I assume you mean cost / performance as in Cost to amazon and not price as in price paid by consumers? Because Graviton is both faster and cheaper per vCPU. ( Amazon unit for a single thread )
>AWS taking a short term margin hit
It is hard because even if you can reliably extrapolate the cost of Graviton chip by wafer price. You will never know how they put the R&D into accounting. Do you have NRE cost in every single one those chips? ( which is what most people assume but not necessarily true ) Or do you move the whole R&D of Graviton into whole AWS R&D budget? And then you will have to calculate the power usage per workload to work out the power saving which gives you the TCO. Since 30%+ of Operating cost are going to energy usage. Being power efficient is also extremely important at the scale of AWS.
All in all I do not believe that Amazon is takin a short term margin hit ( and I dont understand where this narrative came from ), it is cheaper to produce, it uses less energy, and Amazon is pricing it as such, slightly cheaper than Intel and AMD's counterpart. Just like they did with the first generation of ARM. Graviton actually being faster per core just happens to be a bonus.
One has to remember. Moving to ARM / Graviton instances isn't free. You have to do your own testing and benchmarks to make sure it is indeed faster for your Apps. And that isn't always the case. You also have to make sure every part of your stack compile and works 100% on ARM. It just happens the cost saving is so gigantic lots of companies are spending time to move, which create a positive feedback loop in both open source and proprietary software to move towards ARM.
The paranoid might suggest it is coming from Intel's PR team, who might want AWS customers to believe that the savings might not be sustainable.
This would only make sense if Intel and AMD are still the dominant platform for Amazon. But in reality nearly 50% of all new EC2 instances built on are Graviton, and they are only limited by TSMC capacity. ( Or more like Amazon inability to predict the Graviton demand ) in another year or two this could close down to 70-80%. Last time I heard this pace is two years ahead of their internal estimate and schedule. And most of these deals were signed years before, i.e Amazon are still enjoying discounts while producing Graviton. So I dont think discount from Intel and AMD factor much into those decisions. If Intel no longer give discount AWS just purchase more from AMD. Amazon has all the cards in these deals. Not Intel or AMD.
a1/32gb/16vcpu (early graviton) @ 8c and
M5zn/48gb/12vcpu (late Intel) @ 12c
I think the intel is better value. What are those graviton instances with better value (given that they are probably much slower than Intel)?
Intel instances are significantly more expensive when considering the cost for performance. In fact it's not even close [0].
[0] https://www.anandtech.com/show/15578/cloud-clash-amazon-grav...
The key part being the cheapest available Graviton and Intel spot instances:
a1/32gb/16vcpu (early graviton) @ 8c and
versus:
M5zn/48gb/12vcpu (late Intel) @ 12c
Perhaps that will change as Graviton ages and availability changes.
Fair enough - I was trying to provide some data showing that Graviton is on par and exceeds cost/performance value in some cases.
> Perhaps that will change as Graviton ages and availability changes.
Graviton isn't standing still - AWS bought Annapura labs in 2015, so while older versions of Graviton will obviously shift left in terms of it's value, AWS is going to continue to push in that direction. Graviton 3 was recently announced [0].
[0] https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-ec...
My framework runs a fairly simple pipeline: for each 1GB file, stream it from S3, decompress it, search it with a regex library, stream results back to S3.
A1 spot instances have consistently been cheaper for this task when measured on a $/GB scanned basis. Part of this might be that the framework doesn't need lots of RAM, so paying for more than 2GB per core on the non-A1 instances is just wasted expense for me.
Lambdas can be cost effective for bursty loads, but if you can push sustained CPU utilization, as this example does, EC2 is cheaper.
For example, an ARM-based Lambda with 2 GB of RAM running for 1 hour is $0.09. An a1.medium is $0.025/hr on-demand or $0.0084/hr spot.
Part of this is that Lambda scales your CPU performance with your memory usage. So even if your code can run in 128 MB of RAM, there's no cost benefit to you if it's CPU-constrained, because it will run 16x slower than if you allocated it 2048 MB of RAM.
If there are custom instructions added, AWS customers aren't aware of them. Feature set pretty much unchanged too. It's a non-effect on that front.
Also the field is not static. Amazon does a lot of lobbying. Let's imagine you can check a certain legal compliance box simply by running on graviton.
Or the next industry trend which might be funded and hyped by AWS requires a specific feature for isolation that only really works on graviton.