AWS Morning Brief Whiteboard Confessional: The Core Problem in Cloud Economics
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.
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Transcript
Corey: Welcome to AWS Morning Brief: Whiteboard Confessional. I’m Cloud Economist Corey Quinn. This weekly show exposes the semi-polite lie that is whiteboard architecture diagrams. You see, a child can draw a whiteboard architecture, but the real world is a mess. We discuss the hilariously bad decisions that make it into shipping products, the unfortunate hacks the real-world forces us to build, and that the best to call your staging environment is “theory”. Because invariably whatever you’ve built works in the theory, but not in production. Let’s get to it.
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Corey: Welcome to the AWS Morning Brief: Whiteboard Confessional. Today we're going to tell a story that only happened a couple of weeks ago. We don't usually get to tell stories about what we do in the AWS bill fixing realm because companies are understandably relatively reticent to talk about this stuff in public. They believe, rightly or wrongly, that it will annoy Amazon which, frankly, is one of my core competencies. They think that it shows improper attention to detail to their investors and others.
I don't see it that way, but I found a story that we can actually talk about today in a bit more depth and detail than we normally would. So, we get a phone call about three weeks ago. Someone has a low five-figure bill every month on AWS. That's generally not large enough for us to devote a consulting project to, because frankly the ROI would take far too long. It's too small of a bill to make an engagement with us cost-effective, but we had a few minutes to kill and thought, “Eh, go ahead and pull up your bill. We'll take a quick look at it here.” Half of their bill historically—and growing—had been data transfer which, okay, that's interesting. And as we've known from previous episodes, data transfers is always strange. So, they looked at this and they said, “Okay, well, obviously then instead of serving things directly, we should get a CDN.”
So, then instead of getting a CDN, they chose to set up CloudFront, which basically is a CDN only worse in every way. And they saw no impact to their bill after a month of this. Okay, let's change that up a bit. Now, instead of CloudFront. We're going to move to an actual CDN. So, they did, there was a small impact to their bill. Okay, and costs continue to rise and what's going on? At this point in the story, they call us, which generally if you're seeing something strange on your bill, is not a terrible direction to go in. We see a lot of these things and if we can help you, we will point you towards someone who can. So, our consensus on this was, great. It is too small to look at the bill.
But let's pop into Cost Explorer and see what's going on. We break it down by service and S3 was the biggest driver of spend. Now, that's interesting. Number two was EC2. But okay, we start with the big numbers and work our way down. This is apparently novel for folks doing in-depth bill analysis, but we're going to go with it anyway. We start taking a look within that S3 category of usage type, and lo and behold, data transfer out to the internet is driving almost all of it. The cost per request is super low. That tells us in turn that—because we've seen a lot of these—that there are large objects, but relatively few requests for them.
So, all right, we're going to slice and dice slightly differently within Cost Explorer, AWS’s free—with an asterisk next to it—tool for exploring various aspects of your bill. That asterisk, incidentally, means that if you're doing this via API, it is one cent per call. If you're doing this in the console, it's free. Be aware, that can catch you by surprise if you write a lot of very chatty scripts. You have been warned. So, yeah, most of the spend was indeed on GetObject calls. So, okay, we know that data transfer spend was coming from an S3 bucket that was not going to a CDN. Otherwise, it's going to show up as a different data transfer charge in a different section of their bill.
Okay, so now we know it's S3. We have to figure out what bucket it lives within. And this is an obnoxious process, and we tell them this. And they’re like, “Oh, yeah, we know what bucket that is.” This, incidentally, is where almost every software tool tends to fall down. We could spend some time tracking this down programmatically. Or we can just ask someone who already has the context of what their business does and how it works loaded into their head. Because otherwise, what we'd have to do is tag all their buckets, and then wait a few days for that tag to percolate into the billing system, and then query it again because the visibility into this sort of thing is terrible. It's a shortcoming of both Cost Explorer and S3 in that weird seam between the two. There's fundamentally no easy way to see at a glance which buckets are costing you money unless you do something fun with tagging.
To that end, I'm a big believer in having every bucket tagged with a bucket name option. So, I can start slicing on that, and then you enable that as a cost allocation tag. So, great. Now, what is it that's getting requested? Well, you can also dig into this via access logs once you have the bucket, to see what's going on. Great. Now, we take a look at this, and sure enough—well, before I go into what it actually was, let's pause here for a moment.
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Corey: So, this bucket was set to public access. Aha! it only allowed GetO...