The Amazon Prime Day 2023 AWS Bill
lastweekinaws.com
lastweekinaws.com
Amazon Prime Day event resulted in an incremental 163 petabytes of EBS storage capacity allocated – generating a peak of 15.35 trillion requests and 764 petabytes of data transfer per day.
Once a metric becomes a target for optimization, it often loses its value as an indicator of a larger goal. People who obsess over A/B tests rarely understand that.
As we hit these levels we asked them - how many trades are we even doing on this system? The answer was something on the order of.. 50. Granted it was a bond system and the nationals are huge, but theres just no reason to store 20GB per trade.
These are the kinds of decisions that get made when one team is responsible for message generation and the other is responsible for the storage, lol.
We then had to work backwards with them to unwind a lot of the INFO level chatty messaging between what you'd now call "microservices" and reduce the volume by 90+%.
After looking at screen after screen of no-name garbage on Prime Day, I gave up. I suspect that there are tons of people like me. In other words, we only contributed to the numerator, not the denominator.
Although, that does bring up the question of why AWS doesn't have a way to share a single read-only volume across multiple ec2 instances in the same availability zone. In many workloads there isn't any need to write to disk.
Also, it specifically says "incremental capacity allocated", not necessarily used. Keep in mind that every EC2 instance launched also means new EBS storage is allocated. The article also estimates that 50 million EC2 instances were used for Prime Day. If you assume that half of these were newly created to support the surge of Prime Day, 25 million instances using up 160 PB of storage is only 6 gigabytes per instance, which definitely seems in the realm of possibility.
Well it's not amazing if your margin's are tiny, as they are in many industries (such as retail). Plus this was almost certainly architected by some of the foremost AWS experts in the world. It's verrrry easy to spend vastly more than was strictly necessary in AWS.
I don't mean to be too negative though, it was a really interesting article. Pretty wild to think about spending $100m on infrastructure over two days and still making a bunch of profit.
The listing data is almost static and should almost fit in RAM (the hot set probably does. Apparently Amazon has ~350M listings. A 24TB RAM server could give ~68kB/listing, and probably only a small fraction is hot). Since you'll need multiple servers anyway, you could shard on products and definitely fit things in RAM. 375 million sales even if condensed into 1 hour would only be 104k/second. A single db server should be able to handle the cart/checkout. Assuming ~10M page views/second, a couple racks of servers should be able to handle it.
The ad/tracking infrastructure surely can't account for the 1000x disparity in resource usage.
Modern NVMe drives get 1000x the performance of hard disks 10 years ago. You can buy one that can fit the entire reddit text database for $150 now. 10 years ago you'd be looking at a high six-figure SAN appliance from IBM or EMC to get the kind of performance my desktop has now. You can have TBs of RAM and 100+ cores in a server now. You can get 400 Gb/s networking now, and some people even have 10 Gb/s home internet. You could basically run some of the biggest sites from 10 years ago out of your closet these days.
Some software has also improved a lot in the last 10 years. Things like io_uring are great. Green threads are great. Postgres is super fast these days, and it keeps getting faster. My old quad core computer with a SATA drive can already do ~60-70k requests/second with a Scala web app and postgres. That's without even using graal or loom or trying to screw around with core affinity.
If anything, the cloud scales poorly. People in practice end up using vastly underpowered VMs, and then horizontally scale them, which introduces a ton of overhead (computationally and management-wise). RDS gets you like 3000 IOPS baseline and increasing that to the level of a single NVMe drive will cost one employee's firstborn child each month, so people end up with this mistaken belief that RDBMSs are slow or don't scale. AWS will provide you with reference architectures to use lambdas for web requests and advertise their "scalability" [0], but the API only lets you serve 1 request/lambda at a time, and according to their docs, you can only have up to "tens of thousands" of concurrent lambdas[1]. That would also require 10s of thousands of connections to your db, which kills it, and doesn't let you batch things unless you first put your work onto something like an SQS queue and have a separate db worker lambda pick up batches. More infra to manage (and more $$$) instead of writing a dozen lines of code to add an in-memory work queue, and you end up needing to write more code to deal with sending work/status across the system anyway. So my old i5 with an SSD ends up scaling better than their "well-architected" "scalable" serverless solution. AWS will happily give you plenty of this kind of advice that will lead to a slow, expensive, large system.
The one big upside of AWS is that if you do need to manage a lot of servers (like you are in the IoT space and need to handle millions of requests per second), they have good tools for doing that. Multi-region redundancy is also a click of a button if you need that. But they normalize overbuilding (and thus needing that management) way before it's necessary.
[0] https://docs.aws.amazon.com/wellarchitected/latest/serverles...
[1] https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-...
Be it Prime Day or Black Friday/Cyber Monday sales, I've seen the prices before the sale starts, and then once the sales start, it is the same price but with a slashed out higher MSRP type price. It's not any more of a sale during the sale than it was any of the other days.
Of course Amazon is paying itself that premium so they have little incentive to care.
You can absolutely spend an arm and a leg making a system work using a RDBMS that would be simpler and cheaper using a NoSQL store. The opposite is also true.
When picking a database you should always consider the trade offs of the different technologies and weigh those against your goals and budgets.
Sometimes is okay to spend more for a system that is just simpler to manage and use. Sometimes it’s not.
I imagine there would be a ton of Lambda and the like in there too.
RIs for their RDS instances. Saving Plan for their EC2s.
1 or 3 year commit, no upfront vs all upfront, etc.
A customer at the size of Amazon using AWS would have private pricing arrangement and an EDP.
When they realized their entire attack was just a fraction of what Amazon handled during the Holiday shopping season, they realized the futility and called it off.
Is Amazon’s general architecture for their retail site publicly described anywhere?
Do they do this? I have asked some friends who are developers at AWS and both told me that they don't worry or even know what their usage costs. But that's just anecdote; perhaps their boss knows.
I would ABSOLUTELY say that, at a minimum, every director or principal engineer needs to be familiar with costs and _should_ understand their P&L. Senior engineers and line managers probably/should have a passing familiarity or consideration. Individual random SDEs may not as its not their primary business function or deliverable and someone else is ultimately responsible.
Disclosure: Principal at AWS, opinions are my own.
Hmmmm….
That said, why would capacity issues be behind NDA? Anyone can grab their API and attempt to allocate a VM (or 100k)
You can't spin up 100k instances on a virgin account, but it's an interesting idea!
With AWS still growing they are constantly having to add hardware. Ahead of Prime Day, I presume they just bring forward new resources that their model otherwise says aren't needed for a few months.
Unavailability for other customers indicates either AWS growth has plateaued, they have hit the limit of throughput of how much hardware they can provision, or they just did their sums wrong.