Microsoft as far as, I guess, your feelings toward the company?Wes: So, a lot of people—in fact, it used to be more so, but not as much anymore, people would assume I hate Microsoft or I want to demonize Microsoft. But the irony actually is, you know, I want people to remember I worked there for seven-and-a-half years, I shipped—I was on the team that shipped Windows XP, Server 2003, and a bunch of other products that people don’t remember. And I still care about the company, but the company and I are obviously in different trajectories now. And also, my company’s customers today are also Microsoft’s customers today, and we actually have—our customers—our mutual customers—best interest in mind with basically everything we do. Are we helping them be informed? Are we helping them color within the financial lines?And sometimes, we may say things that help a customer that aren’t helping the bottom line or helping a marketing direction and I don’t think that resonates well within Microsoft. So sure, sometimes we even hear from them, “Hey, it’d be great if you guys might want to, you know, say something nice once in a while.” But it’s not necessarily our job to say nice things. I do it once in a while. I want to note that I said something nice about AAD last week, but the reality is that we are there to help our mutual customers.And what I found is, I have found the same thing to be true that you’re finding true that, unfortunately, outbound communications from them, in particular from the whole company, have slowed. I think everybody’s busier, they’ve got a very specific set of directions they’re going on things, and as a result, we hear very little. And even getting, trying to get clarification on things sometimes, “Did we read that right?” It takes a while, and it has to go through several different rungs of people to get the answer.Corey: I have somewhat similar relationships over the years with AWS, where they—in many cases, a lot of their executives prefer not to talk to me at all. Which again, is fair. I’m not—I don’t require any of them to do it. But there’s something in the Amazonian ethos that requires them to talk to customers, especially when customers are having a rough time. And I’m, for better or worse, the voice of the customer.I am usually not the dumbest person in the universe when it comes to trying to understand a service or make it do something that, to me, it seems that it should be able to do. And when I actually start having in-depth conversations, people are surprised. “Wow, you were super pleasant and fun to work with. We thought you were just going to be a jerk.” It’s, yeah, it turns out I don’t go through every meeting like it’s Twitter. What a concept.Wes: Yeah, a lot of people, I’ve had this happen for myself when you meet people in person, when they meet your Twitter persona, especially for someone who I think you and I both come across as rather boisterous, gregarious, and sometimes people take that as our personas. And I remember meeting a friend in the UK for the first time years ago, he’s like, “You’re very different in person.” I’m like, “I know. I know.”Corey: I usually get the, “You’re just like Twitter.” In many respects, I am. Because people don’t always see what I’m putting down. I make it a point to be humorous and I have a quick quip for a lot of things, but it’s never trying to make the person I’m engaging with feel worse for it. And that’s how I work.People are somewhat surprised when I’m working in client meetings that I’m fun and I have a similar sense of humor and personality, as you would see on Twitter. Believe it or not, I haven’t spent all this time just doing a bit. But they’re also surprised that it tends to drive toward an actual business discussion.Wes: Sure.Corey: Everything fun is contextual.Wes: Absolutely. That’s the same sort of thing we get on our side when we talk to customers. I think I’ve learned so much from talking with them that sometimes I do get to share those things with Microsoft when they’re willing to listen.Corey: So, what I’m curious about in the context of Microsoft licensing is something that, once again, it has intruded upon my notice lately with a bunch of security disclosures in which Microsoft has said remarkably little, and that is one of the most concerning things out there. They casually tried to slide past, “Oh, yeah, we had a signing key compromised.” Which is one of those, “Oh, [laugh] and by the way, the building’s on fire. But let’s talk about our rent [unintelligible 00:07:44] for the next year.” Like, “Whoa, whoa, whoa. Hold on. What?”That was one of those horrifying moments. And it came out—I believe I learned about this from you—that you needed something called E3 licensing—sorry, E5 licensing—in order to look at those audit logs, where versus E3, which sounded like the more common case. And after a couple of days of, “Explain this,” Microsoft very quickly wound up changing that. What do all these things mean? This is sort of a foreign concept to me because AWS, for better or worse, does not play games with licensing in the same way that Microsoft does.Wes: Sure. Microsoft has, over the years, you know, they are a master of building suites. This is what they’ve done for over 30 years. And they will build a suite, they’ll sell you that suite, they’ll come back around in three to six years and sell you a new version of that suite. Sometimes they’ll sell you a higher price version of that suite, et cetera.And so, you’ll see products evolve. And did a great podcast with my colleagues Rob and Mary Jo Foley the other day where we talked about what we’ve seen over the last, now for me, 11 years of teaching boot camps. And I think in particular, one of the changes we have seen is exactly what you’re being exposed to on the outside and what a lot of people have been complaining about, which is, products don’t sit still anymore. So, Microsoft actually makes very few products today. Almost everything they sell you is a service. There are a handful of products still.These services all evolve, and about every triennium or two—so every three to six years—you’ll see a price increase and something will be added, and a price increase and something will be added. And so, all this began with the BPOS, the first version of Office 365, which became Office 365 E3, then Microsoft 365 E3 then Microsoft 365 E5. And for people who aren’t in the know, basically, that means they went from Office as a subscription to Office, Windows, and a bunch of management tools as a subscription, to E5, basically, it took all of the security and compliance tools that many of us feel should have been baked into the fundamentals, into E3, the thing that everybody buys, what I refer to still today as the hero SKU and those security and compliance fundamentals should have been baked in. But no, in fact, a lot of customers when this AAD issue came out—and I think a lot discovered this ad hoc for the same reason, “Hey, we’ve been owned, how far back in the logs can we look?” And the answer is, you know, no farther than 90 days, a lot of customers hit that reality of, what do you mean we didn’t pay for the premium thing that has all the logging that we need?Corey: Since you sat on this for eight months before mentioning it to us? Yeah.Wes: Exactly, exactly. And it’s buried. And it’s one of those things that, like, when we teach the licensing boot camp, I specifically call out because of my security background, it’s an area of focus and interest to me. I call out to customers that a lot of the stuff we’ve been showing you has not questionable valuable, but kind of squishy value.This piece right here, this is both about security and compliance. Don’t cheap out. If you’re going to buy anything, buy this because you’re going to need it later. And I’ve been saying that for, like, three years, but obviously only the people who were in the boot camp would hear that and then shake their head;, “Why does it have to be this difficult?” But yeah. Everything becomes a revenue opportunity if it’s a potential to upsell somebody for the next tier.Corey: The couple of times I’ve been asked to look at Azure bills, I backed away slowly as soon as I do, just because so much of it is tied to licensing and areas that are very much outside of my wheelhouse. Because I view, in the cloud context, that cost and architecture tend to be one of the same. But when you bolt an entire layer of seat licensing and what this means for your desktop operating systems on as well as the actual cloud architecture, it gets incredibly confusing incredibly quickly. And architectural advice of the type that I give to AWS customers and would give to GCP customers is absolutely going to be harmful in many respects.I just don’t know what I don’t know and it’s not an area that interests me, as far as learning that competency, just to jump through hoops. I mean, I frankly used to be a small business Windows admin, with the products that you talked about, back when XP and Server 2003 and a few others, I sort of ruled the roost. But I got so tired of surprise audit-style work. It felt like busy work that wasn’t advancing what I was trying to get done in any meaningful way that, in a fit of rage, one day, I wound up exploring the whole Unix side of the world in 2006 and never went back.Wes: [whispering] That’s how it happened.Corey: Yep.Wes: It’s unfortunate that it’s become so commonplace, but when Vista kind of stalled out and they started exploring other revenue opportunities, you have Vista Ultimate Enterprise, all the crazy SKUing that Vista had, I think it sort of created a mindset within the company that this is what we have to do in order to keep growing revenue up and to the right, and you know, shareholder value be the most important thing, that’s what you’ve got to do. I agree entirely, though, the biggest challenge I could see for someone coming into our space is the fact that yes, you’ve got to understand Azure, Azure architecture, development architecture, and then as soon as you feel like you understand that, somebody comes along and says, “Well, yeah, but because we have an EA, we have to do it this way or we only get a discount on this thing.” And yeah, it just makes things more cumbersome. And I think that’s why we still see a lot of customers who come to our boot camps who are still very dedicated AWS customers because that’s where they were, and it’s easier in many regards, and they just want to go with what they know.Corey: And I think that that’s probably fair. I think that there is an evolution that grows here that I think catches folks by surprise. I’m fortunate in that my Microsoft involvement, if we set things like GitHub aside because I like them quite a bit and my Azure stuff as well—which is still small enough to fit in the free tier, given that I use it for one very specific, very useful thing—but the rest of it is simply seat licenses for Office 365 for my team. And I just tend to buy the retail-priced one on the internet that’s licensed for business use, and I don’t really think about it again. Because I don’t need, as you say, in-depth audit logs for Microsoft Word. I really don’t. I’m sorry, but I have a hard time believing that that’s true. But something that immediately crops up when you say this is when you talk about E3 versus E5 licensing, is that organization-wide or is that on a per-seat basis?Wes: It’s even worse than that. It usually comes down to per-user licensing. The whole world used to be per device licensing in Microsoft and it switched to per user when they subscript-ified everything—that’s a word I made up a while ago—so when they subscript-ified everything, they changed it over to per user. And for better or worse, today, you could—there’s actually four different tiers of Microsoft 365. You could go for any one of those four for any distinct user.You could have one of them on F1, F3, E3, and E5. Now, if you do that, you create some other license non-compliance issues that we spend way too much time having to talk about during the boot camp, but the point is, you can buy to fit; it’s not one-size-fits-all necessarily. But you run into, very rapidly, if you deploy E5 for some number of users because the products that are there, the security services and compliance services ironically don’t do license compliance in most cases, customers can actually wind up creating new license compliance problems, thereby basically having to buy E5 for everybody. So, it’s a bit of a trapdoor that customers are not often aware of when they initially step into dabbling in Microsoft 365 E5.Corey: When you take a look at this across the entire board, what is your guidance to customers? Because honestly, this feels like it is a full-time job. At scale, a full-time job for a department simply keeping up with all of the various Microsoft licensing requirements, and changes because, as you say, it’s not static. And it just feels like an overwhelming amount of work that to my understanding, virtually no other vendor makes customers jump through. Sure there’s Oracle, but that tends to be either in a database story or a per developer, or on rare occasions, per user when you build internal Java apps. But it’s not as pervasive and as tricky as this unless I’m missing something.Wes: No, you’re not. You’re not missing anything. It’s very true. It’s interesting to think back over the years at the boot camp. There’s names I’ve heard that I don’t hear anymore in terms of companies that were as bad. But the reality is, you hear the names of the same software companies but, exactly to your point, they’re all departmental. The people who make [Roxio 00:16:26] still, they’re very departmentalized. Oracle, IBM, yeah, we hear about them still, but they are all absolutely very departmentalized.And Microsoft, I think one of the reason why we do get so many—for better or worse, for them—return visitors to our licensing boot camps that we do every two months, is for that exact reason, that some people have found they like outsourcing that part of at least trying to keep up with what’s going on, what’s the record? And so, they’ll come back every two, three, or four years and get an update. And we try to keep them updated on, you know, how do I color within the lines? Should it be like this? No. But it is this way.In fact, it’s funny, I think back, it was probably one of the first few boot camps I did with Rob. We were in New York and we had a very large customer who had gotten a personalized message from Microsoft talking about how they were going to simplify licensing. And we went to a cocktail hour afterwards, as we often do on the first day of the boot camp, to help people, you know, with the pain after a boot camp, and this gentleman asks us well, “So, what are you guys going to do once Microsoft simplifies licensing?” And Rob and I just, like, looked at each other, smiled, looked back at the guy, and laughed. We’re like, “We will cross that bridge when we get to it.”Corey: Yeah, people ask us that question about AWS billing. What if they fix the billing system? Like, we should be so lucky to live that long.Wes: I have so many things I’d rather be doing. Yes.Corey: Mm-hm. Exactly. It’s one of those areas where, “Well, what happens in a post-scarcity world?” Like, “I couldn’t tell you. I can’t even imagine what such a thing would look like.”Wes: Exactly [laugh]. Exactly.Corey: So, the last time we spoke way back, I think in 2019, Microsoft had wound up doing some unfortunate and fairly underhanded-appearing licensed changes, where it was more expensive to run a bunch of Microsoft things, such as server software, most notably SQL Server, on clouds that were not Azure. And then, because you know, you look up the word chutzpah in the dictionary, you’ll find the Microsoft logo there in response, as part of the definition, they ran an advertising campaign saying that, oh, running many cloud workloads on Azure was five times cheaper than on AWS. As if they cracked some magic secret to cloud economics. Rather than no, we just decided to play dumb games that win worse prizes with cloud licensing. How did that play out?Wes: Well, so they made those changes in October of 2019, and I kind of wish they’d become a bigger deal. And I wish they’d become a bigger deal earlier so that things could have been, maybe, reversed when it was easier. But you’re absolutely right. So, it—for those who don’t know, it basically made licensing changes on only AWS, GCP, and Alibaba—who I never had anybody ask me about—but those three. It also added them for Azure, but then they created loopholes for themselves to make Azure actually get beneficial licensing, even better than you could get with any other cloud provider [sigh].So, the net takeaway is that every Microsoft product that matters—so traditionally, SQL Server, Windows Server, Windows client, and Office—is not impossible to use on AWS, but it is markedly more expensive. That’s the first note. To your point, then they did do that marketing campaign that I know you and I probably had exchanges about at the time, and it drove me nuts as well because what they will classically do is when they tout the savings of running something on Azure, not only are they flouting the rules that they created, you know, they’re basically gloating, “Look, we got a toy that they didn’t,” but they’re also often removing costs from the equation. So, for example, in order for you to get those discounts on Azure, you have to maintain what’s called Software Assurance. You basically have to have a subscription by another name.If you don’t have Software Assurance, those opportunities are not available to you. Fine. That’s not my point. My point is this, that Software Assurance is basically 75% of the cost of the next version. So, it’s not free, but if you look at those 5x claims that they made during that time frame, they actually were hand-waving and waving away the [assay 00:20:45] costs.So, if you actually sat down and did the math, the 5x number was a lie. It was not just very nice, but it was wrong, literally mathematically wrong. And from a—as my colleague likes to say, a ‘colors person,’ not a numbers person like me, from a colors person like me, that’s pretty bad. If I can see the error and your math, that’s bad math.Corey: It just feels like it’s one of those taxes on not knowing some of the intricacies of what the heck is going on in the world of Microsoft licensing. And I think every sufficiently complex vendor with, shall we say, non-trivial pricing dimensions, could be accused of the same thing. But it always felt particularly worrisome from the Microsoft perspective. Back in the days of BSA audits—which I don’t know at all if they’re still a thing or not because I got out of that space—every executive that I ever spoke to, in any company lived in fear of them, not because they were pirating software or had decided, “You know what? We have a corporate policy of now acting unethically when it comes to licensing software,” but because of the belief that no matter what they came up with or whatever good faith effort they made to remain compliant, of course, something was not going to work the way they thought it would and they were going to be smacked with a fine. Is that still the case?Wes: Absolutely. In fact, I think it’s worse now than it ever was before. I will often say to customers that you are wildly uncompliant while also being wildly overcompliant because per your point about how broad and deep Microsoft is, there’s so many products. Like, every company today, every company that has Project and Visio still in place today, that still pays for it, you are over-licensed. You have more of it than you need.That’s just one example, but on the other side, SQL Server, odds are, every organization is subtly under-licensed because they think the rule is to do this, but the rules are actually more restrictive than they expect. So, and that’s why Microsoft is, you know, the first place they look, the first rug they look under when they do walk in and do an audit, which they’re entitled to do as a part of an organization’s enterprise agreement. So BSA, I think they do still have those audits, but Microsoft now they have their own business that does that, or at least they have partners that do that for them. And places like SQL Server are the first places that they look.Why? Because it’s big, found money, and because it’s extremely hard to get right. So, there’s a reason why, when we focus on our boot camps, we’ll often tell people, you know, “Our goal is to save you enough money to pay for the class,” because there’s so much money to be found in little mistakes that if you do a big thing wrong with Microsoft software, you could be wildly out of compliance and not know about it until Microsoft-or more likely, a Microsoft partner—points it out to you.Corey: It feels like it’s an inevitability. And, on some level, it’s the cost of doing business. But man, does that leave a sour taste in someone’s mouth.Wes: Mm-hm. It absolutely does. It absolutely does. And I think—you know, I remember, gosh, was it Munich that was talking about, “We’re going to switch to Linux,” and then they came back into the fold. I think the reality is, it absolutely does put a bad taste.And it doesn’t leave customers with good hope for where they go from here. I mean, okay, fine. So, we got burned on that thing in the Microsoft 365 stack. Now, they want us to pay 30 bucks for Copilot for Microsoft 365. What? And we’d have no idea what they’re even buying, so it’s hard to give any kind of guidance. So, it’s a weird time.Corey: I’m curious to see what the ultimate effect of this is going to be. Well, one thing I’ve noticed over the past decade and change—and I think everyone has as well—increasingly, the local operating system on people’s laptops or desktops—or even phones, to some extent—is not what it once was. Increasingly, most of the tools that I find myself using on a daily basis are just web use or in a browser entirely. And that feels like it’s an ongoing problem for a company like Microsoft when you look at it through the lens of OS. Which at some level, makes perfect sense why they would switch towards everything as a service. But it’s depressing, too.Wes: Yeah. I think that’s one of the reasons why, particularly after Steve left, they changed focus a lot and really begin focusing on Microsoft 365 as the platform, for better or worse. How do we make Microsoft 365 sticky? How do we make Office 365 sticky? And the thing about, like, the Microsoft 365 E5 security stuff we were talking about, it often doesn’t matter what the user is accessing it through. The user could be accessing it only through a phone, they could be a frontline worker, they could be standing at a sales kiosk all day, they could be using Office every single day, or they could be an exec who’s only got an iPad.The point is, you’re in for a penny, in for a pound at that point that you’ll still have to license the user. And so, Microsoft will recoup it either way. In some ways, they’ve learned to stop caring as much about, is everyone actively using our technology? And on the other side, with things like Teams, and as we’re seeing very, very slowly, with the long-delayed Outlook here, you know, they’re also trying to switch things to have that less Win32 surface that we’re used to and focus more on the web as well. But I think that’s a pretty fundamental change for Microsoft to try and take broadly and I don’t anticipate, for example, Office will ever be fully replaced with a fat client like it has on Windows and the Mac OS.Corey: Yeah, part of me wonders what the future that all looks like because increasingly, it feels more than a little silly that I’m spending, like, all of this ever-increasing dollar figure on a per-seat basis every year for all of Microsoft 365. Because we don’t use their email system. We don’t use so much of what they offer. We need basically Word and Excel and once in a blue moon PowerPoint, I guess. But that’s it. Our fundamental needs have not materially shifted since Office 2003. Other than the fact that everything uses different extensions now and there’s, of course, the security story on top of it, too. We just need some fairly basic stuff.Wes: And I think that’s the case for a lot of—I mean, we’re the exact same way at Directions. And I think that’s the case for a lot of small and even into mid-size companies. Microsoft has traditionally with the, like, Small Business Premium, they have an offering that they intentionally only scale up to 300 people. And sometimes they’ll actually give you perks there that they wouldn’t give away in the enterprise suite, so you arguably get more—if they let you have it, you get more than you would if you’ve got E5. On the other side, they’ve also begun, for enterprises, honing in on opportunities that they may have historically ignored.And when I was at Microsoft, you’d have an idea, like, “Hey, Bob. I got an idea. Can we try to make a new product?” He’s like, “Okay, is it a billion-dollar business?” And you get waved away if it wasn’t all a billion-dollar business. And I don’t think that’s the case anymore today, particularly if you can make the case, this thing I’m building makes Microsoft 365 sticky or makes Azure sticky. So, things like the Power Platform, which is subtly and slowly replacing Access at a minimum, but a lot of other tools.Power BI, which has come from behind. You know, people would look at it and say, “Oh, it’s no Excel.” And now it, I think, far exceeds Excel for that type of user. And Copilot, as I talked about, you know, Microsoft is definitely trying to throw things in that are beyond Office, beyond what we think of as Microsoft. And why are they doing that? Because they’re trying to make their platform more sticky. They’re trying to put enough value in there so you need to subscribe for every user in your organization.And even things, as we call them, ‘Batteries not Included’ like Copilot, that you’re going to buy E5 and that you’re still going to have to buy something else beyond that for some number of users. So, you may even have a picture in your head of how much it’s going to cost, but it’s like buying a BMW 5 Series; it’s going to cost more than you think.Corey: I wish that there were a better path forward on this. Honestly, I wish that they would stop playing these games, let you know Azure compete head-to-head against AWS and let it win on some of its merits. To be clear, there are several that are great. You know, if they could get out of their own way from a security perspective, lately. But there seems to be a little appetite for that. Increasingly, it seems like even customers asking them questions tends to hit a wall until, you know, a sitting US senator screams at them on Twitter.Wes: Mm-hm. No, and then if you look carefully at—Microsoft is very good at pulling just enough off of the sweater without destroying the sweater. And for example, what they did, they gave enough away to potentially appease, but they didn’t actually resolve the problem. They didn’t say, “All right, everybody gets logging if they have Microsoft 365 E3,” or, “Everybody gets logging, period.” They basically said, “Here’s the kind of logging you can get, and we’re going to probably tweak it a little bit more in the future,” and they will not tweak it more in the future. If anything, they’ll tighten it back up.This is very similar to the 2019 problem we talked about earlier, too, that you know, they began with one set of rules and they’ve had to revisit it a couple of times. And most of the time, when they’ve had an outcry, primarily from the EU, from smaller cloud providers in the EU who felt—justifiably—that Microsoft was being not—uncompetitive with Azure vis-à-vis every other cloud provider. Well, Microsoft turned around and last year changed the rules such that most of these smaller cloud providers get rules that are, ehh, similar to what Azure can provide. There are still exclusives that only Azure gets. So, what you have now is basically, if you’re a customer, the best set and cheapest set is with Azure, then these smaller cloud providers give you a secondary—it’s close to Azure, but still not quite as good. Then AWS, GCP, and Alibaba.So, the rules have been switched such that you have to know who you’re going to in order to even know what the rules are and to know whether you can comply with those rules with the thing you want to build. And I find it most peculiar that, I believe it was the first of last month that Microsoft made the change that said, “You’ll be able to run Office on AWS,” which was Amazon WorkSpaces, in particular. Which I think is huge and it’s very important and I’m glad they made this change, but it’s weird because it creates almost a fifth category because you can’t run it anywhere else in Amazon, like if you were spinning something up in VMware on Amazon, but within Amazon WorkSpaces, you can. This is great because customers now can run Office for a fee. And it’s a fee that’s more than you’d pay if you were running the same thing on Microsoft’s cloud.But it also was weird because let’s say Google had something competitive in VDI, but they don’t really, but if they had something competitive in VDI, now this is the benefit that Amazon has that’s not quite as good as what Microsoft has, that Google doesn’t get it at all. So, it’s just weird. And it’s all an attempt to hold… to both hold a market strategy and an attempt to grow market share where they’re still behind. They are markedly behind in several areas. And I think the reality is, Amazon WorkSpaces is a really fine offering and a lot of customers use it.And we had a customer at our last in-person boot camp in Atlanta, and I was really impressed—she had been to one boot camp before, but I was really impressed at how much work she’d put into making sure we know, “We want to keep using Amazon WorkSpaces. We’re very happy with it. We don’t want to move anywhere else. Am I correct in understanding that this, this, this, and this? If we do these things will be aboveboard?” And so, she knew how much more she’d have to pay to stay on Amazon WorkSpaces, but it was that important to the company that they’d already bet the farm on the technology, and they didn’t want to shift to somebody else that they didn’t know.Corey: I’m wondering how many people have installed Office just through a standard Microsoft 365 subscription on a one-off Amazon WorkSpace, just because they had no idea that that was against license terms. I recall spinning up an Amazon WorkSpace back when they first launched, or when they wound up then expanding to Amazon Linux; I forget the exact timeline on this. I have no idea if I did something like that or not. Because it seems like it’d be a logical thing. “Oh, I want to travel with just an iPad. Let me go ahead and run a full desktop somewhere in the cloud. Awesome.”That feels like exactly the sort of thing an audit comes in and then people are on the hook for massive fines as a result. It just feels weird, as opposed to, there are a number of ways to detect you’re running on a virtual machine that isn’t approved for this. Stop the install. But of course, that doesn’t happen, does it?Wes: No. When we teach at the boot camp, Rob will often point out that, you know, licensing is one of the—and it’s true—licensing is one of the last things that comes in when Microsoft is releasing a product. It was that way when he was at the company before I was—he shipped Word 1.0 for the Mac, to give you an idea of his epoch—and I was there for XP, like I said, which was the first version that used activation—which was a nightmare—there was a whole dedicated team on. And that team was running down to the wire to get everything installed.And that is still the case today because marketing and legal make decisions about how a product gets sold. Licensing is usually tacked on at the very end if it gets tacked on at all. And in fact, in a lot of the security, compliance, and identity space within Microsoft 365, there is no license compliance. Microsoft will show you a document that, “Hey, we do this,” but it’s very performative. You can’t actually rely on it, and if you do rely on it, you’ll get in trouble during an audit because you’ve got non-compliance problems. So yeah, it’s—you would hope that it keeps you from coloring outside the lines, but it very much does not.Corey: It’s just a tax on going about your business, in some ways [sigh].Wes: Exactly. “Don’t worry, we’ll be back to fix it for you later.”Corey: [laugh]. I really appreciate your taking the time to go through this with me. If people want to learn more, where’s the best place for them to keep up with what you’re up to?Wes: Well, obviously, I’m on Twitter, and—oh, sorry, X, whatever.Corey: No, we’re calling it Twitter.Wes: Okay, I’m on—I’m on—[laugh] thank you. I’m on Twitter at @getwired. Same alias over on [BlueSky 00:35:27]. And they can also find me on LinkedIn, if they’re looking for a professional question beyond that and want to send a quiet message.The other thing is, of course, go to directionsonmicrosoft.com. And directionsonmicrosoft.com/training if they’re interested in one of our licensing boot camps. And like I said, Rob, and I do those every other month. We’re increasingly doing them in person. We got one in Bellevue coming up in just a few weeks. So, there’s opportunities to learn more.Corey: Excellent. And we will, of course, put links to that in the [show notes 00:35:59]. Thank you so much for taking the time to chat with me again, Wes. It’s appreciated.Wes: Thank you for having me.Corey: Wes Miller, Research VP at Directions on Microsoft. I’m Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice, along with an angry, insulting comment that will no doubt be taken down because you did not sign up for that podcasting platform’s proper license level.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.

Thomas LaRock, Principal Developer Evangelist at Selector AI, joins Corey on Screaming in the Cloud to discuss why he loves having a career in data and his most recent undertaking at Selector AI. Thomas explains how his new role aligned perfectly with his career goals in his recent job search, and why Selector AI is not in competition with other data analysis tools. Corey and Thomas discuss the benefits and drawbacks to going back to school for additional degrees, and why it’s important to maintain a healthy balance of education and practical experience. Thomas also highlights the impact that data can have on peoples’ lives, and why he finds his career in data so meaningful. About ThomasThomas’ career and life experiences are best described as follows: he takes things that are hard and makes them simple for others to understand. Thomas is a highly experienced data professional with over 25 years of expertise in diverse roles, from individual contributor to team lead. He is passionate about simplifying complex challenges for others and leading with empathy, challenging assumptions, and embracing a systems-thinking approach. Thomas has strong analytical reasoning skills and expertise to identify trends and opportunities for significant impact, and is a builder of cohesive teams by breaking down silos resulting in increased efficiencies and collective success. He has a track record of driving revenue growth, spearheading industry-leading events, and fostering valuable relationships with major tech players like Microsoft and VMware. Links Referenced: Selector: https://www.selector.ai/ LinkedIn: https://www.linkedin.com/in/sqlrockstar/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: Do you wish there were cheat codes for database optimization? Well, there are – no seriously. If you’re using Postgres or MySQL on Amazon Aurora or RDS, OtterTune uses AI to automatically optimize your knobs and indexes and queries and other bits and bobs in databases. OtterTune applies optimal settings and recommendations in the background or surfaces them to you and allows you to do it. The best part is that there’s no cost to try it. Get a free, thirty-day trial to take it for a test drive. Go to ottertune dot com to learn more. That’s O-T-T-E-R-T-U-N-E dot com.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. There are some guests I have been nagging-slash-angling to have on this show for years on end, and that you almost give up, until they wind up having a job change. At which point, there’s no better opportunity to pounce like some sort of scavenger or hyena or whatnot in order to get them on before their new employer understands what I am, and out of an overabundance of caution, decides not to talk with me. Thomas LaRock is a recently minted Principal Developer Evangelist at Selector. Thomas, thank you for finally deigning to appear on the show. It is deeply appreciated.Thomas: Oh, thanks for having me. Thanks for extending invitation. I’m sorry. It’s my fault I haven’t come here before now; it’s just been one of those scheduling things. And I always think I’m going to see you. Like, I’ll go to re:Invent, and I’m like, “I’ll see Corey there.” And then, nah, Corey is a little busy.Corey: Yeah, I have no recollection of basically anything that ever happens at re:Invent, just because it is eight days of ridiculous Cloud Chanukah and thing to thing to thing to thing to thing. It’s just overload and I wind up effectively blocking all of it out. You are one of those very interesting people where, depending upon the context in which someone encounters you, it’s difficult to actually put a finger on where you start and where you stop. You are, for example, a Microsoft MVP, which means you presumably have a fair depth of experience with at least some subset of Microsoft products. You have been working at SolarWinds for a while now, and you also have the username of SQLRockstar on a number of social media environments, which leads me to think, oh, you’re a database person. What are you exactly? Where do you start? Where do you stop?Thomas: Yeah, in my heart-of-hearts, a data professional. And that can mean a lot of things to a lot of different people. My latest thing I’ve taken from a friend where I just call myself a data janitor because that’s pretty much what I do all day, right? I’ll clean data up, I’ll move it around, it’s a pile here and a pile there. But that’s my heart of hearts. I’ve been a database administrator, I’ve been the data advocate. I’ve done a lot of roles, but it’s always been heavily focused on data.Corey: So, these days, your new role—let’s start at the present and see if we work our way backwards or not—you’ve been, at the time of this recording, in your role for a week where you are a principal developer evangelist at Selector, which to my understanding, is an AIOps or MLOps or whatever buzzword that we’re sprinkling on top of things today is, which of course presupposes having some amount of data to wind up operating on. What do you folks do over there?Thomas: That’s a great question. I’m hoping to figure that out eventually. No. So, here’s the thing, Corey. So, when I started my unforced sabbatical this past June, I was, of course, doing what everybody does: panicking. And I was looking for job opportunities just about anywhere.But I, again, data professional. I really wanted a role that would allow me to use my math skills—I have a master’s in mathematics—I wanted to use those math and analytical skills and go beyond the data into the application of the data. So, in the past five, six years, I’ve been earning a lot of data science certifications, I’ve been just getting back into my roots, right, statistical analysis, even my Six Sigma training is suddenly relevant again. So, what happened was I was on LinkedIn and friend had posted a note and mentioned Selector. I clicked on the link, and [all of sudden 00:04:17] I read, I go, “So, here’s a company that is literally building new tools and it’s data-science-centric. Is data-science-first.”It is, “We are going to find a way to go through your data and truly build out a better set of correlations to get you a signal through the noise.” Traditional monitoring tools, you know, collect a lot of things and then they kind of tell you what’s wrong. Or you’re collecting a lot of different things, so they slap, like, I don’t know, timestamps in there and they guess at correlations. And these people are like, “No, no, no. We’re going to go through everything and we will tell you what the data really says about your environment.”And I thought it was crazy how at the moment I was looking for a role that involve data and advocacy, the moment I’m looking for that role, that company was looking for someone like me. And so, I reached out immediately. They wanted not just a resume, but they’re like, where’s your portfolio? Have you spoken before? I’m like, “Yeah, I’ve spoken in a couple places,” right?So, I gave them everything, I reached right out to the recruiter. I said, “In case it doesn’t arrive, let me know. I’ll send it again. But this sounds very interesting.” And it didn’t take more than—Corey: Exactly. [unintelligible 00:05:24] delivery remains hard.Thomas: Yeah. And it didn’t take more than a couple of weeks. And I had gone through four or five interviews, they said that they were going to probably fly me out to Santa Clara to do, like, a last round or whatever. That got changed at some point and we went from, “Hey, we’ll have you fly out,” to, “Hey, here’s the offer. Why don’t you just sign?” And I’m like, “Yeah, I’ll start Monday. Let’s go.”Corey: Fantastic. I imagine at some point, you’ll be out in this neck of the woods just for an off-site or an all-hands or basically to stare someone down when you have a sufficiently large disagreement.Thomas: Yes, I do expect to be out there at some point. Matter of fact, I think one of my trips coming up might be to San Diego if you happen to head down south.Corey: Oh, I find myself all over the place these days, which is frankly, a welcome change after a few years of seclusion during the glorious pandemic years. What I like about Selector’s approach, from what I can tell at least, is that it doesn’t ask all of its customers to, “Hey, you know, all that stuff that you’ve instrumented over the last 20 years with a variety of different tools in the observability pipeline? Yeah, rip them all out and replace them with our new shiny thing.” Which never freaking happens. It feels like it’s a better step toward meeting folks where they are.Thomas: Yeah. So, we’re finding—I talk like I’ve been there forever: “What we’re finding,”—in the past 40 hours of my work experience there, what we’re finding, if you just look at the companies that are listed on the website, you’ll get an idea for the scale that we’re talking about. So no, we’re not there to rip and replace. We’re not going to show up and tell you, “Yeah, get rid of everything. We’re going to do that for you.”Matter of fact, we think it’s great you have all of those different things because it just reflects the complexity of your environment right now, is that you’ve grown, you’ve got so many disparate systems, you’ve got some of the technologies trying to monitor it all, and you’re really hoping to have everything rolled into one big dashboard, right? Instead of right now, you’ve got to go through three, four, or five dashboards, to even think you have an idea of the problem. And you never really—you guess. We all guess. We think we know where it is, and you start looking and then you figure it out.But yeah, we take kind of a different approach right from the start, and we say, “Great, you’ve got all that data? Ingest it. Bring it right to us, okay? We don’t care where it comes from, we can bring it in, and we can start going through it and start giving you true actionable insights.” We can filter out the noise, right, instead of one node going down, triggering a thousand alerts, we can just filter all of that out for you and just let you focus on the things that you need to be looking at right now.Corey: One of the things that I think gets overlooked in this space a lot is, “Well, we have this tool that does way better than that legacy tool that you’re using right now and it’s super easy to do a just drop-in replacement with our new awesomeness.” Great. What that completely misses is that there are other business units who perhaps care about data interchange and the idea that yeah, thing’s a legacy piece of junk and replacing it would take an afternoon. And then it would take 14 years to wind up redoing all the other reports that other things are generating downstream of that because they integrate with that thing. So yeah, it’s easy to replace the thing itself, but not in a way that anything else can take advantage of it.Thomas: Right.Corey: And when it turns out also when you sit there making fun of people’s historical technological decisions, they don’t really like becoming customers as it turns out. This was something of a shock for an awful lot of very self-assured startup founders in the early days.Thomas: Yeah. And again, you’re talking about how, you know some of the companies we’re looking at, it’s y—we don’t want to rip and replace things. Like you just said, you’ve got an ecosystem. It’s a delicate ecosystem that has [laugh] developed over time. We aren’t interested in replacing all that. We want to enhance it, we want to be on top of it and amplify what’s in there for you.So yeah, we’re not interested in coming in and say, “Yeah, rip every tool out.” And in some ways, when somebody will ask, you know, “Who do you compete with?” I’ll go, “Nobody.” Because I’m not looking to replace anybody. I’m looking to go on top.And again, the companies we’re dealing with have lots of data. We’re talking very large companies. Some of these are the backbone of the internet. They just have way too much data for any of these legacy tools to help with, you know? They can help with, like, little things, but in terms of making sense of it all, in terms of doing the real big data analytics, yeah, that’s where our tool comes in and it really shines.Corey: Yeah, it turns out that is not a really compelling sales pitch to walk it and say, “Hey, listen up, idiots, you all are doing it wrong. Now, pay me and we’ll do it right.” Yeah, even if you’re completely right, you’ve already lost the room at that point.Thomas: Exactly.Corey: People make decisions based upon human aspects, not about arithmetic, in most cases. I will say, taking a glance at the website, a couple of things are very promising. One, your picture and profile are already up there, which is good. No one is still on the fence about that, and further as a bonus, they’ve taken your job role down off the website, which is always disconcerting when you’re there and, “Why is that job still open?” “Oh, we’re preserving optionality. Don’t you worry your head about that. We’ve got it.” No one finds that a reassuring story when it’s about the role that they’re in. So, good selection.Thomas: I went to—after I signed, it was within the day, I went to send somebody the link to the job req. Like, they’re like, “What are”—I go, “Here, let me show you.” It was already down. The ink was even dry on the DocuSign and it was already down. So, I thought that—Corey: Good on them.Thomas: —was a good sign, too.Corey: Oh, yeah. Now, looking at the rest of your website, I do see a couple of things that lead to natural questions. One of the first things I look at on a web page is, okay, how is this thing priced? Because you always want to see the free tier option when I’m trying to solve a problem the middle of the night that I can just sign up for and see if it works for a small use case, but you also, in a big company definitely want to have the ‘Contact Us’ option because we’re procurement and we don’t know how to sign a deal that doesn’t have two commas in it with a bunch of special terms that ride along with it. Selector does not at the time of this recording, have a pricing page at all, which usually indicates if you have to ask, it might not be for you.Then I look at your customer case studies and they talk about very large enterprises, such as a major cable operator, for example, or TracFone. And oh okay, yeah, that is probably not the scale that I tend to be operating at. So, if I were to envision this as a carnival ride and there’s a sign next to it, “You must be at least this tall to ride,” how tall should someone be?Thomas: That is a great way of putting it and I would—I can’t really go into specifics because I’m still kind of new. But my understanding—Corey: Oh yeah. Make sweeping policy statements about your new employer 40 hours in. What could possibly go wrong?Thomas: My understanding is the companies that we—that are our target market today are fairly large enterprises with real data challenges, real monitoring data challenges. And so no, we’re not doing—it’s not transactional. You can’t just come to our website and say, “Here, click this, you’ll be up and running.” Because the volumes of data we’re talking about, this requires a little bit of specialty in helping make sure that things are getting set up and correct.Think of it this way. Like if somebody said, “Here, do the statistical analysis on whatever, and here’s Excel and go at it and get me that report by the end of the day and tell me how we’re doing,” most people would be like, “I don’t have enough information on that. Can you help me?” So, we’re still at that, hey, we’re going to need to help you through this and make sure it’s correctly configured. And it’s doing what you expect. So, how tall are you? I think that goes both ways. I think you’re at a height where you still need some supervision [laugh]. Does that make sense?Corey: I think that’s probably a good way of framing it. It’s a—again, I’m not saying that you should never ever, ever, ever have a ‘you must contact us to get started.’ There are a bunch of products like that out there. It turns out that even at The Duckbill Group here, we always want to have a series of conversations first. We don’t have a shopping cart that’s, “One consulting, please,” just because we’ll get into trouble with that.Though I think our first pass offering of a two-day engagement might have one of those somewhere still lurking around. Don’t quote me on that. Hell is other people’s websites. It’s great. But your own yeah, whoever reads that thing“. Wait, we’re saying what?” Don’t quote me on any of that, my God.Thomas: But I think that’s a good way of putting it. Like, you want to have some conversations first. Yeah, so you—and again, we’re still, we’re fairly young. We’ve only—we’re Series A, so we’ve been around 16 months, like… you know, the other website you’re looking at is probably going to change within the next six or eight weeks just because information gets outdated—Corey: It already has. It put your picture on it.Thomas: Right. But I mean, things are going to things move pretty fast with startups, especially this one. So, I just expect that over time, I envision some type of a free tier, but we’re not there yet.Corey: That’s one of those challenges as far as in some cases moving down market. I found that anything that acts like a security tool, for example, has to, on some level, charge enough to be worth the squeeze. One of the challenges there is, I’m either limited for anything that does CloudTrail analysis over in AWS-land, for example. I can either find a bunch of janky things off GitHub or I can spend what starts at $1,000 a month and increases rapidly from there, which is about twice the actual AWS bill that it would wind up alerting on. Not that the business value isn’t there, but because a complex sale is, in many cases, always going to be attendant with some of these products, so why not go after the larger companies where the juice is worth the squeeze rather than the folks who are not going to see the value and it’d be just as challenging to wind up launching a sale into?The corollary, of course, is that some of those small companies do in fact, grow meteorically. But it’s a bit of a lottery.Thomas: Yep.Corey: Ugh. So, I have to ask as well, while we’re talking about strange decisions that people might have made, in the world of tech, in many cases, when someone gets promoted—like, “So, does that mean extra money?” “No, not really. We just get extra adjectives added to our job title.” Good for us. You have decided to add letters in a different way, by going back for a second master’s degree. What on earth would possess you to do such a thing?Thomas: I—man, that is—you know, so I got my first master’s degree because I thought I was going to, I thought I was be a math teacher and basketball coach. And I had a master’s degree in math and I thought that was going to be a thing. I’ll get a job, you know, coaching and teaching at some small school somewhere. But then I realized that I enjoyed things like eating and keeping the wind off me, and so I realized I had to go get a jobby-job. And so, I took my masters in math, I ended—I got a job as a software analyst, and just rolled that from one thing to another until where I am today.But about four years ago, when I started falling back in love with my roots in math, and statistical analysis became a real easy thing for people to really start doing for themselves—well actually, that was about eight years ago—but the past four or five years, I’ve been earning more certifications in data science technologies. And then I found this program at Georgia Tech. So, Georgia Tech has an online masters of science and data analytics. And it’s extremely affordable. So, I looked at a lot of programs, Corey, over the past few years, especially during the pandemic.I had some free time, so I browsed the love these places, and they were charging 50, $60,000 and you had to do it within two, three years. And in one case, the last class you had to take, your practicum, had to be all done on campus. So, you had to go, like, live somewhere. And I’m looking at all—none of that was practical. And all of a sudden, somebody shows up and goes, “So, you can go online, fully online, Georgia Tech, $275 a credit. Costs ten grand for the entire program.”And you can—it’s geared towards a working professional and you can take anywhere from two to six years. So, you take, like, one class a semester if you want, or two or even three if they allow you, but they usually restrict you. So, it just blew my mind. Like, this exists today that I can start earning another Master’s degree in data analytics and I’ll say, be… classically trained in how—it’s funny because when I learn things in class, I’m like, I feel like I’m Thornton Melon in Back to School, and I’m just like, “Oh, you left out a bunch of stuff. That isn’t how you do it all,” right?That’s kind of my reaction. I’m like, “Calm down. I’m sure the professor has point. I’ll hear [laugh] him out.” But to me, you asked why, and I just the challenge. Am I really good at what I do? Like, I feel I am. I already have a master’s degree. I’m not worried about the level of work and the commitment involved in earning another one.I just wanted to show to myself that could—I want to learn and make sure I can do things like code in Python. If anybody has a chance to take a programming class, a graduate-level programming classes at Georgia Tech, you should do it. You should see where your skills rate at that level, right? So, it was for the challenge. I want to know if I can do it. I’m three classes in. I just started my fourth, actually, today was the start of the fall semester.And so, I’m about halfway through, and I’m loving it. It’s not too taxing. It’s just the right speed for me. I get to do it in my leisure hours as they were. Yeah, so I did it for the challenge. I’m really glad I’m doing it. I encourage anybody interested in obtaining a degree in data analytics to look at the Georgia Tech program. It’s well worth it. Georgia Tech’s not a bad school. Like, if you had to go to school in the South, it’s all right.Corey: I always find it odd, just, you had your first master’s degree in, you know, mathematics, and now you’re going for data analytics, which sounds like mathematics with extra steps.Thomas: It is.Corey: Were there opportunities that you were hoping to pursue that were not available to you with just the one master’s degree?Thomas: So, it’s interesting you say that because I’m so old that when I went to school, all we had was math, that was it. It was pure mathematics. I could have been a statistics major, I think, and computer science was a thing. And one day I met a guy who transferred into math from computer science. I’m like, “Why would you do that? What are you going to do with the degree in math?”And his response is, “What am I going to do with a degree in computer science?” And I look back and I realized how we were both right. So, I think at the time if there had been a course in applied mathematics, that would have piqued my interest. Like, what am I going to do with this math degree other than become an actuary because that was about all I knew at the time. You were a teacher or an actuary, and that was about it.So, the idea now that they have these programs in data analytics or data science that are little more narrow of focus, like, “This is what we’re going to do: we’re going to apply a little bit of math, some calculus, some stats; we’re going to show you how to build your own simulations; we’re going to show you how to ask the right questions of the data.” To give you a little bit of training. Because they can’t teach you everything. You really have to have real-world experience in whatever domain you’re going to focus on, be it finance or marketing or whatever. All these bright financial operations, that’s just analytics for finance, marketing operations, that’s analytics for marketing. It’s just, to me, I think just the opportunity to have that focus would have been great back then and it didn’t exist. And I want to take advantage of it now.Corey: I’ve always been a fan of advising people who ask me, “Should I go back to school,” because usually, there’s something else driving that. Like, I am honestly not much of a career mentor. My value basically comes in as being a horrible warning to others. On paper, I have an eighth-grade education. I am not someone to follow for academic approaches.But when someone early or mid-career asks, “Should I get another degree?” Unpacking that is always a bit of a fun direction for me to go in. Because at some level, we’ve sold entire generations a bill of goods, where oh, if you don’t know what to do, just get more credentials and then your path will be open to you in a bunch of new and exciting ways. Okay, great. I’m not saying that’s inherently wrong, but talk to people doing the thing you’d want to do after you have that degree, maybe, you know, five or six years down the professional line from where you are and get their take on it.Because in some cases, yeah, there are definite credentials you’re going to need—I don’t want you to be a self-taught surgeon, for example—but there are other things where it doesn’t necessarily open doors. People are just reflexively deciding that I’m going to go after that instead. And then you can start doing the math of, okay, assume that you have whatever the cost of the degree is in terms of actual cost and opportunity cost. Is this the best path forward for you to wind up getting where you want to go? It sounds like in your particular case, this is almost a labor of love or a hobby style of approach, as opposed to, “Well, I really want Job X, but I just can’t get it without the right letters after my name.” Is that a fair assessment?Thomas: It’s not unfair. It is definitely fair, but I would also say, you know, if somebody came and said, “Hey Tom, we need somebody to run our data science team or our data engineering team,” I’ve got the experience for—the only thing I would be lacking is, you know, production experience, like, with machine-learning pipelines or something. I don’t have that today.Corey: Which is basically everyone else, too, but that’s a little—bit of a quiet secret in the industry.Thomas: Yeah, that’s—okay. Bad example. But you know what I’m saying is that the only thing I’d be lacking would be that practical experience, so this is one way that—to at least start that little bit of experience, especially with the end result being the practicum that we’ll be doing. It’s, like, six credits at the very end. So yes, it’s a fair thing.I wouldn’t—hobby isn’t really the right—this is really something that makes me get out of bed in the morning. I get to work with data today and I’m going to get—I’m going to tell a great story using data today. I really do enjoy those things. But then at the tail end of this, if it happens to lead to a position that somebody says, “Hey, we need somebody, vice president of data engineering. This a really good”—honestly, the things I look for are the roles and the roles I want are to have a role that allows me to really have an impact on other people’s lives.And that’s one of the things about Selector. The things that we’re able to do for these admins that are just drowning in data, the data is just in their way, and that we can help them make sense of it all, to me, that’s impactful. So, those are the types of roles that I will be looking for as well in the future, especially at the high level of something data science-y.Corey: I think that that is a terrific example of what I’m talking about. Because I’ve met a number of folks, especially very early-20s range where, okay, they’ve gotten the degree, but now they don’t know what to do because every time they’re applying for jobs, it doesn’t seem to work for them. You’ve been around this industry for 25 years. Everyone needs a piece of paper that says they know certain things, and in your case, it long ago transitioned into being—I would assume—your resumé, the history of things you have done that look equivalent. Part of me, on some level, wonders if there isn’t an academic snobbery going on at some level, where a number of teams are, “Oh, we’d love to have you in, but you don’t have a PhD.”And then people get the PhD. “From the right school, in the right area of concentration.” It’s like, you just keep moving these very expensive goalposts super quickly. Remember, I have an eighth-grade education. I’m not coming at this from a place of snobbery and I’m also not one of those folks who’s well it didn’t work for me, therefore, it won’t work for anyone else either because that’s equally terrible in a different direction.It’s just making sure that people are going into these things with their eyes open. With you, it’s never been a concern. You’ve been around this industry so long that it is extremely unlikely to me [laugh] that you, “Oh, wait. You mean a degree won’t magically solve all of my problems and regrow some of my hair and make me two inches taller, et cetera, et cetera?” But yeah, do I remember in the early days just how insipid and how omnipresent that pressure was.Thomas: Yeah. I’ve been at companies where we’ve brought in people because of the education and—or I’m sorry. Let’s be more specific. I’ve been at companies where we’ve sent current employees—as we used to call it—off the charm school, which is basically [MBA 00:25:44].Corey: [laugh].Thomas: And I swear, so many of them came back and they just forgot how to think, how to have common sense. Like, they were very much focused on one particular thing and this is just it, and they forgot there were maybe humans involved, and maybe look for a human answer instead of the statistically correct one. So, I think that was a good thing for me as well to be around that because, yeah, somebody put it me best years ago: “Education by itself isn’t enough. If you combine education with motivation, now you’ve really got something.” And your case, I don’t know where you went for eighth grade, it could have been the best eighth-grade program ever, but you definitely have the motivation through the years to overcome anything that might have been lacking in the form of education. So, it’s really the combination—Corey: Oh, you’d be surprised. A lot of those things are still readily apparent to people who work with me, so I’ve done a good job of camouflaging them. Hazzah.Thomas: Just it’s, you got to have both. You can’t just rely on one or the other.Corey: So, last question, given that you are the data guy and SQLRockstar is your username in a bunch of places. What’s the best database? I mean, I would always say it’s Route 53, but I understand that can be controversial for some folks, given that their SQL implementation is not yet complete. What’s your take?Thomas: So clearly, I’m partial to anything inside the Microsoft data platform, with the exception being Access. I think if Access disappeared from the universe… society might be better off. But that’s for a different day, I think the best database is the one that does the job you need it to do. Honestly, the database shouldn’t really matter. It’s just an abstraction. The database engine is just something in between you and the data you need, right?So, whatever you’re using, if it’s doing the job that you need it to do, then that’s the best database you could have. I learned a long time ago to not pick sides, choose fiefdoms. Like, it just didn’t matter. It’s all kind of the same. And in a lot of cases, if you go to, like, the DB-Engines Rankings, you’ll see how many of these systems these days, there’s a lot of overlap. They offer all the same features and the differences between them are getting smaller and smaller in a lot of cases. So yeah, it’s… you got to database, it does what you need to do? That’s great. That’s the best database.Corey: Especially since any database, I suspect, can be made to perform a given task, even if sub-optimally. Which states back to my core ethos of, quite frankly, anything is a database if you hold it wrong.Thomas: Yeah, it really is. I mean, we’ve had those discussions. I kid about Access because it’s just a painful thing for a lot of different reasons. But is Excel a database? And I would say no but, you know—because it can’t do certain things that I would expect a relational engine to do. And then you find out, well, I can make it do those things. So, now is it a database? And, yeah…Corey: [laugh]. Yeah. Well, what if I apply some brute force? Will it count then? Like, you have information, Thomas. Can I query you?Thomas: Yes. Yes, yes, [laugh] you can. I also have latency.Corey: Exactly. That means you are a suboptimal database.Thomas: [laugh].Corey: Good job. I really want to thank you for taking the time to talk about what you’re up to these days and finally coming on the show. If people want to learn more, where’s the best place for them to find you?Thomas: Well, I’m becoming more active on LinkedIn. So, it’s linkedin/in/sqlrockstar. Just search for SQLRockstar, you’ll find me everywhere. I mean, I do have a blog. I rarely blog these days. Most of the posts I do is over at LinkedIn.And you might find me at some networking events coming up since Selector really does focus on network observability. So, you could see me there. And you know what? I’m also going to have an appearance on the Screaming in the Cloud podcast, so you can listen to me there.Corey: Excellent. And I imagine that’s the one we don’t have to put into these [show notes. 00:29:44]. Thank you so much for taking the time to speak with me. I really do appreciate it.Thomas: Thanks for having me, Corey. I look forward to coming back.Corey: As I look forward to seeing you again over here. Thomas LaRock, Principal Developer Evangelist at Selector. I’m Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice along with an insulting comment because then we’re going to use all those together as a distributed database.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.

Tony Baer, Principal at dbInsight, joins Corey on Screaming in the Cloud to discuss his definition of what is and isn’t a database, and the trends he’s seeing in the industry. Tony explains why it’s important to try and have an outsider’s perspective when evaluating new ideas, and the growing awareness of the impact data has on our daily lives. Corey and Tony discuss the importance of working towards true operational simplicity in the cloud, and Tony also shares why explainability in generative AI is so crucial as the technology advances. About TonyTony Baer, the founder and CEO of dbInsight, is a recognized industry expert in extending data management practices, governance, and advanced analytics to address the desire of enterprises to generate meaningful value from data-driven transformation. His combined expertise in both legacy database technologies and emerging cloud and analytics technologies shapes how clients go to market in an industry undergoing significant transformation. During his 10 years as a principal analyst at Ovum, he established successful research practices in the firm’s fastest growing categories, including big data, cloud data management, and product lifecycle management. He advised Ovum clients regarding product roadmap, positioning, and messaging and helped them understand how to evolve data management and analytic strategies as the cloud, big data, and AI moved the goal posts. Baer was one of Ovum’s most heavily-billed analysts and provided strategic counsel to enterprises spanning the Fortune 100 to fast-growing privately held companies.With the cloud transforming the competitive landscape for database and analytics providers, Baer led deep dive research on the data platform portfolios of AWS, Microsoft Azure, and Google Cloud, and on how cloud transformation changed the roadmaps for incumbents such as Oracle, IBM, SAP, and Teradata. While at Ovum, he originated the term “Fast Data” which has since become synonymous with real-time streaming analytics.Baer’s thought leadership and broad market influence in big data and analytics has been formally recognized on numerous occasions. Analytics Insight named him one of the 2019 Top 100 Artificial Intelligence and Big Data Influencers. Previous citations include Onalytica, which named Baer as one of the world’s Top 20 thought leaders and influencers on Data Science; Analytics Week, which named him as one of 200 top thought leaders in Big Data and Analytics; and by KDnuggets, which listed Baer as one of the Top 12 top data analytics thought leaders on Twitter. While at Ovum, Baer was Ovum’s IT’s most visible and publicly quoted analyst, and was cited by Ovum’s parent company Informa as Brand Ambassador in 2017. In raw numbers, Baer has 14,000 followers on Twitter, and his ZDnet “Big on Data” posts are read 20,000 – 30,000 times monthly. He is also a frequent speaker at industry conferences such as Strata Data and Spark Summit.Links Referenced:dbInsight: https://dbinsight.io/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is brought to us in part by our friends at RedHat.As your organization grows, so does the complexity of your IT resources. You need a flexible solution that lets you deploy, manage, and scale workloads throughout your entire ecosystem. The Red Hat Ansible Automation Platform simplifies the management of applications and services across your hybrid infrastructure with one platform. Look for it on the AWS Marketplace.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. Back in my early formative years, I was an SRE sysadmin type, and one of the areas I always avoided was databases, or frankly, anything stateful because I am clumsy and unlucky and that’s a bad combination to bring within spitting distance of anything that, you know, can’t be spun back up intact, like databases. So, as a result, I tend not to spend a lot of time historically living in that world. It’s time to expand horizons and think about this a little bit differently. My guest today is Tony Baer, principal at dbInsight. Tony, thank you for joining me.Tony: Oh, Corey, thanks for having me. And by the way, we’ll try and basically knock down your primal fear of databases today. That’s my mission.Corey: We’re going to instill new fears in you. Because I was looking through a lot of your work over the years, and the criticism I have—and always the best place to deliver criticism is massively in public—is that you take a very conservative, stodgy approach to defining a database, whereas I’m on the opposite side of the world. I contain information. You can ask me about it, which we’ll call querying. That’s right. I’m a database.But I’ve never yet found myself listed in any of your analyses around various database options. So, what is your definition of databases these days? Where do they start and stop? Tony: Oh, gosh.Corey: Because anything can be a database if you hold it wrong.Tony: [laugh]. I think one of the last things I’ve ever been called as conservative and stodgy, so this is certainly a way to basically put the thumbtack on my share.Corey: Exactly. I’m trying to normalize my own brand of lunacy, so we’ll see how it goes.Tony: Exactly because that’s the role I normally play with my clients. So, now the shoe is on the other foot. What I view a database is, is basically a managed collection of data, and it’s managed to the point where essentially, a database should be transactional—in other words, when I basically put some data in, I should have some positive information, I should hopefully, depending on the type of database, have some sort of guidelines or schema or model for how I structure the data. So, I mean, database, you know, even though you keep hearing about unstructured data, the fact is—Corey: Schemaless databases and data stores. Yeah, it was all the rage for a few years.Tony: Yeah, except that they all have schemas, just that those schemaless databases just have very variable schema. They’re still schema.Corey: A question that I have is you obviously think deeply about these things, which should not come as a surprise to anyone. It’s like, “Well, this is where I spend my entire career. Imagine that. I might think about the problem space a little bit.” But you have, to my understanding, never worked with databases in anger yourself. You don’t have a history as a DBA or as an engineer—Tony: No.Corey: —but what I find very odd is that unlike a whole bunch of other analysts that I’m not going to name, but people know who I’m talking about regardless, you bring actual insights into this that I find useful and compelling, instead of reverting to the mean of well, I don’t actually understand how any of these things work in reality, so I’m just going to believe whoever sounds the most confident when I ask a bunch of people about these things. Are you just asking the right people who also happen to sound confident? But how do you get away from that very common analyst trap?Tony: Well, a couple of things. One is I purposely play the role of outside observer. In other words, like, the idea is that if basically an idea is supposed to stand on its own legs, it has to make sense. If I’ve been working inside the industry, I might take too many things for granted. And a good example of this goes back, actually, to my early days—actually this goes back to my freshman year in college where I was taking an organic chem course for non-majors, and it was taught as a logic course not as a memorization course.And we were given the option at the end of the term to either, basically, take a final or  do a paper. So, of course, me being a writer I thought, I can BS my way through this. But what I found—and this is what fascinated me—is that as long as certain technical terms were defined for me, I found a logic to the way things work. And so, that really informs how I approach databases, how I approach technology today is I look at the logic  on how things work. That being said, in order for me to understand that, I need to know twice as much as the next guy in order to be able to speak that because I just don’t do this in my sleep.Corey: That goes a big step toward, I guess, addressing a lot of these things, but it also feels like—and maybe this is just me paying closer attention—that the world of databases and data and analytics have really coalesced or emerged in a very different way over the past decade-ish. It used to be, at least from my perspective, that oh, that the actual, all the data we store, that’s a storage admin problem. And that was about managing NetApps and SANs and the rest. And then you had the database side of it, which functionally from the storage side of the world was just a big file or series of files that are the backing store for the database. And okay, there’s not a lot of cross-communication going on there.Then with the rise of object store, it started being a little bit different. And even the way that everyone is talking about getting meaning from data has really seem to be evolving at an incredibly intense clip lately. Is that an accurate perception, or have I just been asleep at the wheel for a while and finally woke up?Tony: No, I think you’re onto something there. And the reason is that, one, data is touching us all around ourselves, and the fact is, I mean, I’m you can see it in the same way that all of a sudden that people know how to spell AI. They may not know what it means, but the thing is, there is an awareness the data that we work with, the data that is about us, it follows us, and with the cloud, this data has—well, I should say not just with the cloud but with smart mobile devices—we’ll blame that—we are all each founts of data, and rich founts of data. And people in all walks of life, not just in the industry, are now becoming aware of it and there’s a lot of concern about can we have any control, any ownership over the data that should be ours? So, I think that phenomenon has also happened in the enterprise, where essentially where we used to think that the data was the DBAs’ issue, it’s become the app developers’ issue, it’s become the business analysts’ issue. Because the answers that we get, we’re ultimately accountable for. It all comes from the data.Corey: It also feels like there’s this idea of databases themselves becoming more contextually aware of the data contained within them. Originally, this used to be in the realm of, “Oh, we know what’s been accessed recently and we can tier out where it lives for storage optimization purposes.” Okay, great, but what I’m seeing now almost seems to be a sense of, people like to talk about pouring ML into their database offerings. And I’m not able to tell whether that is something that adds actual value, or if it’s marketing-ware.Tony: Okay. First off, let me kind of spill a couple of things. First of all, it’s not a question of the database becoming aware. A database is not sentient.Corey: Niether are some engineers, but that’s neither here nor there.Tony: That would be true, but then again, I don’t want anyone with shotguns lining up at my door after this—Corey: [laugh].Tony: —after this interview is published. But [laugh] more of the point, though, is that I can see a couple roles for machine learning in databases. One is a database itself, the logs, are an incredible font of data, of operational data. And you can look at trends in terms of when this—when the pattern of these logs goes this way, that is likely to happen. So, the thing is that I could very easily say we’re already seeing it: machine learning being used to help optimize the operation of databases, if you’re Oracle, and say, “Hey, we can have a database that runs itself.”The other side of the coin is being able to run your own machine-learning models in database as opposed to having to go out into a separate cluster and move the data, and that’s becoming more and more of a checkbox feature. However, that’s going to be for essentially, probably, like, the low-hanging fruit, like the 80/20 rule. It’ll be like the 20% of an ana—of relatively rudimentary, you know, let’s say, predictive analyses that we can do inside the database. If you’re going to be doing something more ambitious, such as a, you know, a large language model, you probably do not want to run that in database itself. So, there’s a difference there.Corey: One would hope. I mean, one of the inappropriate uses of technology that I go for all the time is finding ways to—as directed or otherwise—in off-label uses find ways of tricking different services into running containers for me. It’s kind of a problem; this is probably why everyone is very grateful I no longer write production code for anyone.But it does seem that there’s been an awful lot of noise lately. I’m lazy. I take shortcuts very often, and one of those is that whenever AWS talks about something extensively through multiple marketing cycles, it becomes usually a pretty good indicator that they’re on their back foot on that area. And for a long time, they were doing that about data and how it’s very important to gather data, it unlocks the key to your business, but it always felt a little hollow-slash-hypocritical to me because you’re going to some of the same events that I have that AWS throws on. You notice how you have to fill out the exact same form with a whole bunch of mandatory fields every single time, but there never seems to be anything that gets spat back out to you that demonstrates that any human or system has ever read—Tony: Right.Corey: Any of that? It’s basically a, “Do what we say, not what we do,” style of story. And I always found that to be a little bit disingenuous.Tony: I don’t want to just harp on AWS here. Of course, we can always talk about the two-pizza box rule and the fact that you have lots of small teams there, but I’d rather generalize this. And I think you really—what you’re just describing is been my trip through the healthcare system. I had some sports-related injuries this summer, so I’ve been through a couple of surgeries to repair sports injuries. And it’s amazing that every time you go to the doctor’s office, you’re filling the same HIPAA information over and over again, even with healthcare systems that use the same electronic health records software. So, it’s more a function of that it’s not just that the technologies are siloed, it’s that the organizations are siloed. That’s what you’re saying.Corey: That is fair. And I think at some level—I don’t know if this is a weird extension of Conway’s Law or whatnot—but these things all have different backing stores as far as data goes. And there’s a—the hard part, it seems, in a lot of companies once they hit a certain point of maturity is not just getting the data in—because they’ve already done that to some extent—but it’s also then making it actionable and helping various data stores internal to the company reconcile with one another and start surfacing things that are useful. It increasingly feels like it’s less of a technology problem and more of a people problem.Tony: It is. I mean, put it this way, I spent a lot of time last year, I burned a lot of brain cells working on data fabrics, which is an idea that’s in the idea of the beholder. But the ideal of a data fabric is that it’s not the tool that necessarily governs your data or secures your data or moves your data or transforms your data, but it’s supposed to be the master orchestrator that brings all that stuff together. And maybe sometime 50 years in the future, we might see that.I think the problem here is both technical and organizational. [unintelligible 00:11:58] a promise, you have all these what we used call island silos. We still call them silos or islands of information. And actually, ironically, even though in the cloud we have technologies where we can integrate this, the cloud has actually exacerbated this issue because there’s so many islands of information, you know, coming up, and there’s so many different little parts of the organization that have their hands on that. That’s also a large part of why there’s such a big discussion about, for instance, data mesh last year: everybody is concerned about owning their own little piece of the pie, and there’s a lot of question in terms of how do we get some consistency there? How do we all read from the same sheet of music? That’s going to be an ongoing problem. You and I are going to get very old before that ever gets solved.Corey: Yeah, there are certain things that I am content to die knowing that they will not get solved. If they ever get solved, I will not live to see it, and there’s a certain comfort in that, on some level.Tony: Yeah.Corey: But it feels like this stuff is also getting more and more complicated than it used to be, and terms aren’t being used in quite the same way as they once were. Something that a number of companies have been saying for a while now has been that customers overwhelmingly are preferring open-source. Open source is important to them when it comes to their database selection. And I feel like that’s a conflation of a couple of things. I’ve never yet found an ideological, purity-driven customer decision around that sort of thing.What they care about is, are there multiple vendors who can provide this thing so I’m not going to be using a commercially licensed database that can arbitrarily start playing games with seat licenses and wind up distorting my cost structure massively with very little notice. Does that align with your—Tony: Yeah.Corey: Understanding of what people are talking about when they say that, or am I missing something fundamental? Which is again, always possible?Tony: No, I think you’re onto something there. Open-source is a whole other can of worms, and I’ve burned many, many brain cells over this one as well. And today, you’re seeing a lot of pieces about the, you know, the—that are basically giving eulogies for open-source. It’s—you know, like HashiCorp just finally changed its license and a bunch of others have in the database world. What open-source has meant is been—and I think for practitioners, for DBAs and developers—here’s a platform that’s been implemented by many different vendors, which means my skills are portable.And so, I think that’s really been the key to why, for instance, like, you know, MySQL and especially PostgreSQL have really exploded, you know, in popularity. Especially Postgres, you know, of late. And it’s like, you look at Postgres, it’s a very unglamorous database. If you’re talking about stodgy, it was born to be stodgy because they wanted to be an adult database from the start. They weren’t the LAMP stack like MySQL.And the secret of success with Postgres was that it had a very permissive open-source license, which meant that as long as you don’t hold University of California at Berkeley, liable, have at it, kids. And so, you see, like, a lot of different flavors of Postgres out there, which means that a lot of customers are attracted to that because if I get up to speed on this Postgres—on one Postgres database, my skills should be transferable, should be portable to another. So, I think that’s a lot of what’s happening there.Corey: Well, I do want to call that out in particular because when I was coming up in the naughts, the mid-2000s decade, the lingua franca on everything I used was MySQL, or as I insist on mispronouncing it, my-squeal. And lately, on same vein, Postgres-squeal seems to have taken over the entire universe, when it comes to the de facto database of choice. And I’m old and grumpy and learning new things as always challenging, so I don’t understand a lot of the ways that thing gets managed from the context coming from where I did before, but what has driven the massive growth of mindshare among the Postgres-squeal set?Tony: Well, I think it’s a matter of it’s 30 years old and it’s—number one, Postgres always positioned itself as an Oracle alternative. And the early years, you know, this is a new database, how are you going to be able to match, at that point, Oracle had about a 15-year headstart on it. And so, it was a gradual climb to respectability. And I have huge respect for Oracle, don’t get me wrong on that, but you take a look at Postgres today and they have basically filled in a lot of the blanks.And so, it now is a very cre—in many cases, it’s a credible alternative to Oracle. Can it do all the things Oracle can do? No. But for a lot of organizations, it’s the 80/20 rule. And so, I think it’s more just a matter of, like, Postgres coming of age. And the fact is, as a result of it coming of age, there’s a huge marketplace out there and so much choice, and so much opportunity for skills portability. So, it’s really one of those things where its time has come.Corey: I think that a lot of my own biases are simply a product of the era in which I learned how a lot of these things work on. I am terrible at Node, for example, but I would be hard-pressed not to suggest JavaScript as the default language that people should pick up if they’re just entering tech today. It does front-end, it does back-end—Tony: Sure.Corey: —it even makes fries, apparently. There’s a—that is the lingua franca of the modern internet in a bunch of different ways. That doesn’t mean I’m any good at it, and it doesn’t mean at this stage, I’m likely to improve massively at it, but it is the right move, even if it is inconvenient for me personally.Tony: Right. Right. Put it this way, we’ve seen—and as I said, I’m not an expert in programming languages, but we’ve seen a huge profusion of programming languages and frameworks. But the fact is that there’s always been a draw towards critical mass. At the turn of the millennium, we thought is between Java and .NET. Little did we know that basically JavaScript—which at that point was just a web scripting language—[laugh] we didn’t know that it could work on the server; we thought it was just a client. Who knew?Corey: That’s like using something inappropriately as a database. I mean, good heavens.Tony: [laugh]. That would be true. I mean, when I could have, you know, easily just use a spreadsheet or something like that. But so, I mean, who knew? I mean, just like for instance, Java itself was originally conceived for a set-top box. You never know how this stuff is going to turn out. It’s the same thing happen with Python. Python was also a web scripting language. Oh, by the way, it happens to be really powerful and flexible for data science. And whoa, you know, now Python is—in terms of data science languages—has become the new SaaS.Corey: It really took over in a bunch of different ways. Before that, Perl was great, and I go, “Why would I use—why write in Python when Perl is available?” It’s like, “Okay, you know, how to write Perl, right?” “Yeah.” “Have you ever read anything a month later?” “Oh…” it’s very much a write-only language. It is inscrutable after the fact. And Python at least makes that a lot more approachable, which is never a bad thing.Tony: Yeah.Corey: Speaking of what you touched on toward the beginning of this episode, the idea of databases not being sentient, which I equate to being self-aware, you just came out very recently with a report on generative AI and a trip that you wound up taking on this. Which I’ve read; I love it. In fact, we’ve both been independently using the phrase [unintelligible 00:19:09] to, “English is the new most common programming language once a lot of this stuff takes off.” But what have you seen? What have you witnessed as far as both the ground truth reality as well as the grandiose statements that companies are making as they trip over themselves trying to position as the forefront leader and all of this thing that didn’t really exist five months ago?Tony: Well, what’s funny is—and that’s a perfect question because if on January 1st you asked “what’s going to happen this year?” I don’t think any of us would have thought about generative AI or large language models. And I will not identify the vendors, but I did some that had— was on some advanced briefing calls back around the January, February timeframe. They were talking about things like server lists, they were talking about in database machine learning and so on and so forth. They weren’t saying anything about generative.And all of a sudden, April, it changed. And it’s essentially just another case of the tail wagging the dog. Consumers were flocking to ChatGPT and enterprises had to take notice. And so, what I saw, in the spring was—and I was at a conference from SaaS, I’m [unintelligible 00:20:21] SAP, Oracle, IBM, Mongo, Snowflake, Databricks and others—that they all very quickly changed their tune to talk about generative AI. What we were seeing was for the most part, position statements, but we also saw, I think, the early emphasis was, as you say, it’s basically English as the new default programming language or API, so basically, coding assistance, what I’ll call conversational query.I don’t want to call it natural language query because we had stuff like Tableau Ask Data, which was very robotic. So, we’re seeing a lot of that. And we’re also seeing a lot of attention towards foundation models because I mean, what organization is going to have the resources of a Google or an open AI to develop their own foundation model? Yes, some of the Wall Street houses might, but I think most of them are just going to say, “Look, let’s just use this as a starting point.”I also saw a very big theme for your models with your data. And where I got a hint of that—it was a throwaway LinkedIn post. It was back in, I think like, February, Databricks had announced Dolly, which was kind of an experimental foundation model, just to use with your own data. And I just wrote three lines in a LinkedIn post, it was on Friday afternoon. By Monday, it had 65,000 hits.I’ve never seen anything—I mean, yes, I had a lot—I used to say ‘data mesh’ last year, and it would—but didn’t get anywhere near that. So, I mean, that really hit a nerve. And other things that I saw, was the, you know, the starting to look with vector storage and how that was going to be supported was it was going be a new type of database, and hey, let’s have AWS come up with, like, an, you know, an [ADF 00:21:41] database here or is this going to be a feature? I think for the most part, it’s going to be a feature. And of course, under all this, everybody’s just falling in love, falling all over themselves to get in the good graces of Nvidia. In capsule, that’s kind of like what I saw.Corey: That feels directionally accurate. And I think databases are a great area to point out one thing that’s always been more a little disconcerting for me. The way that I’ve always viewed databases has been, unless I’m calling a RAND function or something like it and I don’t change the underlying data structure, I should be able to run a query twice in a row and receive the same result deterministically both times.Tony: Mm-hm.Corey: Generative AI is effectively non-deterministic for all realistic measures of that term. Yes, I’m sure there’s a deterministic reason things are under the hood. I am not smart enough or learned enough to get there. But it just feels like sometimes we’re going to give you the answer you think you’re going to get, sometimes we’re going to give you a different answer. And sometimes, in generative AI space, we’re going to be supremely confident and also completely wrong. That feels dangerous to me.Tony: [laugh]. Oh gosh, yes. I mean, I take a look at ChatGPT and to me, the responses are essentially, it’s a high school senior coming out with an essay response without any footnotes. It’s the exact opposite of an ACID database. The reason why we’re very—in the database world, we’re very strongly drawn towards ACID is because we want our data to be consistent and to get—if we ask the same query, we’re going to get the same answer.And the problem is, is that with generative, you know, based on large language models, computers sounds sentient, but they’re not. Large language models are basically just a series of probabilities, and so hopefully those probabilities will line up and you’ll get something similar. That to me, kind of scares me quite a bit. And I think as we start to look at implementing this in an enterprise setting, we need to take a look at what kind of guardrails can we put on there. And the thing is, that what this led me to was that missing piece that I saw this spring with generative AI, at least in the data and analytics world, is nobody had a clue in terms of how to extend AI governance to this, how to make these models explainable. And I think that’s still—that’s a large problem. That’s a huge nut that it’s going to take the industry a while to crack.Corey: Yeah, but it’s incredibly important that it does get cracked.Tony: Oh, gosh, yes.Corey: One last topic that I want to get into. I know you said you don’t want to over-index on AWS, which, fair enough. It is where I spend the bulk of my professional time and energy—Tony: [laugh].Corey: Focusing on, but I think this one’s fair because it is a microcosm of a broader industry question. And that is, I don’t know what the DBA job of the future is going to look like, but increasingly, it feels like it’s going to primarily be picking which purpose-built AWS database—or larger [story 00:24:56] purpose database is appropriate for a given workload. Even without my inappropriate misuse of things that are not databases as databases, they are legitimately 15 or 16 different AWS services that they position as database offerings. And it really feels like you’re spiraling down a well of analysis paralysis, trying to pick between all these things. Do you think the future looks more like general-purpose databases, or very purpose-built and each one is this beautiful, bespoke unicorn?Tony: [laugh]. Well, this is basically a hit on a theme that I’ve been—you know, we’ve been all been thinking about for years. And the thing is, there are arguments to be made for multi-model databases, you know, versus a for-purpose database. That being said, okay, two things. One is that what I’ve been saying, in general, is that—and I wrote about this way, way back; I actually did a talk at the [unintelligible 00:25:50]; it was a throwaway talk, or [unintelligible 00:25:52] one of those conferences—I threw it together and it’s basically looking at the emergence of all these specialized databases.But how I saw, also, there’s going to be kind of an overlapping. Not that we’re going to come back to Pangea per se, but that, for instance, like, a relational database will be able to support JSON. And Oracle, for instance, does has some fairly brilliant ideas up the sleeve, what they call a JSON duality, which sounds kind of scary, which basically says, “We can store data relationally, but superimpose GraphQL on top of all of this and this is going to look really JSON-y.” So, I think on one hand, you are going to be seeing databases that do overlap. Would I use Oracle for a MongoDB use case? No, but would I use Oracle for a case where I might have some document data? I could certainly see that.The other point, though, and this is really one I want to hammer on here—it’s kind of a major concern I’ve had—is I think the cloud vendors, for all their talk that we give you operational simplicity and agility are making things very complex with its expanding cornucopia of services. And what they need to do—I’m not saying, you know, let’s close down the patent office—what I think we do is we need to provide some guided experiences that says, “Tell us the use case. We will now blend these particular services together and this is the package that we would suggest.” I think cloud vendors really need to go back to the drawing board from that standpoint and look at, how do we bring this all together? How would he really simplify the life of the customer?Corey: That is, honestly, I think the biggest challenge that the cloud providers have across the board. There are hundreds of services available at this point from every hyperscaler out there. And some of them are brand new and effectively feel like they’re there for three or four different customers and that’s about it and others are universal services that most people are probably going to use. And most things fall in between those two extremes, but it becomes such an analysis paralysis moment of trying to figure out what do I do here? What is the golden path?And what that means is that when you start talking to other people and asking their opinion and getting their guidance on how to do something when you get stuck, it’s, “Oh, you’re using that service? Don’t do it. Use this other thing instead.” And if you listen to that, you get midway through every problem for them to start over again because, “Oh, I’m going to pick a different selection of underlying components.” It becomes confusing and complicated, and I think it does customers largely a disservice. What I think we really need, on some level, is a simplified golden path with easy on-ramps and easy off-ramps where, in the absence of a compelling reason, this is what you should be using.Tony: Believe it or not, I think this would be a golden case for machine learning.Corey: [laugh].Tony: No, but submit to us the characteristics of your workload, and here’s a recipe that we would propose. Obviously, we can’t trust AI to make our decisions for us, but it can provide some guardrails.Corey: “Yeah. Use a graph database. Trust me, it’ll be fine.” That’s your general purpose—Tony: [laugh].Corey: —approach. Yeah, that’ll end well.Tony: [laugh]. I would hope that the AI would basically be trained on a better set of training data to not come out with that conclusion.Corey: One could sure hope.Tony: Yeah, exactly.Corey: I really want to thank you for taking the time to catch up with me around what you’re doing. If people want to learn more, where’s the best place for them to find you?Tony: My website is dbinsight.io. And on my homepage, I list my latest research. So, you just have to go to the homepage where you can basically click on the links to the latest and greatest. And I will, as I said, after Labor Day, I’ll be publishing my take on my generative AI journey from the spring.Corey: And we will, of course, put links to this in the [show notes 00:29:39]. Thank you so much for your time. I appreciate it.Tony: Hey, it’s been a pleasure, Corey. Good seeing you again.Corey: Tony Baer, principal at dbInsight. I’m Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice, along with an angry, insulting comment that we will eventually stitch together with all those different platforms to create—that’s right—a large-scale distributed database.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.

Bret Fisher, DevOps Dude & Cloud-Native Trainer, joins Corey on Screaming in the Cloud to discuss what it’s like being a practitioner and a content creator in the world of cloud. Bret shares why he feels it’s so critical to get his hands dirty so his content remains relevant, and also how he has to choose where to focus his efforts to grow his community. Corey and Bret discuss the importance of finding the joy in your work, and also the advantages and downfalls of the latest AI advancements. About BretFor 25 years Bret has built and operated distributed systems, and helped over 350,000 people learn dev and ops topics. He's a freelance DevOps and Cloud Native consultant, trainer, speaker, and open source volunteer working from Virginia Beach, USA. Bret's also a Docker Captain and the author of the popular Docker Mastery and Kubernetes Mastery series on Udemy. He hosts a weekly DevOps YouTube Live Show, a container podcast, and runs the popular devops.fan Discord chat server.Links Referenced: Twitter: https://twitter.com/BretFisher YouTube Channel: https://www.youtube.com/@BretFisher Website: https://www.bretfisher.com TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: In the cloud, ideas turn into innovation at virtually limitless speed and scale. To secure innovation in the cloud, you need Runtime Insights to prioritize critical risks and stay ahead of unknown threats. What's Runtime Insights, you ask? Visit sysdig.com/screaming to learn more. That's S-Y-S-D-I-G.com/screaming.My thanks as well to Sysdig for sponsoring this ridiculous podcast.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn, a little bit off the beaten path today, in that I’m talking to someone who, I suppose like me, if that’s not considered to be an insult, has found themselves eminently unemployable in a quote-unquote, “Real job.” My guest today is Bret Fisher, DevOps dude and cloud-native trainer. Bret, great to talk to you. What do you do?Bret: [laugh]. I’m glad to be here, Corey. I help people for a living like a lot of us end up doing in tech. But nowadays, it’s courses, it’s live trainings, webinars, all that stuff. And then of course, the fun side of it is the YouTube podcast, hanging out with friends, chatting on the internet. And then a little bit of running a Discord community, which is one of the best places to have a little text chat community, if you don’t know Discord.Corey: I’ve been trying to get the Discord and it isn’t quite resonating with me, just because by default, it alerts on everything that happens in any server you’re in. It, at least historically, was very challenging to get that tuned in, so I just stopped having anything alert me on my phone, which means now I miss things constantly. And that’s been fun and challenging. I still have the slack.lastweekinaws.com community with a couple of thousand people in it.Bret: Nice. Yeah, I mean, some people love Slack. I still have a Slack community for my courses. Discord, I feel like is way more community friendly. By the way, a good server admin knows how to change those settings, which there are a thousand settings in Discord, so server admins, I don’t blame you for not seeing that setting.But there is one where you can say new members, don’t bug them on every message; only bug them on a mentions or, you know, channel mentions and stuff like that. And then of course, you turn off all those channel mentions and abilities for people to abuse it. But yeah, I had the same problem at first. I did not know what I was doing and it took me years to kind of figure out. The community, we now have 15,000 people. We call it Cloud Native DevOps, but it’s basically people from all walks of DevOps, you know, recovering IT pros.And the wonderful thing about it is you always start out—like, you’d do the same thing, I’m sure—where you start a podcast or YouTube channel or a chat community or Telegram, or a subreddit, or whatever your thing is, and you try to build a community and you don’t know if it’s going to work and you invite your friends and then they show up for a day and then go away. And I’ve been very lucky and surprised that the Discord server has, to this point, taken on sort of a, its own nature. We’ve got, I don’t know, close to a dozen moderators now and people are just volunteering their time to help others. It’s wonderful. I actually—I consider it, like, one of the safe places, unlike maybe Stack Overflow where you might get hated for the wrong question. And we try to guide you to a better question so [laugh] that we can answer you or help you. So, every day I go in there, and there’s a dozen conversations I missed that I wasn’t able to keep up with. So, it’s kind of fun if you’re into that thing.Corey: I remember the olden days when I was one of the volunteer staff members on the freenode IRC network before its untimely and awful demise, and I really have come to appreciate the idea of, past a certain point, you can either own the forum that you’re working within or you can participate in it, but being a moderator, on some level, sets apart how people treat you in some strange ways. And none of these things are easy once you get into the nuances of codes of conduct, of people participating in good faith, but also are not doing so constructively. And people are hard. And one of these years I should really focus on addressing aspects of that with what I’m focusing on.Bret: [laugh]. Yeah, the machines—I mean, as frustrating as the machines are, they at least are a little more reliable. I don’t have anonymous machines showing up yet in Discord, although we do get almost daily spammers and stuff like that. So, you know, I guess I’m blessed to have attracted some of the spam and stuff like that. But a friend of mine who runs a solid community for podcasters—you know, for podcasts hosters—he warned me, he’s like, you know, if you really want to make it the community that you have the vision for, it requires daily work.Like, it’s a part-time job, and you have to put the time in, or it will just not be that and be okay with that. Like, be okay with it being a small, you know, small group of people that stick around and it doesn’t really grow. And that’s what’s happened on the Slack side of things is I didn’t care and feed it, so it has gotten pretty quiet over there as we’ve grown the Discord server. Because I kind of had to choose, you know? Because we—like you, I started with Slack long, long ago. It was the only thing out there. Discord was just for gamers.And in the last four or five years, I think Discord—I think during the pandemic, they officially said, “We are now more than gamers,” which I was kind of waiting for to really want to invest my company’s—I mean, my company of three—you know, my company [laugh] time into a platform that I thought was maybe just for gamers; couldn’t quite figure it out. And once they kind of officially said, “Yeah, we’re for all communities,” we’re more in, you know, and they have that—the thing I really appreciate like we had an IRC, but was mostly human-driven is that Discord, unlike Slack, has actual community controls that make it a safer place, a more inclusive place. And you can actually contact Discord when you have a spammer or someone doing bad things, or you have a server raid where there’s a whole bunch of accounts and bot accounts trying to take you down, you can actually reach out to Discord, where Slack doesn’t have any of that, they don’t have a way for you to reach out. You can’t block people or ban them or any of that stuff with Slack. And we—the luckily—the lucky thing of Dis—I kind of look at Discord as, like, the best new equivalent of IRC, even though for a lot of people IRC is still the thing, right? We have new clients now, you can actually have off—you could have sort of synced IRC, right, where you can have a web client that remembers you so you didn’t lose the chat after you left, which was always the problem back in the day.Corey: Oh, yeah. I just parked it on, originally, a hardware box, now EC2. And this ran Irssi as my client—because I’m old school—inside of tmux and called it a life. But yeah, I still use that from time to time, but the conversation has moved on. One challenge I’ve had is that a lot of the people I talk to about billing nuances skew sometimes, obviously in the engineering direction, but also in the business user perspective and it always felt, on some level like it was easier to get business users onto Slack from a community perspective—Bret: Mmm. Absolutely. Yeah.Corey: —than it was for Discord. I mean, this thing started as well. This was years ago, before Discord had a lot of those controls. Might be time to take another bite at that apple.Bret: Yeah. Yeah, I definitely—and that, I think that’s why I still keep the Slack open is there are some people, they will only go there, right? Like, they just don’t want another thing. That totally makes sense. In fact, that’s kind of what’s happening to the internet now, right?We see the demise of Twitter or X, we see all these other new clients showing up, and what I’ve just seen in the dev community is we had this wonderful dev community on Twitter. For a moment. For a few years. It wasn’t perfect by far, there was a lot people that still didn’t want to use Twitter, but I felt like there was—if you wanted to be in the cloud-native community, that was very strong and you didn’t always have to jump into Slack. And then you know, this billionaire came along and kind of ruined it, so people have fractured over to Mastodon and we’ve got some people have run Threads and some people on Bluesky, and now—and then some people like me that have stuck with Twitter.And I feel like I’ve lost a chunk of my friends because I don’t want to spend my life on six different platforms. So, I am—I have found myself actually kind of sort of regressing to our Discord because it’s the people I know, we’re all talking about the same things, we all have a common interest, and rather than spending my time trying to find those people on the socials as much as I used to. So, I don’t know, we’ll see.Corey: Something that I have found, I’m curious to get your take on this, you’ve been doing this for roughly twice as long as I have, but what I’ve been having to teach myself is that I am not necessarily representative of the totality of the audience. And, aside from the obvious demographic areas, I learned best by reading or by building something myself—I don’t generally listen to podcasts, which is a weird confession in this forum for me to wind up admitting to—and I don’t basically watch videos at all. And it took me a while to realize that not everyone is like me; those are wildly popular forms of absorbing information. What I have noticed that the audience engages differently in different areas, whereas for this podcast, for the first six months, I didn’t think that I’d remember to turn the microphone on. And that was okay; it was an experiment, and I enjoyed doing it. But then I went to a conference and wound up getting a whole bunch of feedback.Whereas for the newsletter, I had immediate responses to basically every issue when I sent it out. And I think the reason is, is because people are not sitting in front of a computer when they’re listening to something and they’re not going to be able to say, “Well, let me give you a piece of my mind,” in quite the same way. And by the time they remember later, it feels weird, like, calling into a radio show. But when you actually meet someone, “Yeah, I love your stuff.” And they’ll talk about the episodes I’ve had out. But you can be forgiven for in some cases in the social media side of it for thinking that I’d forgotten to publish this thing.Bret: Yeah. I think that’s actually a pretty common trait. There was a time where I was sort of into the science of learning and whatnot, and one of the things that came out of that was that the way we communicate or the way we learn and then the way—the input and the outputs are different per human. It’s actually almost, like, comparable maybe to love languages, if you’ve read that book, where the way we give love and the way we receive love from others is—we prefer it in different ways and it’s often not the same thing. And I think the same is true of learning and teaching, where my teaching style has always been visual.I think have almost always been in all my videos. My first course seven years ago, I was in it phy—like, I had my headshot in there and I just thought that that was a part of the best way you could make that content. And doesn’t mean that I’m instantly better; it just means I wanted to communicate with my hands, maybe I got a little bit of Italian or French in me or something [laugh] where I’m moving my hands around a lot. So, I think that the medium is very specific to the person. And I meet people all the time that I find out, they didn’t learn from me—they didn’t learn about me, rather, from my course; they learned about me from a conference talk because they prefer to watch those or someone else learned about me from the podcast I run because they stumbled onto that.And it always surprises me because I always figure that since my biggest audience in my Udemy courses—over 300,000 people there—that that’s how most of the people find me. And it turns out nowadays that when I meet people, a lot of times it’s not. It’s some other, you know, other venue. And now we have people showing up in the Discord server from the Discord Discovery. It’s kind of a little feature in Discord that allows you to find servers that are on the topics you’re interested in and were listed in there and people will find me that way and jump in not knowing that I have created courses, I have a weekly YouTube Live show, I have all the other things.And yeah, it’s just it’s kind of great, but also as a content creator, it’s kind of exhausting because you—if you’re interested in all these things, you can’t possibly focus on all of them at the [laugh] same time. So, what is it the great Will Smith says? “Do two things and two things suffer.” [laugh]. And that’s exactly what my life is like. It’s like, I can’t focus on one thing, so they all aren’t as amazing as they could be, maybe, if I had only dedicated to one thing.Corey: No, I’m with you on that it’s a saying yes to something means inherently saying no to something else. But for those of us whose interests are wide and varied, I find that there are always more things to do than I will ever be able to address. You have to pick and choose, on some level. I dabble with a lot of the stuff that I work on. I have given thought in the past towards putting out video courses or whatnot, but you’ve done that for ages and it just seems like it is so much front-loaded work, in many cases with things I’m not terrific at.And then, at least in my side of the world, oh, then AWS does another console refresh, as they tend to sporadically, and great, now I have to go back and redo all of the video shoots showing how to do it because now it’s changed just enough to confuse people. And it feels like a treadmill you climb on top of and never get off.Bret: It can definitely feel like that. And I think it’s also harder to edit existing courses like I’m doing now than it is to just make up something brand new and fresh. And there’s something about… we love to teach, I think what we’re learning in the moment. I think a lot of us, you get something exciting and you want to talk about it. And so, I think that’s how a lot of people’s conference talk ideas come up if you think about it.Like you’re not usually talking about the thing that you were interested in a decade ago. You’re talking about the thing you just learned, and you thought it was great, and you want everyone to know about it, which means you’re going to make a YouTube video or a blog post or something about it, you’ll share somewhere on social media about it. I think it’s harder to make this—any of these content creation things, especially courses, a career if you come back to that course like I’m doing seven years after publication and you’re continuing every year to update those videos. And you’re thinking I—not that my interests have moved on, but my passion is in the new things. And I’m not making videos right now on new things.I’m fixing—like you’re saying, like, I’m fixing the Docker Hub video because it has completely changed in seven years and it doesn’t even look the same and all that. So, there’s definitely—that’s the work side of this business where you really have to put the time in and it may not always be fun. So, one of the things I’m learning from my business coach is like how to find ways to make some of this stuff fun again, and how to inject some joy into it without it feeling like it’s just the churn of video after video after video, which, you know, you can fall into that trap with any of that stuff. So, yeah. That’s what I’m doing this year is learning a little bit more about myself and what I like doing versus what I have to do and try to make some of it a little funner.Corey: This question might come across as passive-aggressive or back-handedly insulting and I swear to you it is not intended to, but how do you avoid what has been a persistent fear of mine and that is becoming a talking head? Whereas you’ve been doing this as a trainer for long enough that you haven’t had a quote-unquote, “Real job,” in roughly, what, 15 years at this point?Bret: Yeah. Yeah.Corey: And so, you’ve never run Kubernetes in anger, which is, of course, was what we call production environment. That’s right, I call it ‘Anger.’ My staging environment is called ‘Theory’ because it works in theory, but not in production. And there you have it. So, without being hands-on and running these things at scale, it feels like on some level, if I were to, for example, give up the consulting side of my business and just talk about the pure math that I see and what AWS is putting out there, I feel like I’d pretty quickly lose sight of what actual customer pain looks like.Bret: Yeah. That’s a real fear, for sure. And that’s why I’m kind of—I think I kind of do what you do and maybe wasn’t… didn’t try to mislead you, but I do consult on a fairly consistent basis and I took a break this year. I’ve only—you know, then what I’ll do is I’ll do some advisory work, I usually won’t put hands on a cluster, I’m usually advising people on how to put the hands on that cluster kind of thing, or how to build accepting their PRs, doing stuff like that. That’s what I’ve done in the last maybe three or four years.Because you’re right. There’s two things that are, right? Like, it’s hard to stay relevant if you don’t actually get your hands dirty, your content ends up I think this naturally becoming very… I don’t know, one dimensional, maybe, or two dimensional, where it doesn’t, you don’t really talk about the best practices because you don’t actually have the scars to prove it. And so, I’m always nervous about going long lengths, like, three or four years of time, with zero production work. So, I think I try to fill that with a little bit of advisory, maybe trying to find friends and actually trying to talk with them about their experiences, just so I can make sure I’m understanding what they’re dealing with.I also think that that kind of work is what creates my stories. So like, my latest course, it’s on GitHub Actions and Argo CD for using automation and GitOps for deployments, basically trying to simplify the deployment lifecycle so that you can just get back to worrying about your app and not about how it’s deployed and how it’s tested and all that. And that all came out of consulting I did for a couple of firms in 2019 and 2020, and I think right into 2021, that’s kind of where I started winding them down. And that created the stories that caused me, you know, sort of the scars of going into production. We were migrating a COTS app into a SaaS app, so we were learning lots of things about their design and having to change infrastructure. And I had so many learnings from that.And one of them was I really liked GitHub Actions. And it worked well for them. And it was very flexible. And it wasn’t as friendly and as GUI beautiful as some of the other CI solutions out there, but it was flexible enough and direct—close enough to the developer that it felt powerful in the developers’ hands, whereas previous systems that we’ve all had, like Jenkins always felt like this black box that maybe one or two people knew.And those stories came out of the real advisory or consultancy that I did for those few years. And then I was like, “Okay, I’ve got stuff. I’ve learned it. I’ve done it in the field. I’ve got the scars. Let me go teach people about it.” And I’m probably going to have to do that again in a few years when I feel like I’m losing touch like you’re saying there. That’s a—yeah, so I agree. Same problem [laugh].Corey: Crap, I was hoping you had some magic silver bullet—Bret: No. [laugh].Corey: —other than, “No, it still gnaws at you forever and there’s no real way to get away for”—great. But, uhh, it keeps things… interesting.Bret: I would love to say that I have that skill, that ability to, like, just talk with you about your customers and, like, transfer all that knowledge so that I can then talk about it, but I don’t know. I don’t know. It’s tough.Corey: Yeah. The dangerous part there is suddenly you stop having lived experience and start just trusting whoever sounds the most confident, which of course, brings us to generative AI.Bret: Ohhh.Corey: Which apparently needs to be brought into every conversation as per, you know, analysts and Amazon leadership, apparently. What’s your take on it?Bret: Yeah. Yeah. Well, I was earl—I mean, well maybe not early, early. Like, these people that are talking about being early were seven years ago, so definitely wasn’t that early.Corey: Yeah. Back when the Hello World was a PhD from Stanford.Bret: Yeah [laugh], yeah. So, I was maybe—my first step in was on the tech side of things with Copilot when it was in beta a little over two years ago. We’re talking about GitHub Copilot. That was I think my first one. I was not an OpenAI user for any of their solutions, and was not into the visual—you know, the image AI stuff as we all are now dabbling with.But when it comes to code and YAML and TOML and, you know, the stuff that I deal with every day, I didn’t start into it until about two years ago. I think I actually live-streamed my first experiences with it with a friend of mine. And I was just using it for DevOps tasks at the time. It was an early beta, so I was like, kind of invited. And it was filling out YAML for me. It was creating Kubernetes YAML for me.And like we’re all learning, you know, it hallucinates, as we say, which is lying. It made stuff up for 50% of the time. And it was—it is way better now. So, I think I actually wrote in my newsletter a couple weeks ago a recent story—or a recent experience because I wanted to take a project in a language that I had not previously written from scratch in but maybe I was just slightly familiar with. So, I picked Go because everything in cloud-native is written in Go and so I’ve been reading it for years and years and years and maybe making small PRs to various things, but never taken on myself to write it from scratch and just create something, start to finish, for myself.And so, I wanted a real project, not something that was contrived, and it came up that I wanted to create—in my specific scenario, I wanted to take a CSV of all of my students and then take a template certificate, you know, like these certificates of completion or certifications, you know, that you get, and it’s a nice little—looks like the digital equivalent of a paper certificate that you would get from maybe a university. And I wanted to create that. So, I wanted to do it in bulk. I wanted to give it a stock image and then give it a list of names and then it would figure out the right place to put all those names and then generate a whole bunch of images that I could send out. And then I can maybe turn this into a web service someday.But I wanted to do this, and I knew, if I just wrote it myself, I’d be horrible at it, I would suck at Go, I’d probably have to watch some videos to remember some of the syntax. I don’t know the standard libraries, so I’d have to figure out which libraries I needed and all that stuff. All the dependencies.Corey: You make the same typical newcomer mistakes of not understanding the local idioms and whatnot. Oh, yeah.Bret: Yeah. And so, I’d have to spend some time on Stack Overflow Googling around. I kind of guessed it was going to take me 20 to 40 hours to make. Like, and it was—we’re talking really just hundreds of lines of code at the end of the day, but because Go standard library actually is really great, so it was going to be far less code than if I had to do it in NodeJS or something. Anyway, long story short there, it ended up taking three to three-and-a-half hours end to end, including everything I needed, you know, importing a CSV, sucking in a PNG, outputting PNG with all the names on them in the right places in the right font, the right colors, all that stuff.And I did it all through GitHub Copilot Chat, which is their newest Labs beta thing. And it brings the ChatGPT-4 experience into VS Code. I think it’s right now only for VS Code, but other editors coming soon. And it was kind of wonderful. It remembered my project as a whole. It wasn’t just in the file I was in. There was no copying-pasting back and forth between the web interface of ChatGPT like a lot of people tend to do today where they go into ChatGPT, they ask a question, then they copy out code and they paste it in their editor.Well, there was none of that because since that’s built into the editor, it kind of flows naturally into your existing project. You can kind of just click a button and it’ll automatically paste in where your cursor is. It does all this convenient stuff. And then it would relook at the code. I would ask it, you know, “What are ten ways to improve this code now that it works?” And you know, “How can I reduce the number of lines in this code?” Or, “How can I make it easier to read?”And I was doing all this stuff while I was creating the project. I haven’t had anyone, like, look at it to tell me if it looks good [laugh], which I hear you had that experience. But it works, it solved my problem, and I did it in a half a day with no prep time. And it’s all in ChatGPT’s history. So, when I open up VS Code now, I open that project up and get it, it recognizes that oh, this is the project that you’ve asked all these previous questions on, and it reloads all those questions, allowing me to basically start the conversation off again with my AI friend at the same place I left off.And I think that experience basically proved to me that what everybody else is telling us, right, that yes, this is definitely the future. I don’t see myself ever writing code again without an AI partner. I don’t know why I ever would write it without the AI partner at least to help me, quicken my learning, and solve some of the prompts. I mean, it was spitting out code that wasn’t perfect. It would actually—[unintelligible 00:23:53] sometimes fail.And then I would tell it, “Here’s the error you just caused. What do I do with that?” And it would help me walk through the solution, it would fix it, it would recommend changes. So, it’s definitely not something that will avoid you knowing how to program or make someone who’s not a programmer suddenly write a perfect program, but man, it really—I mean, it took basically what I would consider to be a novice in that language—not a novice at programming, but a novice at that language—and spit out a productive program in less than a day. So, that’s huge, I think.[midroll 00:24:27]Corey: What I think is a necessary prerequisite is a domain expertise in order to figure out what is accurate versus what is completely wrong, but sounds competent. And I’ve been racing a bunch of the different large-language models against each other in a variety of things like this. One of the challenges I’ll give them is to query the AWS pricing API—which motto is, “Not every war crime happens in faraway places”—and then spit out things like the Managed Nat Gateway hourly cost table, sorted from most to least expensive by region. And some things are great at it and other things really struggle with it. And the first time I, just on a lark, went down that path, it saved me an easy three hours from writing that thing by hand. It was effectively an API interface, whereas now the most common programming language I think we’re going to see on the rise is English.Bret: Yeah, good point. I’ve heard some theories, right? Like maybe the output language doesn’t matter. You just tell it, “Oh, don’t do that in Java, do it in PHP.” Whatever, or, “Convert this Java to PHP,” something like that.I haven’t experimented with a lot of that stuff yet, but I think that having spent this time watching a lot of other videos, right, you know, watching [Fireship 00:25:37], and a lot of other people talking about LLMs on the internet, seeing the happy-face stuff happen. And it’s just, I don’t know where we’re going to be in five or ten years. I am definitely not a good prediction, like a futurist. And I’m trying to imagine what the daily experience is going to be, but my assumption is, every tool we’re using is going to have some sort of chat AI assistant in it. I mean, this is kind of the future that, like, none of the movies predicted.[laugh]. We were talking about this the other day with a friend of mine. We were talking about it over dinner, some developer friends. And we were just talking about, like, this would be too boring for a movie, like, we all want the—you know, we think of the movies where there’s the three laws of robotics and all these things. And these are in no way sentient.I’m not intimidated or scared by them. I think the EU is definitely going to do the right thing here and we’re going to have to follow suit eventually, where we rank where you can use AI and, like, there’s these levels, and maybe just helping you with a program is a low-level, there’s very few restrictions, in other words, by the government, but if you’re talking about in cars or in medical or you know, in anything like that, that’s the highest level and the highest restrictions and all that. I could definitely see that’s the safety. Obviously, we’ll probably do it too slow and too late and there’ll be some bad uses in the meantime, but I think we’re there. I mean, like, if you’re not using it today—if you’re listening to this, and you’re not using AI yet in your day-to-day as someone related to the IT career, it’s going to be everywhere and I don’t think it’s going to be, like, one tool. The tools on the CLI to me are kind of weird right now. Like, they certainly can help you write command lines, but it just doesn’t flow right for me. I don’t know if you’ve tried that.Corey: Yeah. I ha—I’ve dabbled lightly, but again, I’ve been a Unix admin for the better part of 20 years and I’m used to a world in which you type exactly what you mean or you suffer the consequences. So, having a robot trying to outguess me of what it thinks I’m trying to do, if it works correctly, it looks like a really smart tab complete. If it guesses wrong, it’s incredibly frustrating. The risk/reward is not there in the same way.Bret: Right.Corey: So, for me at least, it’s more frustration than anything. I’ve seen significant use cases across the business world where this would have been invaluable back when I was younger, where it’s, “Great, here’s a one-line email I’m about to send to someone, and people are going to call me brusque or difficult for it. Great. Turn this into a business email.” And then on the other side, like, “This is a five-paragraph email. What does he actually want?” It’ll turn it back into one line. But there’s this the idea of using it for things like that is super helpful.Bret: Yeah. Robots talking to robots? Is that what you’re saying? Yeah.Corey: Well, partially, yes. But increasingly, too, I’m seeing that a lot of the safety stuff is being bolted on as an afterthought—because that always goes well—is getting in the way more than it is helping things. Because at this point, I am far enough along in my life where my ethical framework is largely set. I am not going to have radical changes in my worldview, no matter how much a robot [unintelligible 00:28:29] me.So, snark and sarcasm are my first languages and that is something that increasingly they’re leery about, like, oh, sarcasm can hurt people’s feelings. “Well, no kidding, professor, you don’t say.” As John Scalzi says, “The failure mode of clever is ‘asshole.’” But I figured out how to walk that line, so don’t you worry your pretty little robot head about that. Leave that to me. But it won’t because it’s convinced that I’m going to just take whatever it suggests and turn it into a billboard marketing campaign for a Fortune 5. There are several more approval steps in there.Bret: There. Yeah, yeah. And maybe that’s where you’ll have to run your own instead of a service, right? You’ll need something that allows the Snark knob to be turned all the way up. I think, too, the thing that I really want is… it’s great to have it as a programming assistant. It’s great and notion to help me, you know, think out, you know, sort of whiteboard some things, right, or sketch stuff out in terms of, “Give me the top ten things to do with this,” and it’s great for ideas and stuff like that.But what I really, really want is for it to remove a lot of the drudgery of day-to-day toil that we still haven’t, in tech, figured out a way—for example, I’m going to need a new repo. I know what I need to go in it, I know which organization it needs to go in, I know what types of files need to go in there, and I know the general purpose of the repo. Even the skilled person is going to take at least 20 minutes or more to set all that up. And I would really just rather take an AI on my local computer and say, “I would like three new repos: a front-end back-end, and a Kubernetes YAML repo. And I would like this one to be Rust, and I would like this one to be NodeJS or whatever, and I would like this other repo to have all the pieces in Kubernetes. And I would like Docker files in each repo plus GitHub Actions for linting.”Like, I could just spill out, you know, all these things: the editor.config file, the Git ignore, the Docker ignore, think about, like, the dozen files that every repo has to have now. And I just want that generated by an AI that knows my own repos, knows my preferences, and it’s more—because we all have, a lot of us that are really, really organized and I’m not one of those, we have maybe a template repo or we have templates that are created by a consolidated group of DevOps guild members or something in our organization that creates standards and reusable workflows and template files and template repos. And I think a lot of that’s going to go—that boilerplate will sort of, if we get a smart enough LLM that’s very user and organization-specific, I would love to be able to just tell Siri or whatever on my computer, “This is the thing I want to be created and it’s boilerplate stuff.” And it then generates all that.And then I jump into my code creator or my notion drafting of words. And that’s—like, I hop off from there. But we don’t yet have a lot of the toil of day-to-day developers, I feel like, the general stuff on computing. We don’t really have—maybe I don’t think that’s a general AI. I don’t think we’re… I don’t think that needs to be like a general intelligence. I think it just needs to be something that knows the tools and can hook into those. Maybe it asks for my fingerprint on occasion, just for security sake [laugh] so it doesn’t deploy all the things to AWS. But.Corey: Yeah. Like, I’ve been trying to be subversive with a lot of these things. Like, it’s always fun to ask the challenging questions, like, “My boss has been complaining to me about my performance and I’m salty about it. Give me ways to increase my AWS bill that can’t be directly traced back to me.” And it’s like, oh, that’s not how to resolve workplace differences.Like, okay. Good on, you found that at least, but cool, give me the dirt. I get asked in isolation of, “Yeah, how can I increase my AWS bill?” And its answer is, “There is no good reason to ever do that.” Mmm, there are exceptions on this and that’s not really what I asked. It’s, on some level, that tries to out-human you and gets it hilariously wrong.Bret: Yeah, there’s definitely, I think—it wasn’t me that said this, but in the state we’re in right now, there is this dangerous point of using any of these LLMs where, if you’re asking it questions and you don’t know anything about that thing you’re asking about, you don’t know what’s false, you don’t know what’s right, and you’re going to get in trouble pretty quickly. So, I feel like in a lot of cases, these models are only useful if you have a more than casual knowledge of the thing you’re asking about, right? Because, like, you can—like, you’ve probably tried to experiment. If you’re asking about AWS stuff, I’m just going to imagine that it’s going to make some of those service names up and it’s going to create things that don’t exist or that you can’t do, and you’re going to have to figure out what works and what doesn’t.And what do you do, right? Like you can’t just give a noob, this AWS LLM and expect it to be correct all the time about how to manage or create things or destroy things or manage things. So, maybe in five years. Maybe that will be the thing. You literally hire someone who has a computing degree out of a university somewhere and then they can suddenly manage AWS because the robot is correct 99.99% of the time. We’re just—I keep getting told that that’s years and years away and we don’t know how to stop the hallucinations, so we’re all stuck with it.Corey: That is the failure mode that is disappointing. We’re never going to stuff that genie back in the bottle. Like, that is—technology does not work that way. So, now that it’s here, we need to find a way to live with it. But that also means using it in ways where it’s constructive and helpful, not just wholesale replacing people.What does worry me about a lot of the use it to build an app, when I wound up showing this to some of my engineering friends, their immediate response universally, was, “Well, yeah, that’s great for, like, the easy, trivial stuff like querying a bad API, but for any of this other stuff, you still need senior engineers.” So, their defensiveness was the reaction, and I get that. But also, where do you think senior engineers come from? It’s solving a bunch of stuff like this. You didn’t all spring, fully formed, from the forehead of some God. Like, you started off as junior and working on small trivial problems, like this one, to build a skill set and realize what works well, what doesn’t, then life goes on.Bret: Yeah. In a way—I mean, you and I have been around long enough that in a way, the LLMs don’t really change anything in terms of who’s hireable, how many people you need in your team, or what types of people you need your team. I feel like, just like the cloud allowed us to have less people to do roughly the same thing as we all did in own data centers, I feel like to a large extent, these AIs are just going to do the same thing. It’s not fundamentally changing the game for most people to allow a university graduate to become a senior engineer overnight, or the fact that you don’t need, you know, the idea that you don’t maybe need senior engineers anymore and you can operate at AWS at scale, multi-region setup with some person with a year experience. I don’t think any of those things are true in the near term.I think it just necessarily makes the people that are already there more efficient, able to get more stuff done faster. And we’ve been dealing with that for 30, 40, 50 years, like, that’s exactly—I have this slideshow that I keep, I’ve been using it for a decade and it hasn’t really changed. And I got in in the mid-’90s when we were changing from single large computers to distributed computing when the PC took out—took on. I mean, like, I was doing miniframes, and, you know, IBMs and HP Unixes. And that’s where I jumped in.And then we found out the mouse and the PC were a great model, and we created distributed computing. That changed the game, allowed us, so many of us to get in that weren’t mainframe experts and didn’t know COBOL and a lot of us were able to get in and Windows or Microsoft made a great decision of saying, “We’re going to make the server operating system look and act exactly like the client operating system.” And then suddenly, all of us PC enthusiasts were now server admins. So, there’s this big shift in the ’90s. We got a huge amount of server admins.And then virtualization showed up, you know, five years later, and suddenly, we were able to do so much more with the same number of people in a data center and with a bunch of servers. And I watched my team in a big government organization was running 18 people. I had three hardware guys in the data center. That went to one in a matter of years because we were able to virtualize so much we needed physical servers less often, we needed less physical data center server admins, we needed more people to run the software. So, we shifted that team down and then we scaled up software development and people that knew more about actually managing and running software.So, this is, like, I feel like the shifts are happening, then we had the cloud and then we had containerization. It doesn’t really change it at a vast scale. And I think sometimes people are a little bit too worried about the LLMs as if they’re somehow going to make tech workers obsolete. And I just think, no, we’re just going to be managing the different things. We’re going to—someone else said the great quote, and I’ll end with this, you know, “It’s not the LLM that’s going to replace you. It’s the person who knows the LLMs that’s going to replace you.”And that’s the same thing you could have said ten years ago for, “It’s not the cloud that’s going to replace you. It’s someone who knows how to manage the cloud that’s going to replace you.” [laugh]. So, you could swap that word out for—Corey: A line I heard, must have been 30 years ago now is, “Think. It’s the only thing keeping a computer from taking your job.”Bret: Yeah [laugh], and these things don’t think so. We haven’t figured that one out yet.Corey: Yeah. Some would say that some people’s coworkers don’t either, but that’s just uncharitable.Bret: That’s me without coffee [laugh].Corey: [laugh]. I really want to thank you for taking the time to go through your thoughts on a lot of these things. If people want to learn more, where’s the best place for them to find you?Bret: bretfisher.com, or just search Bret Fisher. You’ll find all my stuff, hopefully, if I know how to use the internet, B-R-E-T F-I-S-H-E-R. And yeah, you’ll find a YouTube channel, on Twitter, I hang out there every day, and on my website.Corey: And we will, of course, put links to that in the [show notes 00:38:22]. Thank you so much for taking the time to speak with me today. I really appreciate it.Bret: Yeah. Thanks, Corey. See you soon.Corey: Bret Fisher, DevOps dude and cloud-native trainer. I’m Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry comment that you have a Chat-Gippity thing write for you, where, just like you, it sounds very confident, but it’s also completely wrong.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.

Austin Parker, Community Maintainer at OpenTelemetry, joins Corey on Screaming in the Cloud to discuss OpenTelemetry’s mission in the world of observability. Austin explains how the OpenTelemetry community was able to scale the OpenTelemetry project to a commercial offering, and the way Open Telemetry is driving innovation in the data space. Corey and Austin also discuss why Austin decided to write a book on OpenTelemetry, and the book’s focus on the evergreen applications of the tool. About AustinAustin Parker is the OpenTelemetry Community Maintainer, as well as an event organizer, public speaker, author, and general bon vivant. They've been a part of OpenTelemetry since its inception in 2019.Links Referenced: OpenTelemetry: https://opentelemetry.io/ Learning OpenTelemetry early release: https://www.oreilly.com/library/view/learning-opentelemetry/9781098147174/ Page with Austin’s social links: https://social.ap2.io TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: Look, I get it. Folks are being asked to do more and more. Most companies don’t have a dedicated DBA because that person now has a full time job figuring out which one of AWS’s multiple managed database offerings is right for every workload. Instead, developers and engineers are being asked to support, and heck, if time allows, optimize their databases. That’s where OtterTune comes in. Their AI is your database co-pilot for MySQL and PostgresSQL on Amazon RDS or Aurora. It helps improve performance by up to four x OR reduce costs by 50 percent – both of those are decent options. Go to ottertune dot com to learn more and start a free trial. That’s O-T-T-E-R-T-U-N-E dot com.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. It’s been a few hundred episodes since I had Austin Parker on to talk about the things that Austin cares about. But it’s time to rectify that. Austin is the community maintainer for OpenTelemetry, which is a CNCF project. If you’re unfamiliar with, we’re probably going to fix that in short order. Austin, Welcome back, it’s been a month of Sundays.Austin: It has been a month-and-a-half of Sundays. A whole pandemic-and-a-half.Corey: So, much has happened since then. I tried to instrument something with OpenTelemetry about a year-and-a-half ago, and in defense to the project, my use case is always very strange, but it felt like—a lot of things have sharp edges, but it felt like this had so many sharp edges that you just pivot to being a chainsaw, and I would have been at least a little bit more understanding of why it hurts so very much. But I have heard from people that I trust that the experience has gotten significantly better. Before we get into the nitty-gritty of me lobbing passive-aggressive bug reports at you have for you to fix in a scenario in which you can’t possibly refuse me, let’s start with the beginning. What is OpenTelemetry?Austin: That’s a great question. Thank you for asking it. So, OpenTelemetry is an observability framework. It is run by the CNCF, you know, home of such wonderful award-winning technologies as Kubernetes, and you know, the second biggest source of YAML in the known universe [clear throat].Corey: On some level, it feels like that is right there with hydrogen as far as unlimited resources in our universe.Austin: It really is. And, you know, as we all know, there are two things that make, sort of, the DevOps and cloud world go around: one of them being, as you would probably know, AWS bills; and the second being YAML. But OpenTelemetry tries to kind of carve a path through this, right, because we’re interested in observability. And observability, for those that don’t know or have been living under a rock or not reading blogs, it’s a lot of things. It’s a—but we can generally sort of describe it as, like, this is how you understand what your system is doing.I like to describe it as, it’s a way that we can model systems, especially complex, distributed, or decentralized software systems that are pretty commonly found in larg—you know, organizations of every shape and size, quite often running on Kubernetes, quite often running in public or private clouds. And the goal of observability is to help you, you know, model this system and understand what it’s doing, which is something that I think we can all agree, a pretty important part of our job as software engineers. Where OpenTelemetry fits into this is as the framework that helps you get the telemetry data you need from those systems, put it into a universal format, and then ship it off to some observability back-end, you know, a Prometheus or a Datadog or whatever, in order to analyze that data and get answers to your questions you have.Corey: From where I sit, the value of OTel—or OpenTelemetry; people in software engineering love abbreviations that are impenetrable from the outside, so of course, we’re going to lean into that—but what I found for my own use case is the shining value prop was that I could instrument an application with OTel—in theory—and then send whatever I wanted that was emitted in terms of telemetry, be it events, be it logs, be it metrics, et cetera, and send that to any or all of a curation of vendors on a case-by-case basis, which meant that suddenly it was the first step in, I guess, an observability pipeline, which increasingly is starting to feel like a milit—like an industrial-observability complex, where there’s so many different companies out there, it seems like a good approach to use, to start, I guess, racing vendors in different areas to see which performs better. One of the challenges I’ve had with that when I started down that path is it felt like every vendor who was embracing OTel did it from a perspective of their implementation. Here’s how to instrument it to—send it to us because we’re the best, obviously. And you’re a community maintainer, despite working at observability vendors yourself. You have always been one of those community-first types where you care more about the user experience than you do this quarter for any particular employer that you have, which to be very clear, is intended as a compliment, not a terrifying warning. It’s why you have this authentic air to you and why you are one of those very few voices that I trust in a space where normally I need to approach it with significant skepticism. How do you see the relationship between vendors and OpenTelemetry?Austin: I think the hard thing is that I know who signs my paychecks at the end of the day, right, and you always have, you know, some level of, you know, let’s say bias, right? Because it is a bias to look after, you know, them who brought you to the dance. But I think you can be responsible with balancing, sort of, the needs of your employer, and the needs of the community. You know, the way I’ve always described this is that if you think about observability as, like, a—you know, as a market, what’s the total addressable market there? It’s literally everyone that uses software; it’s literally every software company.Which means there’s plenty of room for people to make their numbers and to buy and sell and trade and do all this sort of stuff. And by taking that approach, by taking sort of the big picture approach and saying, “Well, look, you know, there’s going to be—you know, of all these people, there are going to be some of them that are going to use our stuff and there are some of them that are going to use our competitor’s stuff.” And that’s fine. Let’s figure out where we can invest… in an OpenTelemetry, in a way that makes sense for everyone and not just, you know, our people. So, let’s build things like documentation, right?You know, one of the things I’m most impressed with, with OpenTelemetry over the past, like, two years is we went from being, as a project, like, if you searched for OpenTelemetry, you would go and you would get five or six or ten different vendor pages coming up trying to tell you, like, “This is how you use it, this is how you use it.” And what we’ve done as a community is we’ve said, you know, “If you go looking for documentation, you should find our website. You should find our resources.” And we’ve managed to get the OpenTelemetry website to basically rank above almost everything else when people are searching for help with OpenTelemetry. And that’s been really good because, one, it means that now, rather than vendors or whoever coming in and saying, like, “Well, we can do this better than you,” we can be like, “Well, look, just, you know, put your effort here, right? It’s already the top result. It’s already where people are coming, and we can prove that.”And two, it means that as people come in, they’re going to be put into this process of community feedback, where they can go in, they can look at the docs, and they can say, “Oh, well, I had a bad experience here,” or, “How do I do this?” And we get that feedback and then we can improve the docs for everyone else by acting on that feedback, and the net result of this is that more people are using OpenTelemetry, which means there are more people kind of going into the tippy-tippy top of the funnel, right, that are able to become a customer of one of these myriad observability back ends.Corey: You touched on something very important here, when I first was exploring this—you may have been looking over my shoulder as I went through this process—my impression initially was, oh, this is a ‘CNCF project’ in quotes, where—this is not true universally, of course, but there are cases where it clearly—is where this is an, effectively, vendor-captured project, not necessarily by one vendor, but by an almost consortium of them. And that was my takeaway from OpenTelemetry. It was conversations with you, among others, that led me to believe no, no, this is not in that vein. This is clearly something that is a win. There are just a whole bunch of vendors more-or-less falling all over themselves, trying to stake out thought leadership and imply ownership, on some level, of where these things go. But I definitely left with a sense that this is bigger than any one vendor.Austin: I would agree. I think, to even step back further, right, there’s almost two different ways that I think vendors—or anyone—can approach OpenTelemetry, you know, from a market perspective, and one is to say, like, “Oh, this is socializing, kind of, the maintenance burden of instrumentation.” Which is a huge cost for commercial players, right? Like, if you’re a Datadog or a Splunk or whoever, you know, you have these agents that you go in and they rip telemetry out of your web servers, out of your gRPC libraries, whatever, and it costs a lot of money to pay engineers to maintain those instrumentation agents, right? And the cynical take is, oh, look at all these big companies that are kind of like pushing all that labor onto the open-source community, and you know, I’m not casting any aspersions here, like, I do think that there’s an element of truth to it though because, yeah, that is a huge fixed cost.And if you look at the actual lived reality of people and you look at back when SignalFx was still a going concern, right, and they had their APM agents open-sourced, you could go into the SignalFx repo and diff, like, their [Node Express 00:10:15] instrumentation against the Datadog Node Express instrumentation, and it’s almost a hundred percent the same, right? Because it’s truly a commodity. There’s no—there’s nothing interesting about how you get that telemetry out. The interesting stuff all happens after you have the telemetry and you’ve sent it to some back-end, and then you can, you know, analyze it and find interesting things. So, yeah, like, it doesn’t make sense for there to be five or six or eight different companies all competing to rebuild the same wheels over and over and over and over when they don’t have to.I think the second thing that some people are starting to understand is that it’s like, okay, let’s take this a step beyond instrumentation, right? Because the goal of OpenTelemetry really is to make sure that this instrumentation is native so that you don’t need a third-party agent, you don’t need some other process or jar or whatever that you drop in and it instruments stuff for you. The JVM should provide this, your web framework should provide this, your RPC library should provide this right? Like, this data should come from the code itself and be in a normalized fashion that can then be sent to any number of vendors or back ends or whatever. And that changes how—sort of, the competitive landscape a lot, I think, for observability vendors because rather than, kind of, what you have now, which is people will competing on, like, well, how quickly can I throw this agent in and get set up and get a dashboard going, it really becomes more about, like, okay, how are you differentiating yourself against every other person that has access to the same data, right? And you get more interesting use cases and how much more interesting analysis features, and that results in more innovation in, sort of, the industry than we’ve seen in a very long time.Corey: For me, just from the customer side of the world, one of the biggest problems I had with observability in my career as an SRE-type for years was you would wind up building your observability pipeline around whatever vendor you had selected and that meant emphasizing the things they were good at and de-emphasizing the things that they weren’t. And sometimes it’s worked to your benefit; usually not. But then you always had this question when it got things that touched on APM or whatnot—or Application Performance Monitoring—where oh, just embed our library into this. Okay, great. But a year-and-a-half ago, my exposure to this was on an application that I was running in distributed fashion on top of AWS Lambda.So great, you can either use an extension for this or you can build in the library yourself, but then there’s always a question of precedence where when you have multiple things that are looking at this from different points of view, which one gets done first? Which one is going to see the others? Which one is going to enmesh the other—enclose the others in its own perspective of the world? And it just got incredibly frustrating. One of the—at least for me—bright lights of OTel was that it got away from that where all of the vendors receiving telemetry got the same view.Austin: Yeah. They all get the same view, they all get the same data, and you know, there’s a pretty rich collection of tools that we’re starting to develop to help you build those pipelines yourselves and really own everything from the point of generation to intermediate collection to actually outputting it to wherever you want to go. For example, a lot of really interesting work has come out of the OpenTelemetry collector recently; one of them is this feature called Connectors. And Connectors let you take the output of certain pipelines and route them as inputs to another pipeline. And as part of that connection, you can transform stuff.So, for example, let’s say you have a bunch of [spans 00:14:05] or traces coming from your API endpoints, and you don’t necessarily want to keep all those traces in their raw form because maybe they aren’t interesting or maybe there’s just too high of a volume. So, with Connectors, you can go and you can actually convert all of those spans into metrics and export them to a metrics database. You could continue to save that span data if you want, but you have options now, right? Like, you can take that span data and put it into cold storage or put it into, like, you know, some sort of slow blob storage thing where it’s not actively indexed and it’s slow lookups, and then keep a metric representation of it in your alerting pipeline, use metadata exemplars or whatever to kind of connect those things back. And so, when you do suddenly see it’s like, “Oh, well, there’s some interesting p99 behavior,” or we’re hitting an alert or violating an SLO or whatever, then you can go back and say, like, “Okay, well, let’s go dig through the slow da—you know, let’s look at the cold data to figure out what actually happened.”And those are features that, historically, you would have needed to go to a big, important vendor and say, like, “Hey, here’s a bunch of money,” right? Like, “Do this for me.” Now, you have the option to kind of do all that more interesting pipeline stuff yourself and then make choices about vendors based on, like, who is making a tool that can help me with the problem that I have? Because most of the time, I don’t—I feel like we tend to treat observability tools as—it depends a lot on where you sit in the org—but you certainly seen this movement towards, like, “Well, we don’t want a tool; we want a platform. We want to go to Lowe’s and we want to get the 48-in-one kit that has a bunch of things in it. And we’re going to pay for the 48-in-one kit, even if we only need, like, two things or three things out of it.”OpenTelemetry lets you kind of step back and say, like, “Well, what if we just got, like, really high-quality tools for the two or three things we need, and then for the rest of the stuff, we can use other cheaper options?” Which is, I think, really attractive, especially in today’s macroeconomic conditions, let’s say.Corey: One thing I’m trying to wrap my head around because we all find when it comes to observability, in my experience, it’s the parable of three blind people trying to describe an elephant by touch; depending on where you are on the elephant, you have a very different perspective. What I’m trying to wrap my head around is, what is the vision for OpenTelemetry? Is it specifically envisioned to be the agent that runs wherever the workload is, whether it’s an agent on a host or a layer in a Lambda function, or a sidecar or whatnot in a Kubernetes cluster that winds up gathering and sending data out? Or is the vision something different? Because part of what you’re saying aligns with my perspective on it, but other parts of it seem to—that there’s a misunderstanding somewhere, and it’s almost certainly on my part.Austin: I think the long-term vision is that you as a developer, you as an SRE, don’t even have to think about OpenTelemetry, that when you are using your container orchestrator or you are using your API framework or you’re using your Managed API Gateway, or any kind of software that you’re building something with, that the telemetry data from that software is emitted in an OpenTelemetry format, right? And when you are writing your code, you know, and you’re using gRPC, let’s say, you could just natively expect that OpenTelemetry is kind of there in the background and it’s integrated into the actual libraries themselves. And so, you can just call the OpenTelemetry API and it’s part of the standard library almost, right? You add some additional metadata to a span and say, like, “Oh, this is the customer ID,” or, “This is some interesting attribute that I want to track for later on,” or, “I’m going to create a histogram here or counter,” whatever it is, and then all that data is just kind of there, right, invisible to you unless you need it. And then when you need it, it’s there for you to kind of pick up and send off somewhere to any number of back-ends or databases or whatnot that you could then use to discover problems or better model your system.That’s the long-term vision, right, that it’s just there, everyone uses it. It is a de facto and du jour standard. I think in the medium term, it does look a little bit more like OpenTelemetry is kind of this Swiss army knife agent that’s running on—inside cars in Kubernetes or it’s running on your EC2 instance. Until we get to the point of everyone just agrees that we’re going to use OpenTelemetry protocol for the data and we’re going to use all your stuff and we just natively emit it, then that’s going to be how long we’re in that midpoint. But that’s sort of the medium and long-term vision I think. Does that track?Corey: It does. And I’m trying to equate this to—like the evolution back in the Stone Age was back when I was first getting started, Nagios was the gold standard. It was kind of the original Call of Duty. And it was awful. There were a bunch of problems with it, but it also worked.And I’m not trying to dunk on the people who built that. We all stand on the shoulders of giants. It was an open-source project that was awesome doing exactly what it did, but it was a product built for a very different time. It completely had the wheels fall off as soon as you got to things were even slightly ephemeral because it required this idea of the server needed to know where all of the things that was monitoring lived as an individual host basis, so there was this constant joy of, “Oh, we’re going to add things to a cluster.” Its perspective was, “What’s a cluster?” Or you’d have these problems with a core switch going down and suddenly everything else would explode as well.And even setting up an on-call rotation for who got paged when was nightmarish. And a bunch of things have evolved since then, which is putting it mildly. Like, you could say that about fire, the invention of the wheel. Yeah, a lot of things have evolved since the invention of the wheel, and here we are tricking sand into thinking. But we find ourselves just—now it seems that the outcome of all of this has been instead of one option that’s the de facto standard that’s kind of terrible in its own ways, now, we have an entire universe of different products, many of which are best-of-breed at one very specific thing, but nothing’s great at everything.It’s the multifunction printer conundrum, where you find things that are great at one or two things at most, and then mediocre at best at the rest. I’m excited about the possibility for OpenTelemetry to really get to a point of best-of-breed for everything. But it also feels like the money folks are pushing for consolidation, if you believe a lot of the analyst reports around this of, “We already pay for seven different observability vendors. How about we knock it down to just one that does all of these things?” Because that would be terrible. What do you land on that?Austin: Well, as I intu—or alluded to this earlier, I think the consolidation in the observability space, in general, is very much driven by that force you just pointed out, right? The buyers want to consolidate more and more things into single tools. And I think there’s a lot of… there are reasons for that that—you know, there are good reasons for that, but I also feel like a lot of those reasons are driven by fundamentally telemetry-side concerns, right? So like, one example of this is if you were Large Business X, and you see—you are an engineering director and you get a report, that’s like, “We have eight different metrics products.” And you’re like, “That seems like a lot. Let’s just use Brand X.”And Brand X will tell you very, very happily tell you, like, “Oh, you just install our thing everywhere and you can get rid of all these other tools.” And usually, there’s two reasons that people pick tools, right? One reason is that they are forced to and then they are forced to do a bunch of integration work to get whatever the old stuff was working in the new way, but the other reason is because they tried a bunch of different things and they found the one tool that actually worked for them. And what happens invariably in these sort of consolidation stories is, you know, the new vendor comes in on a shining horse to consolidate, and you wind up instead of eight distinct metrics tools, now you have nine distinct metrics tools because there’s never any bandwidth for people to go back and, you know—you’re Nagios example, right, Nag—people still use Nagios every day. What’s the economic justification to take all those Nagios installs, if they’re working, and put them into something else, right?What’s the economic justification to go and take a bunch of old software that hasn’t been touched for ten years that still runs and still does what needs to do, like, where’s the incentive to go and re-instrument that with OpenTelemetry or anything else? It doesn’t necessarily exist, right? And that’s a pretty, I think, fundamental decision point in everyone’s observability journey, which is what do you do about all the old stuff? Because most of the stuff is the old stuff and the worst part is, most of the stuff that you make money off of is the old stuff as well. So, you can’t ignore it, and if you’re spending, you know, millions of millions of dollars on the new stuff—like, there was a story that went around a while ago, I think, Coinbase spent something like, what, $60 million on Datadog… I hope they asked for it in real money and not Bitcoin. But—Corey: Yeah, something I’ve noticed about all the vendors, and even Coinbase themselves, very few of them actually transact in cryptocurrency. It’s always cash on the barrelhead, so to speak.Austin: Yeah, smart. But still, like, that’s an absurd amount of money [laugh] for any product or service, I would argue, right? But that’s just my perspective. I do think though, it goes to show you that you know, it’s very easy to get into these sort of things where you’re just spending over the barrel to, like, the newest vendor that’s going to come in and solve all your problems for you. And just, it often doesn’t work that way because most places aren’t—especially large organizations—just aren’t built in is sort of like, “Oh, we can go through and we can just redo stuff,” right? “We can just roll out a new agent through… whatever.”We have mainframes [unintelligible 00:25:09], mainframes to thinking about, you have… in many cases, you have an awful lot of business systems that most, kind of, cloud people don’t like, think about, right, like SAP or Salesforce or ServiceNow, or whatever. And those sort of business process systems are actually responsible for quite a few things that are interesting from an observability point of view. But you don’t see—I mean, hell, you don’t even see OpenTelemetry going out and saying, like, “Oh, well, here’s the thing to let you know, observe Apex applications on Salesforce,” right? It’s kind of an undiscovered country in a lot of ways and it’s something that I think we will have to grapple with as we go forward. In the shorter term, there’s a reason that OpenTelemetry mostly focuses on cloud-native applications because that’s a little bit easier to actually do what we’re trying to do on them and that’s where the heat and light is. But once we get done with that, then the sky is the limit.[midroll 00:26:11]Corey: It still feels like OpenTelemetry is evolving rapidly. It’s certainly not, I don’t want to say it’s not feature complete, which, again, what—software is never done. But it does seem like even quarter-to-quarter or month-to-month, its capabilities expand massively. Because you apparently enjoy pain, you’re in the process of writing a book. I think it’s in early release or early access that comes out next year, 2024. Why would you do such a thing?Austin: That’s a great question. And if I ever figure out the answer I will tell you.Corey: Remember, no one wants to write a book; they want to have written the book.Austin: And the worst part is, is I have written the book and for some reason, I went back for another round. I—Corey: It’s like childbirth. No one remembers exactly how horrible it was.Austin: Yeah, my partner could probably attest to that. Although I was in the room, and I don’t think I’d want to do it either. So, I think the real, you know, the real reason that I decided to go and kind of write this book—and it’s Learning OpenTelemetry; it’s in early release right now on the O’Reilly learning platform and it’ll be out in print and digital next year, I believe, we’re targeting right now, early next year.But the goal is, as you pointed out so eloquently, OpenTelemetry changes a lot. And it changes month to month sometimes. So, why would someone decide—say, “Hey, I’m going to write the book about learning this?” Well, there’s a very good reason for that and it is that I’ve looked at a lot of the other books out there on OpenTelemetry, on observability in general, and they talk a lot about, like, here’s how you use the API. Here’s how you use the SDK. Here’s how you make a trace or a span or a log statement or whatever. And it’s very technical; it’s very kind of in the weeds.What I was interested in is saying, like, “Okay, let’s put all that stuff aside because you don’t necessarily…” I’m not saying any of that stuff’s going to change. And I’m not saying that how to make a span is going to change tomorrow; it’s not, but learning how to actually use something like OpenTelemetry isn’t just knowing how to create a measurement or how to create a trace. It’s, how do I actually use this in a production system? To my point earlier, how do I use this to get data about, you know, these quote-unquote, “Legacy systems?” How do I use this to monitor a Kubernetes cluster? What’s the important parts of building these observability pipelines? If I’m maintaining a library, how should I integrate OpenTelemetry into that library for my users? And so on, and so on, and so forth.And the answers to those questions actually probably aren’t going to change a ton over the next four or five years. Which is good because that makes it the perfect thing to write a book about. So, the goal of Learning OpenTelemetry is to help you learn not just how to use OpenTelemetry at an API or SDK level, but it’s how to build an observability pipeline with OpenTelemetry, it’s how to roll it out to an organization, it’s how to convince your boss that this is what you should use, both for new and maybe picking up some legacy development. It’s really meant to give you that sort of 10,000-foot view of what are the benefits of this, how does it bring value and how can you use it to build value for an observability practice in an organization?Corey: I think that’s fair. Looking at the more quote-unquote, “Evergreen,” style of content as opposed to—like, that’s the reason for example, I never wind up doing tutorials on how to use an AWS service because one console change away and suddenly I have to redo the entire thing. That’s a treadmill I never had much interest in getting on. One last topic I want to get into before we wind up wrapping the episode—because I almost feel obligated to sprinkle this all over everything because the analysts told me I have to—what’s your take on generative AI, specifically with an eye toward observability?Austin: [sigh], gosh, I’ve been thinking a lot about this. And—hot take alert—as a skeptic of many technological bubbles over the past five or so years, ten years, I’m actually pretty hot on AI—generative AI, large language models, things like that—but not for the reasons that people like to kind of hold them up, right? Not so that we can all make our perfect, funny [sigh], deep dream, meme characters or whatever through Stable Fusion or whatever ChatGPT spits out at us when we ask for a joke. I think the real win here is that this to me is, like, the biggest advance in human-computer interaction since resistive touchscreens. Actually, probably since the mouse.Corey: I would agree with that.Austin: And I don’t know if anyone has tried to get someone that is, you know, over the age of 70 to use a computer at any time in their life, but mapping human language to trying to do something on an operating system or do something on a computer on the web is honestly one of the most challenging things that faces interface design, face OS designers, faces anyone. And I think this also applies for dev tools in general, right? Like, if you think about observability, if you think about, like, well, what are the actual tasks involved in observability? It’s like, well, you’re making—you’re asking questions. You’re saying, like, “Hey, for this metric named HTTPrequestsByCode,” and there’s four or five dimensions, and you say, like, “Okay, well break this down for me.” You know, you have to kind of know the magic words, right? You have to know the magic promQL sequence or whatever else to plug in and to get it to graph that for you.And you as an operator have to have this very, very well developed, like, depth of knowledge and math and statistics to really kind of get a lot of—Corey: You must be at least this smart to ride on this ride.Austin: Yeah. And I think that, like that, to me is the real—the short-term win for certainly generative AI around using, like, large language models, is the ability to create human language interfaces to observability tools, that—Corey: As opposed to learning your own custom SQL dialect, which I see a fair number of times.Austin: Right. And, you know, and it’s actually very funny because there was a while for the—like, one of my kind of side projects for the past [sigh] a little bit [unintelligible 00:32:31] idea of, like, well, can we make, like, a universal query language or universal query layer that you could ship your dashboards or ship your alerts or whatever. And then it’s like, generative AI kind of just, you know, completely leapfrogs that, right? It just says, like, well, why would you need a query language, if we can just—if you can just ask the computer and it works, right?Corey: The most common programming language is about to become English.Austin: Which I mean, there’s an awful lot of externalities there—Corey: Which is great. I want to be clear. I’m not here to gatekeep.Austin: Yeah. I mean, I think there’s a lot of externalities there, and there’s a lot—and the kind of hype to provable benefit ratio is very skewed right now towards hype. That said, one of the things that is concerning to me as sort of an observability practitioner is the amount of people that are just, like, whole-hog, throwing themselves into, like, oh, we need to integrate generative AI, right? Like, we need to put AI chatbots and we need to have ChatGPT built into our products and da-da-da-da-da. And now you kind of have this perfect storm of people that really don’t ha—because they’re just using these APIs to integrate gen AI stuff with, they really don’t understand what it’s doing because a lot you know, it is very complex, and I’ll be the first to admit that I really don’t understand what a lot of it is doing, you know, on the deep, on the foundational math side.But if we’re going to have trust in, kind of, any kind of system, we have to understand what it’s doing, right? And so, the only way that we can understand what it’s doing is through observability, which means it’s incredibly important for organizations and companies that are building products on generative AI to, like, drop what—you know, walk—don’t walk, run towards something that is going to give you observability into these language models.Corey: Yeah. “The computer said so,” is strangely dissatisfying.Austin: Yeah. You need to have that base, you know, sort of, performance [goals and signals 00:34:31], obviously, but you also need to really understand what are the questions being asked. As an example, let’s say you have something that is tokenizing questions. You really probably do want to have some sort of observability on the hot path there that lets you kind of break down common tokens, especially if you were using, like, custom dialects or, like, vectors or whatever to modify the, you know, neural network model, like, you really want to see, like, well, what’s the frequency of the certain tokens that I’m getting they’re hitting the vectors versus not right? Like, where can I improve these sorts of things? Where am I getting, like, unexpected results?And maybe even have some sort of continuous feedback mechanism that it could be either analyzing the tone and tenor of end-user responses or you can have the little, like, frowny and happy face, whatever it is, like, something that is giving you that kind of constant feedback about, like, hey, this is how people are actually like interacting with it. Because I think there’s way too many stories right now people just kind of like saying, like, “Oh, okay. Here’s some AI-powered search,” and people just, like, hating it. Because people are already very primed to distrust AI, I think. And I can’t blame anyone.Corey: Well, we’ve had an entire lifetime of movies telling us that’s going to kill us all.Austin: Yeah.Corey: And now you have a bunch of, also, billionaire tech owners who are basically intent on making that reality. But that’s neither here nor there.Austin: It isn’t, but like I said, it’s difficult. It’s actually one of the first times I’ve been like—that I’ve found myself very conflicted.Corey: Yeah, I’m a booster of this stuff; I love it, but at the same time, you have some of the ridiculous hype around it and the complete lack of attention to safety and humanity aspects of it that it’s—I like the technology and I think it has a lot of promise, but I want to get lumped in with that set.Austin: Exactly. Like, the technology is great. The fan base is… ehh, maybe something a little different. But I do think that, for lack of a better—not to be an inevitable-ist or whatever, but I do think that there is a significant amount of, like, this is a genie you can’t put back in the bottle and it is going to have, like, wide-ranging, transformative effects on the discipline of, like, software development, software engineering, and white collar work in general, right? Like, there’s a lot of—if your job involves, like, putting numbers into Excel and making pretty spreadsheets, then ooh, that doesn’t seem like something that’s going to do too hot when I can just have Excel do that for me.And I think we do need to be aware of that, right? Like, we do need to have that sort of conversation about, like… what are we actually comfortable doing here in terms of displacing human labor? When we do displace human labor, are we doing it so that we can actually give people leisure time or so that we can just cram even more work down the throats of the humans that are left?Corey: And unfortunately, I think we might know what that answer is, at least on our current path.Austin: That’s true. But you know, I’m an optimist.Corey: I… don’t do well with disappointment. Which the show has certainly not been. I really want to thank you for taking the time to speak with me today. If people want to learn more, where’s the best place for them to find you?Austin: Welp, I—you can find me on most social media. Many, many social medias. I used to be on Twitter a lot, and we all know what happened there. The best place to figure out what’s going on is check out my bio, social.ap2.io will give you all the links to where I am. And yeah, been great talking with you.Corey: Likewise. Thank you so much for taking the time out of your day. Austin Parker, community maintainer for OpenTelemetry. I’m Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice, along with an angry comment pointing out that actually, physicists say the vast majority of the universe’s empty space, so that we can later correct you by saying ah, but it’s empty whitespace. That’s right. YAML wins again.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.