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Screaming in the Cloud with Corey Quinn features conversations with domain experts in the world of Cloud Computing. Topics discussed include AWS, GCP, Azure, Oracle Cloud, and the "why" behind how businesses are coming to think about the Cloud.
Stephen Barr: I think that, like, the fundamentals of cryptocurrency, like, it makes sense, and I like it. But then on top of that little core of truth is this giant pile of scams and garbage and hype.
Corey Quinn: Welcome to Screaming in the Cloud, I'm Corey Quinn. Thrilled to be able to talk with Stephen Barr today. We've talked many times previously, but this is the first time we're doing it in public on one of my properties instead of his. Stephen is the Chief Evangelist over at CloudFix. Stephen, how are you?
Stephen Barr: Really well, Corey. It's great to be here on, like I said, on your property, talking in an official capacity.
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Corey Quinn: I have to say that you and I suffer a similar affliction in that it is kind of hard to describe what you do.
How do you define yourself as far as the starting, the stopping?
Stephen Barr: So I like to see it as a facilitating a two way relationship between the, well, our customers who are interested in cost optimization and then the engineering and the internals of the company to make sure I can be a trusted source for developers to go to for the more technical folks within the business to go to and say, "Hey, does this actually do what we're claiming it to do?" To be able to talk shop with the developers in our, with our clients, and then also to make sure to advocate for them. So I see the evangelism as a two-way street. It's not just, it's me doing a lot of talking and that goes through content creation through marketing, that sort of thing, but also a lot of listening and bringing that back to the rest of the team.
Corey Quinn: I've always found that cost optimization tends to be a content area that people care about at very fixed points in time, usually when there's a burning fire and the rest of the time they could not possibly care less. So my strategy around it has always been to talk about the, the greater AWS ecosystem and architectural fun things thereabouts. I guess make it a point to periodically throw some of the cost content in to remind people that I exist, and I found that that's been working for eight years so far.
Stephen Barr: I almost see it as like, well, like you said, it comes up when there's a fire. And almost like fitness, right? You go to your doctor and he's like, "Hey, your cholesterol is way off," and all of a sudden you're like, "Alright, I'm going to the gym. I'm getting serious. I'm going to change my diet," and then, you know, we're human. We tend to regress.
Corey Quinn: Three weeks later, we're on the couch eating chips.
Stephen Barr: Exactly. And so it has to be this constant pressure, and I want to see myself as being, in a way, a bit of a constant friendly encouragement, constant pressure. Say, "Hey, here's something else you can do," and then, yeah, "Here's something you can try." "Have you looked at your EBS volumes?" Just like you'd have a personal trainer who is saying, "Let's push it on this exercise. Let's try and do an extra set this week." That kind of thing to be that constant pressure.
Corey Quinn: It's interesting just seeing how difficult it is to define what we do in the context of what we do. I like to sometimes say that we're marriage counseling between engineering and finance, which feels like it is not that far from. You know, where a lot of these things tend to play.
Stephen Barr: You don't have a trademark on that phrase, do you?
Corey Quinn: No, no, I don't.
Stephen Barr: I'm sure that will come up in conversation. We have to sit down on the couch here and, and what are your needs and are you being heard here?
That's definitely the case.
Corey Quinn: Exactly. We can talk about insecurities. It's a safe space. Trusting. It'll be great. It'll be great.
So lately, it seems like there have been some shakeups over at AWS. There are a lot of things going on over at AWS as of late. I know that they've been chasing a lot of the ML dragons lately.
They've had some significant and notable departures that I'm not seeing backfilled. That doesn't mean it's not happening, but it's not happening in the public eye. My Rolodex, people I know at AWS seems to get slimmer every year. A Rolodex is a list of contact cards for those of my, uh, those of the audience who are, you know, younger than we are.
Stephen Barr: It's funny that those analogies are starting to break a little bit.
Corey Quinn: The save button is still a floppy disk.
Stephen Barr: Yeah, I mean, so just at point in time, we've learned about Matt Wood's departure, and there's no official word on where he's going.
Corey Quinn: As of this recording. This is one of those things where just invariably as soon as we say this and the track is laid down, ten minutes later there'll be an announcement and it'll be all over the place and we'll sound like fools.
Stephen Barr: Check the show notes for an asterisk somewhere.
Corey Quinn: Exactly.
Stephen Barr: Yeah, but I guess with anyone involved in the generative AI space with that large of a persona, you probably have a lot of opportunities coming your way. So that's, that's my speculation, but I don't have any inside information as to where he's going.
Corey Quinn: It's always interesting to me watching how senior executives manage transitions between companies, the way that they talk about it, how they structure it. Like when you talk about like the Uber executive types, the executive VPs at giant companies, in many cases they'll do a departure, they'll have a long handoff period, there will be a farewell tour with a lot of the clients, they're generally on gardening leave for three-to-six months.
And then it comes out where they're going to go is generally a step up. The inverse of this is stepping down immediately to spend time with family. It's like, "Ooh..."
Stephen Barr: We can read between the lines there.
Corey Quinn: Yeah. That sends a message that isn't terrific. And the fun thing is when companies don't realize that that's the message it sends and it's a legitimate, I know that's actually what happened, but no one believes it because of the messaging.
Stephen Barr: They need to get new PR for them.
Corey Quinn: Honestly, lately it feels like so much of the AWS corporate comms apparatus has been aimed at talking about machine learning, and when you start digging really deep into it, the teams that build and run the services that we know and depend on are still there. They're still doing things that are neat and that are going to be trotted out at reInvent, which is freaking terrific.
The problem is, is that that's not at all what gets talked about.
Stephen Barr: I mean, yeah, certainly I'm, you know, machine learning AI optimist, but It has to, it can't take the place, right? I think the pie should get bigger, right? It shouldn't redraw the pie.
Corey Quinn: I really hope reInvent's keynote is not a rehashing of what we saw at Google Cloud Next earlier this year, wherein the entire keynote was about AI, and it never pivoted away from that.
The problem I'm seeing when these companies flood the zone like this is that when there actually is a fascinating and useful breakthrough, that hits from wherever it happens to come from, we're never going to see it because it'll just sound like, "No, no, this one is actually transformative and revelatory!"
It's- you've said that for the last five disappointing flops. So what makes this one different?
Stephen Barr: And I think that there's a line, right? And I think that Steve Jobs used to represent this as this reality distortion field, right? Where you want to be far enough ahead that it's optimistic, but not so far ahead that you have lost sight. They still have to have EC2 instances and databases and managed services and that sort of thing.
Corey Quinn: And I've talked to customers, I fix AWS bills. I see the spend. There is an awful lot of money in cloud and a surprisingly small percentage of that is even tangentially related to AI.
Companies have not suddenly given up doing the block and tackle the things that, you know, generate the revenue and keep people employed. You're a 50,000 person company. You're not suddenly going to pivot everyone to AI. You're just not.
Stephen Barr: I mean, I guess I could speak for myself personally and the, you know, the company where I'm at.
I think right now people are doing the similar things, but they're doing it differently. Like right now, like whenever I'm trying to do something, I'd spend some time with, "Okay, how can I do it with AI or using AI or trying to make the scale?" But it's also the classic programmer trap, right? Of how do I spend 40 hours to automate this 10 second job?
Corey Quinn: That's part of it. I've found that it's useful for certain things and not useful for others. One area where it excels, obviously, is coding assistance. That's, that is effectively a superpower. Every developer I work with these days is using some form of copilot or something similar. That is magic. Doing it, something similar for writing blog posts or whatnot, I find it helpful, but only because when I, when it spits something out, it is so bad that I feel the need to dive in and fix almost everything.
So there's like 10 percent of what that originally had that was there still, by the time I'm done, usefully for me, that's structure. So great, I've just filled in the content with things that aren't, you know, inane.
Stephen Barr: Yeah, I really like the using it to modify and to play with text and help me rephrase this another way and help me turn this notes into a more useful general content.
I think starting from zero and saying, "Write me a blog post about cost optimization," you're going to get out the effort that you put into it.
Corey Quinn: Oh yeah, but even that is helpful for those of us who struggle when staring at an empty screen.
Stephen Barr: Yeah, absolutely.
Well, I guess, so here's a question, especially with the coding assistants, for young people who are just starting with programming, like, how do you, I still wonder about that, because you know, I have kids who are of the age where they can start learning about programming, but like, is it now worth it to talk about, "Here's how you write a program," or should we just focus just on, "Here's how you use an AI assistant." I mean, because I don't know much about assembly language. I know the principles, but nothing beyond that. And is programming, is Python going to be assembly for kids?
Corey Quinn: I'm taking my guidance from educators, by and large. Math is a good example of this. Very often we'll see that, okay, we have calculators everywhere now.
They're in our pocket. They're ambient in the room around us. So being able to say, "Okay. You're not going to have a calculator with you," is ludicrous. But, I have a second grader who's still learning math without aid of a calculator because you need to understand what is reasonable for a calculator to return.
And I feel like there's a similar progression on this, but it comes down to what is your goal? Are you trying to be a computer scientist? Are you trying to get a job as a front end developer? As your first gig out of school or bootcamp? Are you just looking for something to keep the lights on 40 hours a week?
What is your goal here? I've always found that a deeper understanding of fundamentals is a terrific thing to fall back on when automated things break. Which they tend to do. We've all seen ridiculous suggestions from AI, some of them funnier than others. It's not nearly as funny when it makes it into production.
But there's a strong sense of you, you need to have a grown up looking at these things. But senior engineers can see this, sure, but where do senior engineers come from? We didn't just emerge from nowhere.
Stephen Barr: I love how you mentioned math. Have you read the essay Lockhart's Lament?
Corey Quinn: Not yet.
Stephen Barr: Okay. So it's about this math teacher.
He is terrified that he's talking about, imagine if music was taught the way math is, and you have to learn all of these scales and all of these theory before you could ever touch an instrument.
Corey Quinn: Isn't that how classical piano training works?
Stephen Barr: Well, the idea is you can just sit down at the piano and just start playing, try and make some noise.
And you can learn a lot just by playing. And I feel like with AI, I can play with programming more freely, but you're right. You still have to go back and learn the basics. You still have to go and learn, you know, algorithmic thinking and data structures to some extent, but being able to play more easily.
And I think a lot of, yeah, a lot of poor math education is basically like, learn all of this stuff, but you don't actually just sit there and play with a number, right? Draw a right triangle and try and, understand the relationships between the length of the sides or try and figure out why numbers, when you square them, are always positive or something like that, where you can just sit there and play and you don't have to, it doesn't have to be formal.
Corey Quinn: That's how I learned a lot of math. So much of it was just listening to teachers droning on about stuff that I already got the first time they explained it, and I'm just sitting there playing with numbers in a notebook because this was before the time you could just waste time on your phone. We could be bored back then, and the exploration that you just do for the fun and the joy of it is where you learn a lot.
Stephen Barr: Yeah. It's being second or third grade and we're doing those, what are those trigonometry proofs where you have the angle, side, angle, and it shows that, okay, if you have an angle and a side and an angle, then this, these two triangles are, what are they called, "congruent?"
I use some argument that we hadn't officially learned yet. It's like, well, you can't use that because we haven't been taught yet. But it's true, because if you have this and this, then that has to be true. Yes, we haven't learned it yet. I think some of this formalism can kind of beat the joy out of things.
Corey Quinn: Oh, yeah. I've, things I love when I find them being taught formally, become things I hate. I'm gonna get, I'm gonna get grief for this, I'm sure, but so often in English classes growing up, they pick some of the worst books, and you can tell those books are terrible because they won the Caldecott Medal, and they have the big seal on the front of it, and it is so heavy with meaning and symbolism that they forgot to tell an actual story, and it's just, like, I love reading, but this is crap. If I didn't already love reading, this certainly wouldn't help.
Stephen Barr: I'm remembering an online English class that I took, we were all supposed to write a comment on the book. And I said, "The thing I liked about this book is it led to one of the best naps I've had this year." It was so boring and incomprehensible, right?
There was no fun in it. There was no story. It was just lots of metaphor and simile and stuff to analyze, but there's no, there's nothing, there's no substance.
Corey Quinn: Which brings us back to AI marketing, which is what worries me because in many cases there is substance behind these things, but it's attenuated and it's difficult to get to a point where you can see it being useful.
And there's also a lot of defensiveness that factors into this. People are, in many cases, worried about when, how is this thing going to take my job away from me as a counterpoint? I don't see too many jobs accepted at the margins where that is a realistic possibility in the near term. So there is time.
Stephen Barr: If the crypto world is hard to sort out, AI is gonna be so much worse, right? And like I think that the fundamentals of cryptocurrency, like, it makes sense and I like it, but then on top of that little core of truth is this giant pile of scams and garbage and hype. And so I think with AI, it's gonna be even harder to kind of sort out what's hype, what is someone just with a cool website and going for venture capital and taking us off a ride versus, hey, this is a new innovation. This is a new model. I think that's going to be harder to sort out. And that's where we'll hopefully people, I'm trying to keep myself in the know as much as possible and try to be able to sort that back to the reference point for that.
Corey Quinn: You know, it's, I think there's going to come a future where this is just how computers work. Like, it just, it's unthinkable to sell a computer these days without an SSD attached. It's, similarly, it's going to, oh, of course it's going to have an AI compatible GPU equivalent. Whether it can actually display graphics or not is almost beside the point.
Stephen Barr: Yeah, maybe we've kind of, topped out on what we need in terms of graphics, but AI, uh, yeah, AI focused processors probably have lots of, lots of room to grow.
Corey Quinn: For text based LLMs, for the conversational stuff, I'm getting great results just on my existing Mac hardware, which is not bad. Terrific when it comes to GPU because that's never been its goal.
But the performance is just fine. I'm getting in some cases, what, 200 tokens a second?
Stephen Barr: Yeah, are you using like Ollama or what are you using?
Corey Quinn: I'm using Ollama with a bunch of obviously submodels under that where people have, where I've done a lot of, uh, I've done a lot of playing with some of the custom models, uh, people have tweaked and done some enhancements on top of Llama itself.
Of course, people playing with Gemini as well, as, or Gemma, whichever one the, the one that, uh, you can run locally is. Like, Google's bad at naming things. Who knew?
Stephen Barr: Yeah, it, uh, my most capable local machine is, uh, a Mac M2 Max, and yeah, I use Allama as well, and it is impressive what you can do locally.
Although I do wish I had maxed out the internal storage. I didn't realize we're going to be downloading these 70 gigabyte blobs.
Corey Quinn: Yeah, when I wound up building out my Mac Studio M1 Ultra back when the pandemic was just getting started, it was the first generation of Mac Studio. I went for the middle of the road processor, and I wish I'd gotten higher just for the GPU story on that.
Hindsight. Is it worth paying another $7,000 to correct the mistake? Eh, not so much.
Stephen Barr: I was in an Apple store just the other day, and it's like, I can't think of a reason to upgrade my stuff at the moment. This is an M1 Max, and then I have an M2 Max Studio, and...
Corey Quinn: Yeah, I'm on a laptop myself, M1 Max. It's, it, I got it as a quick laptop in a hurry for reInvent in 2021, and I haven't felt the need to upgrade it since.
Of course, I also travel exclusively with an iPad Pro, so I'm probably not the best example of this. If I need some actual heavy compute, well, that's what the cloud is for.
So, I'm curious as far as, what is your history with AWS? You've been around the ecosystem an awful lot. It's fun talking to folks who've been in this back.
We can remember when there were enough services that most people could hold them all in their head at the same time.
Stephen Barr: Okay. This is an interesting one. So, I was doing a research project with some professors at the UW. I was an undergraduate at the time, and they were finance professors. And we were looking at this lending marketplace called Prosper. And Prosper, it was a peer-to-peer lending platform where someone who was applying for a loan, say they wanted $5,000 to deal with a plumbing emergency, and they'd write who they were, and they'd have their standard loan information, but they'd also provide a writing sample and a photograph.
So you get all the standard loan information, right? What's their credit score? What's their debt to income ratio? That stuff. But you'd also have their writing and a photograph. Or several photographs. And at the time, we had a relatively new service. This was 2007, I think? We had Mechanical Turk. And so I wrote a bunch of Perl scripts for these professors to put all these images onto Mechanical Turk.
And for those of you who don't know Mechanical Turk, you can pay one cent or two cents or three cents, and you can get people to do these little jobs called Human Interface Tasks. A lot of those jobs are now replaced with image recognition, that sort of thing. But at the time you'd use it for, you know, looking for something in an image was a good use of that.
And so we'd ask, is there a dog in the photo? Is there a puppy? Is there children? And try to figure out, did these photos that people were putting in to their loan applications, did they add extra value in terms of people estimating probability of repayment, right? Maybe, uh, the people who put puppies in their loan photos, are they better loan candidates and why?
These were behavioral finance professors. And so I spent a lot of my undergraduate, my last year, writing a mountain of Perl scripts. I learned about Mechanical Turk. I actually, I asked my dad. So my dad, Jeff Barr, Chief Evangelist, AWS. I asked him, we set up a little meeting with these professors. And it was all, it was just such a little ecosystem at the time.
It was so fun just how, how small it was.
Corey Quinn: We wound up building out a lot of stuff in Mechanical Turk in the early days at Expensify for receipt optical character recognition on that and understanding what a receipt is, because there's, uh, there's a lot of variety in receipts. These days, systems are pretty decent at doing that, but, you know, 2012 when I was there, that wasn't the case.
Mechanical Turk was great for it. You'd spend fractions of a penny per read on this or a couple pennies and it would work out.
Stephen Barr: Yeah, absolutely. So that was my first exposure to AWS. Later I was in grad school and I was helping a, another finance professor. She had written this, she had this really expensive GPU rig, and she had written this simulation that had run for like three weeks on her desktop, running the simulation over and over again for different parameters.
And she had submitted this paper to get what is called reviewed by her peers, and she got really nervous that she wanted to make sure that the simulation was reproducible, but she only had three or four days to do that. And her simulation took three weeks to run on her local machine. And so at that time there were six regions.
And so I maxed out what my account could do, which was a hundred instances per region, and that was the first time I had written a program that could spend a substantial amount of money. And it was really simple architecture. It was pull from an SQS queue and committing private keys to GitHub. Yeah, I accidentally helped someone start a Bitcoin farm once.
Corey Quinn: I don't think that there are too many people from those days who didn't.
Stephen Barr: I'm so glad that GitHub will detect that now. That has saved many a person from financial ruin.
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Corey Quinn: What I find interesting is that the large scale of company that I tend to spend most of my time talking to, if there's a breach and someone gets keys and starts mining Bitcoin, it's a lot harder to detect because, yeah, my personal bill's what, $50, $70 a month, something like that, depending on how aggressive I've been with serverless that month.
And yeah, okay, now it's $5,000. I'm going to notice that or $50,000 or $500,000. Whereas when you're spending tens of millions of dollars a month, that starts to really disappear into the background noise. You gotta be paying a lot of attention to even notice it happens.
Stephen Barr: Oh gosh, I was working for a company that shall remain nameless, but they gave every consultant and every person who needed it the same Root credentials to their AWS account.
Everybody, there's no...
Corey Quinn: In my early days, someone emailed me theirs, which scared the crap out of me.
Stephen Barr: And so they had this app that could have run on a Raspberry Pi, and the spend was like $30,000 a month and growing. And they didn't know what to shut off and what not to, and it was a, it was a well funded organization, so they could kind of live with this.
And I think there was some accounting maneuver to subdivide this, but yeah, it was really terrifying what can happen through these bad practices.
Corey Quinn: Oh yeah, I care a lot less, to be very transparent, about the big companies taking the unexpected financial blows. They can absorb those. It's the independent learners who are just figuring out how this stuff works.
Maybe they trust the wrong person on Discord or Whatnot and suddenly they're staring at what they believe to be an insurmountable amount of money. $700,000, that's more than I'll ever make in the course of my life. Which is not generally true, but it feels like the world is ending then, and AWS has never been great at making people feel reassured while they're looking into that.
I haven't heard too many stories where they haven't made it right, at least the first time. But you're twisting in the wind for a week or two first, not knowing.
Stephen Barr: Yeah, there's that moment where you're like, "Oh my gosh, what am I going to do?" And does it even cross your mind? Okay, do I, if I get on chat, are they going to forgive me if I call up support?
And yeah, like you said they usually let you off the hook unless you are phenomenally egregious and have done this multiple times. But if, you know, if they determined that it was a genuine mistake, they'll look after you. Yeah. It can be frightening to get a bill that's, Multiple times your monthly income.
Corey Quinn: Oh yeah, it's horrifying, and I'm just glad that it seems like I haven't had seen nearly as many of those stories lately.
I think a change that is absolutely for the better that is in the process of rolling out is mandating MFA when you spin up an AWS account. It's- so many other things mandate this, and it's just such a no brainer.
Well, it'll act as a brake on growth. If someone's not willing to give a phone number for a text message or use Authy or something like that, then I don't know that you want them in your cloud environment in the first place, do you?
Stephen Barr: No, I agree with that. Use MFA. That is a good idea, and even the inconveniences that it can sometimes cause, like, you know, if you're not good with your backups and you lose your phone, well, yeah, that could hurt.
You're gonna have to go through some, you know, some manual steps to deal with that. But the blast radius protection that it gives you is well worth that, and that's what we always say. Limit your blast radius, right? If you have an AWS account, you can turn off people being able to start GPU instances or the SAP HANA instances, the X ones.
You don't want to accidentally turn one of those on.
Corey Quinn: I haven't- I confess, I haven't put a lot of those in place for our internal corporate org, just because everyone who has access to touch that stuff has multiple years of experience within the AWS universe. So there's, at some point, we're absolutely going to have to get some religion around stuff like that.
And we do have segregation of who can look at data, but at this point, it's assumed that, oh, if you're spinning up a GPU instance, you probably know what you're doing. Maybe it's time to revisit that assumption.
Stephen Barr: Yeah. I think we have it in our larger org just to make sure. Okay. And it's not to stop people, but it's saying, okay, there's a hurdle because this? This hurts. So just make a hurdle in place so that you, if you're doing this, you know that you're doing it.
Corey Quinn: Don't- it's principle of least surprise on some level I think is really where it winds up hitting. Speaking of surprising people, so when you talk to folks who have been at big companies, And are being confronted with areas for improvement when it comes to their, their cloud spend, you and I were talking about this earlier. It's why I call myself basically marriage counseling between engineering and finance. There's a lot more people and behavioral aspects to this than there are raw math. The reason that cloud costs are complicated is only partially due to the fact that arithmetic is hard.
There's a lot more to it than that. What's your take on it?
Stephen Barr: I completely agree that many of the issues are people issues, right? People who might be scared of change, or want to protect territory, and don't want any- there's a lot of those types of things. And also, people don't want to look bad, their careers are on the line, so if you say, "Oh look, we can save you this amount of money."
It's easy for someone to react and say, "Wait, why didn't you do that? You were my AWS person. Why do we have to hire these external people who are then pointing out what you should have been doing in the first place?" But that's what you don't want is this finger pointing to start happening.
So ideally when people see the savings that can do that, they have to say, "Okay, I know you were doing the best you can. We brought in some experts to help you. And look, there's so much more on the table. We're really excited. Now we can do this project and that project." And you're right. It's a marriage counseling to kind of help people see it the second way and not the first way.
Corey Quinn: The tack that I like to take is I approach it from the perspective of, look, no one is going to build something successful while trying to do it for the absolute least amount of money physically possible.
The fact that I'm talking to these people is a sign that they've succeeded to the point where, okay, now it's time to come in and do some optimization. I stressed the blameless aspect of it extensively, because even in my own accounts, I could go through and find significant savings if I could be bothered to do it, but it's a saying. "Yes to focusing on that means saying no to something else." Where do you draw the line? What is the priority? Because when everything's the priority, then nothing is. Where do you want people's energies focused? Because there's a certain mindset, and I admit I'm one of them, where you can, I will spend gleefully a month just knocking a few hundred bucks off the AWS bill.
I cost more than that. So what is the actual value that I'm contributing? At some point, I, one of my roles is to tell people, "Okay, stop saving money here, and go back to doing the thing your business does."
Stephen Barr: That's a really, really good point, right? There's only- there's diminishing returns to this process.
That's why having to automate what you can, I think we're big believers in that. So, for example, GP2 to GP3, right? That should be automatable.
Corey Quinn: I view them in buckets on some level. Like the first pass is generally, okay, great. Click three buttons and you'll save 10 percent. The next 10 percent is going to require some re engineering work, and the 10 percent after that is borderline taking hostages in Seattle.
So there's a, it gets harder and harder once the low hanging fruit gets found and, and sorted out. But there's also a question, increasing the enterprise of how you handle governance. How do you get 15,300 teams all rowing in the same direction?
Stephen Barr: And that's where it has to be- it's that relational thing, getting the top down buy in, but then also having the credibility with the engineering teams.
Hey look, we're doing things, this is- we know our stuff. We're trying to do things that are generally applicable, and that's the other thing we find. I'm sure, you know, people in my position, your position, you get to see a lot of different AWS accounts, and so you can think very generally about them.
Whereas often when you talk to someone at their company, and they've been there 10 years, and they've nurtured it from the very first, EC2 instance up to where it is today, it's very easy to convince yourself that no one else uses AWS like we do.
Corey Quinn: It's one of those ideas where, you're right, at enterprise scale, no one is going to use it exactly like you do.
But there are patterns, history rhymes, there are, okay, great, maybe your naming structure is different, but you're still going to run into the same foundational problem that other companies are.
Stephen Barr: I mean, it's like the marriage counseling example again, right? You're doing this.
Corey Quinn: And messaging is tricky of this because you can't give it as a consultant under the tagline, "You're not special." It does not go well, because who, who wants to be like everyone else?
Stephen Barr: Yeah, exactly. But at the end of the day, they said there's patterns, there's things that you can do that are generally applicable. And that's what one of, like talking to private equity firms who have a portfolio of companies, and they want a policy across their companies.
That often resonates a bit better, we found, because they're in the mindset of thinking at a process level about companies and a process level about operation, whether than like some idiosyncratic, here's the one AWS account for this one, I don't know, company.
Corey Quinn: There's a lot there, but I do want to get to one more topic before we call it an episode, because you are a Chief Evangelist.
Huzzah! Talk to me about content creation. What's your process?
Stephen Barr: Quick self-promotion. We have a show, AWS Made Easy. Myself, my co-host, Rahul Subramaniam try and stream every week. We interview AWS guests. We try and cover AWS news. We rate and review articles, that sort of thing. I got some really great advice early on, which was get to 20 episodes.
And I heard somewhere that like on the Spotify distribution, most podcasts are like three or four episodes, and then they just vanish, right? It's a couple of people, they meet up for a few drinks, do it in their garage, launch a podcast, they lose momentum. So my first thing was get to 20 episodes, and then we did that.
So number one is prioritize shipping it over quality. And I'm sure you've seen that, you know, with video editing, there is no end to how much you can kind of polish an episode.
Corey Quinn: I've never touched it. I've always just handed it off to professionals. It's the most common piece of advice I give to people who ask me when they're starting out.
I was like, okay, what microphone, camera, et cetera, should I buy? Doesn't matter. Doesn't matter. You can record something just fine on your smartphone to get you started. If the content's good, people will forgive an awful lot in production value, and if your content isn't good and isn't compelling, it doesn't matter because no one's going to stick around to see it.
It's trash, but it's so well produced, trash doesn't matter. No one wants to watch trash. There's an attention economy.
Stephen Barr: I agree, but also, at some level, you do need to pay attention to that stuff. And maybe it's just, you know, when your head gets into it, you hear a great piece of content, but you're like, It sounds like it was recorded in a bathroom.
But maybe that's part of having been in that content creation space for a while, right? Maybe I would have never noticed it before, and now I notice. That's almost how, like, people, audiophiles say that it kind of ruins music for them. Because they say, "Oh, it doesn't sound right. It was recorded on this instead of that."
So in general, try and prioritize shipping. Try and do the best we can quality wise in a bounded box of time and money and effort. And yeah, most importantly, like I said, make it usable, and try and distill down our experience of, you know, dealing with a lot of AWS accounts to make it useful for people.
People will be able to submit questions and we try to make shorts and clips. That's been really nice to be able to give people a small taste of it because, you know, our episodes are an hour-ish, and being able to have a 60 second clip that shows, it just plants a seed and then a link to more, that's been really nice.
Corey Quinn: It's nice to see people grow, but I think that people also try to early optimize that.
Stephen Barr: And the problem is there's no end to it, right? There's literally no end. And then as a tech person, right, it's fun to nerd out on the gear and the stuff and the switchers and the distribution. And then you have the AI layer, which is, can I automate everything?
Corey Quinn: And then it takes 30 minutes to get your audio working to join a Zoom call. I've been there.
Stephen Barr: Yeah, exactly. I mean, if I open up my audio devices, it's like nine different things, right? Because you keep changing your setup. Okay, sorry, is it this one? Is it that one? Is that one? Oh, wait, I'm on my UMC 404 HD today and not my Blackmagic.
But I think it's with any approach, right? Try to do the best you can within a bounded level. And ideally, it's about the listener and adding value for them, and we always try to ask our listeners for feedback, answer questions when they ask. Not making it about ourselves, but about remembering who the audience is and try to add value for them.
Corey Quinn: I find that you have to write with someone in mind. Otherwise there's, you're just speaking in generalities and it doesn't help.
Stephen Barr: Yeah. Yeah. Think about who, who is our persona? Persona is someone who, you know, they have AWS, managing their AWS account is one of their many responsibilities, and if they listen to us, they can pick up something useful that can help them without having to hit refresh on the AWS What's New page like you and I do.
Corey Quinn: Exactly.
I have one last question for you because I'm going to invite you to embarrass yourself as, you know, it is always the way it works when you make predictions. Where do you see the future of technology going? You've been around in this space a long time. I have as well. Where do you think the future is in darkness?
Is it awesome stuff? Is it something in between?
Stephen Barr: I'd like to be an optimist, and I hope that we're heading more towards the Star Trek universe than a dystopian future. I think about some of the building blocks that we're working with right now with LLMs and all the generative things. There's a great scene in Star Trek First Contact where the crew of the Enterprise is transporting to earth and they've traveled back to the late 21st century, and they say, "Okay, beam us down. Switch us to late 21st century civilian clothing," and thinking about okay what had to happen for that to work right there has to be some AI about well what what clothing were the civilians of this time wearing and what were they doing and there's a lot of stuff that had to happen in order to make that work.
And I think we're playing with those building blocks right now, right? That our descendants are going to be playing with, you know, Bedrock 3.0, which might power a transporter. So maybe that's the case, or I'm hopeful that's the case. The flip side of that is the amount of monitoring that we can do on ourselves and trying to squeeze the humanity out of some of the processes in the name of, I don't know, efficiency.
So I worry about that. I'm hoping that- in general, I'm an optimist. So I want that. I'm hoping that we tend towards the Star Trek outcome.
Corey Quinn: I do too. I really hope you're right.
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?
Stephen Barr: Find me on LinkedIn, Stephen J. Barr. Type that in, look for a guy with my face, and that's probably me. So, thank you.
Corey Quinn: Stephen Barr, Chief Evangelist at CloudFix. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a 5 star review on your podcast platform of choice, whereas if you hated this podcast, please leave a 5 star review on your podcast platform of choice, along with an angry, insulting comment that your descendants using Bedrock 3.0 will one day discover.