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One of the HUGE advanatages of GCE/AWS is that they will gobble up 100% of the unused resources for their own computation. Nothing is wasted, and the machines b

One of the HUGE advanatages of GCE/AWS is that they will gobble up 100% of the unused resources for their own computation. Nothing is wasted, and the machines basically pay for themselves. Compare this was something like oracle, which simply can't consume the unused resources in order to discount the hardware effectively. They can't beat GCE/AWS at the cloud game until this changes.

alberth 10y ago
Can you explain this in more detail about GCE/AWS bs Oracle. What "unused resources" are used for "their own compitation"? How does this "pay for itself"?
- ddorian43 10y ago
  He's saying they have their own apps (like google search) that can use vps that aren't currently rented to do their own computations (like pagerank etc).
reacharavindh 10y ago
Did you mean to say GCE/AWS could gobble up "unpaid for" resources for their own computation? Curious because if I pay for using a P100 for 2 hours - it is 100% available to me and not virtualized of any sort right? However, if I use it only for 2 hours that day, and no one else were ready and waiting to buy the time on those, then Google uses it internally until...
- boulos 10y ago
  From our post: > GPUs are offered in passthrough mode to provide bare metal performance. Up to 8 GPU dies can be attached per VM instance including custom machine types. When you're using it, it's 100% yours. Disclosure: I work on Google Cloud (and pitched in on this!)
matt4077 10y ago
I'm not sure if Amazon has enough batch-processing type work to make this effective. You can't run amazon.com with these resources because their needs are inflexible. Actually not sure about Google either – their preemtible instances are sold at an 80% discount, so that puts an upper bound on the usefulness of these machines for them.
- matt_wulfeck 10y ago
  Amazons largest "batch" job is their holiday shopping season. They must purchase the horsepower to get them through that season, and then the rest of the year they can resell it. I believe this was the original motivation for AWS.
  - prodigal_erik 10y ago
    A coauthor of the original proposal for AWS denies that: http://www.networkworld.com/article/2891297/cloud-computing/the-myth-about-how-amazon-s-web-service-started-just-won-t-die.amp.html http://www.networkworld.com/article/2891297/cloud-computing/...
  - deleted 10y ago
    [deleted]
  - dragonwriter 10y ago
    If it was, they'd have to shutdown AWS for the holidays.
honkhonkpants 10y ago
I'm curious to know what workloads you think Google is running on the same hardware that cloud customers are using.
- matt_wulfeck 10y ago
  All kinds of CPU intensive work. Isn't that most work?
  - hueving 10y ago
    No, a lot of work is IO bound. That's why M:N threading (e.g. Go's coroutines, python's gevent) is so popular.
- jfoutz 10y ago
  What an odd question. Seems like training a new voice recognition model, or image classifier, or any of a zillion other research projects google is working on would be perfect for any unused capacity. I've never worked at google. Do they just let each team go with their own crazy hardware setup? Or maybe two separate systems, one internal and one external? That seems a little wasteful (they have the money, so whatever). But wouldn't programming against a big unified api be a bit more, well, sane? I can see really sensitive stuff locked away on its own hardware, but the search front end? why not serve some JS or provide chrome downloads from a giant pool of common hardware? Things grow organically, and they might be technically locked into a specific layout right now, that's totally understandable. But, unused capacity is just capital depreciating steadily away with no gain. Soaking up every spare cycle doing something useful should probably be somewhere in the company goals.
  - honkhonkpants 10y ago
    Like I said, I'm just curious. Google has so much capacity that I'm not sure it would be important for their bottom line to move it between Google and customer workloads in quanta smaller than one physical machine. Your theory also requires Google to have a substantial standby workload that is currently not scheduled, doesn't it?
gruez 10y ago
source?
vgt 10y ago
I think there's a better way to think about economies of scale (looking at it through the lens of Google Cloud). Let's quantify your workload as "resource-seconds", what many of Google's services (and some AWS services, like Lambda) allow you to do is maximize resources and minimize seconds (assuming efficient parallelization of workload, which is afforded by Google's super-awesome Networking). Cost is the same to you, but you get your results faster. This is afforded by the scale and by the multi-tenant nature of underlying services. This model can only work when there's lots of folks using such a service. (work on Google Cloud Big Data)
syllogism 10y ago
It's really not about the platform being a "buyer of last resort" of the unused capacity. Think about the narrow band of values you need for that to work. Google must value these compute jobs highly enough to have them offset the unused capacity...But they can't value them so highly that they're worth buying hardware to make sure they run. And this has to remain true, even as the hardware gets much cheaper? Here's how I think AWS and GCE work... Imagine you buy some hardware. You have n=1 users, and so the variance on your compute needs is very high. You buy for peak use, so your median utilisation is low. Now imagine you have n=10,000,000 users. Again, you stock for peak use...But the variance is now much much lower. Your median utilisation is now much better.
- dekhn 10y ago
  I built a system at google called Exacycle which used idle cycles for computation. You can think of my system as the user of last resort. We ran MD simulations, drug docking, and ray tracing simulations of the LSST telescope (along with fundamental mathematical problems), then published the results from this for free. The economics of idle cycles in a large production environment aren't trivial to analyze, and anybody outside of Google speculating is likely to make a mistake.
  - manigandham 10y ago
    Isnt this what folding@home and similar services have been doing for decades now?
    - dekhn 10y ago
      That's correct. in fact, we were the largest (in terms of total simulation seconds produced) provider of resources to Folding@Home and worked with Vijay Pande closely on this effort.

alberth 10y ago

Can you explain this in more detail about GCE/AWS bs Oracle. What "unused resources" are used for "their own compitation"? How does this "pay for itself"?

ddorian43 10y ago
He's saying they have their own apps (like google search) that can use vps that aren't currently rented to do their own computations (like pagerank etc).

reacharavindh 10y ago

Did you mean to say GCE/AWS could gobble up "unpaid for" resources for their own computation? Curious because if I pay for using a P100 for 2 hours - it is 100% available to me and not virtualized of any sort right? However, if I use it only for 2 hours that day, and no one else were ready and waiting to buy the time on those, then Google uses it internally until...

boulos 10y ago
From our post: > GPUs are offered in passthrough mode to provide bare metal performance. Up to 8 GPU dies can be attached per VM instance including custom machine types. When you're using it, it's 100% yours. Disclosure: I work on Google Cloud (and pitched in on this!)

matt4077 10y ago

I'm not sure if Amazon has enough batch-processing type work to make this effective. You can't run amazon.com with these resources because their needs are inflexible. Actually not sure about Google either – their preemtible instances are sold at an 80% discount, so that puts an upper bound on the usefulness of these machines for them.

matt_wulfeck 10y ago
Amazons largest "batch" job is their holiday shopping season. They must purchase the horsepower to get them through that season, and then the rest of the year they can resell it. I believe this was the original motivation for AWS.
- prodigal_erik 10y ago
  A coauthor of the original proposal for AWS denies that: http://www.networkworld.com/article/2891297/cloud-computing/the-myth-about-how-amazon-s-web-service-started-just-won-t-die.amp.html http://www.networkworld.com/article/2891297/cloud-computing/...
- deleted 10y ago
  [deleted]
- dragonwriter 10y ago
  If it was, they'd have to shutdown AWS for the holidays.

honkhonkpants 10y ago

I'm curious to know what workloads you think Google is running on the same hardware that cloud customers are using.

matt_wulfeck 10y ago
All kinds of CPU intensive work. Isn't that most work?
- hueving 10y ago
  No, a lot of work is IO bound. That's why M:N threading (e.g. Go's coroutines, python's gevent) is so popular.
jfoutz 10y ago
What an odd question. Seems like training a new voice recognition model, or image classifier, or any of a zillion other research projects google is working on would be perfect for any unused capacity. I've never worked at google. Do they just let each team go with their own crazy hardware setup? Or maybe two separate systems, one internal and one external? That seems a little wasteful (they have the money, so whatever). But wouldn't programming against a big unified api be a bit more, well, sane? I can see really sensitive stuff locked away on its own hardware, but the search front end? why not serve some JS or provide chrome downloads from a giant pool of common hardware? Things grow organically, and they might be technically locked into a specific layout right now, that's totally understandable. But, unused capacity is just capital depreciating steadily away with no gain. Soaking up every spare cycle doing something useful should probably be somewhere in the company goals.
- honkhonkpants 10y ago
  Like I said, I'm just curious. Google has so much capacity that I'm not sure it would be important for their bottom line to move it between Google and customer workloads in quanta smaller than one physical machine. Your theory also requires Google to have a substantial standby workload that is currently not scheduled, doesn't it?

gruez 10y ago

source?

vgt 10y ago

I think there's a better way to think about economies of scale (looking at it through the lens of Google Cloud). Let's quantify your workload as "resource-seconds", what many of Google's services (and some AWS services, like Lambda) allow you to do is maximize resources and minimize seconds (assuming efficient parallelization of workload, which is afforded by Google's super-awesome Networking). Cost is the same to you, but you get your results faster. This is afforded by the scale and by the multi-tenant nature of underlying services. This model can only work when there's lots of folks using such a service. (work on Google Cloud Big Data)

syllogism 10y ago

It's really not about the platform being a "buyer of last resort" of the unused capacity. Think about the narrow band of values you need for that to work. Google must value these compute jobs highly enough to have them offset the unused capacity...But they can't value them so highly that they're worth buying hardware to make sure they run. And this has to remain true, even as the hardware gets much cheaper? Here's how I think AWS and GCE work... Imagine you buy some hardware. You have n=1 users, and so the variance on your compute needs is very high. You buy for peak use, so your median utilisation is low. Now imagine you have n=10,000,000 users. Again, you stock for peak use...But the variance is now much much lower. Your median utilisation is now much better.

dekhn 10y ago
I built a system at google called Exacycle which used idle cycles for computation. You can think of my system as the user of last resort. We ran MD simulations, drug docking, and ray tracing simulations of the LSST telescope (along with fundamental mathematical problems), then published the results from this for free. The economics of idle cycles in a large production environment aren't trivial to analyze, and anybody outside of Google speculating is likely to make a mistake.
- manigandham 10y ago
  Isnt this what folding@home and similar services have been doing for decades now?
  - dekhn 10y ago
    That's correct. in fact, we were the largest (in terms of total simulation seconds produced) provider of resources to Folding@Home and worked with Vijay Pande closely on this effort.