5 ms·

Now if they'd only throw in S3 for pseudo-infinite data storage, reliable SQS for work queue management, 10/25/100 Gigabit networking between the instances, red

Now if they'd only throw in S3 for pseudo-infinite data storage, reliable SQS for work queue management, 10/25/100 Gigabit networking between the instances, redundant power supplies and cooling and racks in carefully selected stable locations for free, I'd buy a dozen!

KaiserPro 8y ago
Using both S3 and SQS outside of AWS is perfectly possible, and the Colo provides decent bandwidth, cooling and power, that's literally the point of them
sudhirj 8y ago
I never get the point of these things. This is like saying a Raspberry Pi hooked up to your home router is cheaper, why bother buying Gmail for your company. Or like saying that if you spend 20 hours every day in an Uber buying a car would be cheaper over 3 year term. Nobody is disputing that buying similarly specced hardware on the market is likely to have a cheaper TCO, the point of cloud providers is that also have a bunch of stuff attached to the servers, which turns to be pretty important.
- hughesjo 8y ago
  Most HN devs downvoting here never worked on real scalable systems to even understand what you are talking about, tbf
  - dang 8y ago
    Could you please stop posting unsubstantive (and in this case, supercilious) comments to Hacker News? If you know more, it would be really good for you to share some of what you know, so that we can all learn something. If you don't want to take the time to do that, that's fine, but in that case please don't post. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
  - vidarh 8y ago
    Because the vast majority of systems never need that scale. In other words: while it's an interesting niche situation, to most people how to handle small static workloads is much closer to what is actually relevant to them.
- bubblethink 8y ago
  The point is that GPU instances are different. The usecases like ML training or general HPC are sufficiently isolated from the rest of your stuff that you don't really need all the bells and whistles that aws has. If you want to host a niche gpu database like production system, you may get more out of aws's ecosystem, but even then, the cost difference is huge.
- dwild 8y ago
  > This is like saying a Raspberry Pi hooked up to your home router is cheaper, why bother buying Gmail for your company. Where do I get GMAIL for my Raspberry Pi? If you order that Lambda server, you get the same good Linux interface you'll get over AWS. In fact they actually seems to offer some kind of software package that you wouldn't get over AWS. Sure AWS has value-added, but in this case, it's mostly being able to not being billed for unused hours (what we call scalability), which for many is certainly worthwhile, but that's all. Is there anything I'm missing that AWS offer? > if you spend 20 hours every day in an Uber buying a car would be cheaper over 3 year term. Isn't that the case? I failed to see what's wrong in that sentence. I don't own a car, I subscribe to a service similar to Car2Go, I'm at about 150$ a month right now. Sure there's value added there, but owning one also has value added, just different ones and at one point it will be more worthwhile to own one.
paulddraper 8y ago
An availability zone or two wouldn't hurt either.
vidarh 8y ago
The price includes $15k/year colocation costs. That easily covers the redundant power, cooling, rack space, massive amount of bandwidth and redundant network network connections. Last place I handled colocated servers, we spent ~$17k combined for racks in two different data centres hosting a combined ~60 servers, so $15k/year for a single server is a very conservative estimate. If you're buying more than one, that'll easily cover enough to cable up whatever network you want between them. Many colo providers also have their own cloud services, and nothing stops you from using S3, SQS and the like, though of course if you use AWS services "from the outside" you do need to factor in their extortionate outbound bandwidth charges.
mippie_moe 8y ago
Lambda engineer here (I'm one of the authors). As bubblethink already mentioned, the article is arguing that batch processing jobs (e.g. those characteristic of Deep Learning) don't benefit substantially from cloud infrastructure. High availability, edge processing, fast network upload, and the lego blocks for creating redundancy are moot. Most training algorithms automatically recover if a node goes down. That covers all required failure handling.

KaiserPro 8y ago

Using both S3 and SQS outside of AWS is perfectly possible, and the Colo provides decent bandwidth, cooling and power, that's literally the point of them

sudhirj 8y ago

I never get the point of these things. This is like saying a Raspberry Pi hooked up to your home router is cheaper, why bother buying Gmail for your company. Or like saying that if you spend 20 hours every day in an Uber buying a car would be cheaper over 3 year term. Nobody is disputing that buying similarly specced hardware on the market is likely to have a cheaper TCO, the point of cloud providers is that also have a bunch of stuff attached to the servers, which turns to be pretty important.

hughesjo 8y ago
Most HN devs downvoting here never worked on real scalable systems to even understand what you are talking about, tbf
- dang 8y ago
  Could you please stop posting unsubstantive (and in this case, supercilious) comments to Hacker News? If you know more, it would be really good for you to share some of what you know, so that we can all learn something. If you don't want to take the time to do that, that's fine, but in that case please don't post. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- vidarh 8y ago
  Because the vast majority of systems never need that scale. In other words: while it's an interesting niche situation, to most people how to handle small static workloads is much closer to what is actually relevant to them.
bubblethink 8y ago
The point is that GPU instances are different. The usecases like ML training or general HPC are sufficiently isolated from the rest of your stuff that you don't really need all the bells and whistles that aws has. If you want to host a niche gpu database like production system, you may get more out of aws's ecosystem, but even then, the cost difference is huge.
dwild 8y ago
> This is like saying a Raspberry Pi hooked up to your home router is cheaper, why bother buying Gmail for your company. Where do I get GMAIL for my Raspberry Pi? If you order that Lambda server, you get the same good Linux interface you'll get over AWS. In fact they actually seems to offer some kind of software package that you wouldn't get over AWS. Sure AWS has value-added, but in this case, it's mostly being able to not being billed for unused hours (what we call scalability), which for many is certainly worthwhile, but that's all. Is there anything I'm missing that AWS offer? > if you spend 20 hours every day in an Uber buying a car would be cheaper over 3 year term. Isn't that the case? I failed to see what's wrong in that sentence. I don't own a car, I subscribe to a service similar to Car2Go, I'm at about 150$ a month right now. Sure there's value added there, but owning one also has value added, just different ones and at one point it will be more worthwhile to own one.

paulddraper 8y ago

An availability zone or two wouldn't hurt either.

vidarh 8y ago

The price includes $15k/year colocation costs. That easily covers the redundant power, cooling, rack space, massive amount of bandwidth and redundant network network connections. Last place I handled colocated servers, we spent ~$17k combined for racks in two different data centres hosting a combined ~60 servers, so $15k/year for a single server is a very conservative estimate. If you're buying more than one, that'll easily cover enough to cable up whatever network you want between them. Many colo providers also have their own cloud services, and nothing stops you from using S3, SQS and the like, though of course if you use AWS services "from the outside" you do need to factor in their extortionate outbound bandwidth charges.

mippie_moe 8y ago

Lambda engineer here (I'm one of the authors). As bubblethink already mentioned, the article is arguing that batch processing jobs (e.g. those characteristic of Deep Learning) don't benefit substantially from cloud infrastructure. High availability, edge processing, fast network upload, and the lego blocks for creating redundancy are moot. Most training algorithms automatically recover if a node goes down. That covers all required failure handling.