Episode description

About Corey Quinn

Over the course of my career, I’ve worn many different hats in the tech world: systems administrator, systems engineer, director of technical operations, and director of DevOps, to name a few. Today, I’m a cloud economist at The Duckbill Group, the author of the weekly Last Week in AWS newsletter, and the host of two podcasts: Screaming in the Cloud and, you guessed it, AWS Morning Brief, which you’re about to listen to.

Links

• A Cloud Guru Blog post, Lift and Shift Shot Clock: https://acloudguru.com/blog/engineering/the-lift-and-shift-shot-clock-cloud-migration 
• The Duckbill Group: https://www.duckbillgroup.com/

Transcript
Corey: This episode is sponsored in part by Catchpoint. Look, 80 percent of performance and availability issues don’t occur within your application code in your data center itself. It occurs well outside those boundaries, so it’s difficult to understand what’s actually happening. What Catchpoint does is makes it easier for enterprises to detect, identify, and of course, validate how reachable their application is, and of course, how happy their users are. It helps you get visibility into reachability, availability, performance, reliability, and of course, absorbency, because we’ll throw that one in, too. And it’s used by a bunch of interesting companies you may have heard of, like, you know, Google, Verizon, Oracle—but don’t hold that against them—and many more. To learn more, visit www.catchpoint.com, and tell them Corey sent you; wait for the wince.

Pete: Hello, and welcome to the AWS Morning Brief: Whiteboard Confessional. I am again Pete Cheslock, not Corey Quinn. He is still out, so you're stuck with me for the time being. But not just me because I am pleased to have Jesse DeRose join me again today. Welcome back, Jesse.

Jesse: Thanks again for having me.

Pete: So, we are taking this podcast down a slightly different approach. If you've listened to the last few that Jessie and I have ran while Corey has been gone, we've been focusing on kind of deep-diving into some interesting, in some cases, new Amazon services. But today, we're actually not talking about any specific Amazon service. We're talking about another topic we're both very passionate about. And it's something we see a lot with our clients, at The Duckbill Group is people treating the Cloud like a data center. 

And what we know is that the Cloud, Amazon, these are not just data centers, and if you treat it like one, you're not actually going to save any money, you're not going to get any of the benefits out of it. And so there's an impact that these companies will face when they choose between something like cloud-native versus cloud-agnostic or a hybrid-cloud model as they adopt cloud services. So, let's start with a definition of each one. Jessie, can you help me out on this?

Jesse: Absolutely. So, a lot of companies today are cloud-native. They focus primarily on one of the major cloud providers when they initially start their business, and they leverage whatever cloud-native offerings are available within that cloud provider, rather than leveraging a data center. So, they pay for things like AWS Lambda, or Azure Functions, or whatever cloud offering Google's about to shut down next, rather than paying for a data center, rather than investing in physical hardware and spinning up virtual machines, they focus specifically on the cloud-native offerings available to them within their cloud provider.

Whereas cloud-agnostic is usually leveraged by organizations that already use data centers so they're harder pressed to immediately migrate to the Cloud, the ROI is murkier, and there's definitely sunk costs involved. So, in some cases, they focus on the cloud-agnostic model where they leverage their own data centers, and cloud providers equally so that compute resources run virtual servers, no matter where they are. Effectively, all they're looking for is some kind of compute resources to run all their virtual servers, whether that is in their own data center, or one of the various cloud providers, and then their application runs on top of that in some form.

Last but not least, the hybrid-cloud model can take a lot of forms, but the one we see most often is clients moving from their physical data centers to cloud services. And effectively, this looks like continuing to run static workloads in physical data centers or running monolith infrastructure in data centers, and running new or ephemeral workloads in the Cloud. So, this often translates to: the old and busted stays where it is, and new development goes into the Cloud.

Pete: Yeah, we see this quite a bit where a client will be running in their existing data centers, and they want all the benefits that the Cloud can give them, but maybe they don't want to really truly go all-in on the Cloud. They don't want to adopt some of the PaaS services because of fear of lock-in. And we're definitely going to talk about vendor lock-in because I think that is a super-loaded term that gets used a lot. Hybrid-cloud, too, is an interesting one because some people think that this is actually running across multiple cloud providers, and that's just something we don't see a lot of. And I don't think there are a lot of clients, the companies out there running true multi-cloud, I think is the term that you would really hear. 

And the main reason I believe that not a lot of people are doing this, running a single application across multiple clouds is that people don't talk about it at conferences. And at conferences, people talk about all the things that they do when in reality, it's so wishful thinking. And yet no one is willing to talk about this kind of, oh, we're multi-cloud in like, again, kind of, singular application world. So, one thing we do see across these three, you know, models, at a high level, cloud-native, agnostic, hybrid-cloud, the spend is just dramatically different. If you were to compare multiple companies across these different use cases. Jessie, what are some of the things that you've seen across these models that have impacted spend?

Jesse: I think first and foremost, it's really important to note that this is a hard decision to make from a business context because there's a lot of different players involved in the conversation. Engineering generally wants to move into the Cloud because that's what their engineers are familiar with. Whereas finance is familiar with an operating model that does not clearly fit the Cloud. Specifically, we're talking about CapEx versus OpEx: we're talking about capital expenditures versus operating expenditures. Finance comes from a mindset of capital expenditures, where they are writing off funds that are used to maintain, acquire, upgrade physical assets over time. 

So, a lot of enterprise companies manage capital expenditure for all the physical hardware in their data centers. It's a very clear line item to say, “We boug...