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I don't think anybody will argue that if you have a specialised workload (CPU heavy, storage heavy, etc) there's definitely cost savings at scale for DIY over c

I don't think anybody will argue that if you have a specialised workload (CPU heavy, storage heavy, etc) there's definitely cost savings at scale for DIY over cloud. But the calculation is harder than that. People are terrible at estimating the ops personnel cost for DIY. Turns out it's hard running with minimal downtime, or engineering hardware + software to be fault-tolerant. It's hard to put a price on dev tools/APIs/doco/the whole eco-system. Especially for that last reason, I have never been "blown away" by Softlayer, even when their instances were way beefier than anything AWS/GCP offered. YMMV.

IgorPartola 9y ago
First I don’t mean SoftLayer’s cloud. I mean their physical boxes. A dual processor Xeon that is all your own is a lot. Second, it depends on your expertise. And you don’t need scale. I ran a successfully bit of infrastructure on SL with seven servers that was quite a bit cheaper than an equivalent AWS setup. I was pretty much solely responsible for the infrastructure and still my responsibilities included more than 80% coding and later management. Given my salary at the time, it was quite cost effective.
- imbkr 9y ago
  was the comparison based on on-demand instances or reserved instances? we reserve almost all of our instances within our company for 3 years and also get an extra discount on top of it. based on my calculations, i've seen AWS cheapest out of all. would like to know if i'm missing anything
  - IgorPartola 9y ago
    This was a few years ago so prices have changed on both sides. What I advocate is doing exactly what you did: do a comparison with actual numbers and performance stats instead of hand waving that the cloud is always best.
    - mgkimsal 9y ago
      another factor that gets overlooked some is on-hand skills and hireable skills. if you have experience (and/or your team does) with dedicated, that should probably be for a non-trivial in decision making. likewise if you have more aws/cloud experience (or have those skills available on staff), there's benefits to that. cloud skills don't magically happen - someone with minimal AWS skills can provide you with a setup that is more expensive to run, and possibly more insecure than a locked down dedicated box.
      - IgorPartola 9y ago
        Exactly. If you have expertise to run your own servers, and you don't have a spiky workload, maybe it's worth it. If you have cloud expertise, that may be the winner.
user5994461 9y ago
Well, you and the poster are about to be disappointed. I did the comparison recently for 512GB memory servers and Google Cloud is now the same price as SoftLayer, while AWS is a bit more. https://thehftguy.com/2018/01/15/the-inevitable-demise-of-ibm-softlayer-by-aws/ https://thehftguy.com/2018/01/15/the-inevitable-demise-of-ib... If you are willing to pay a lot of money upfront, which you are since you're talking about building your own datacenter, AWS and Google will both give you huge discount and be significantly cheaper than SoftLayer.
- IgorPartola 9y ago
  I don’t see any performance details in your write up. Is the SL server actually comparable to the GC one? I don’t know how to equate vCPUs to real world performance. Memory is easy to compare. But how does it stack up CPU-wise. Another question is whether lower tier servers compare favorably or not. How does a $200-500/month server compare? Lastly, is it possible that SL is just not competitive anymore, but another provider is? I have gotten out of that gig a few years ago so I honestly don’t know, but is it possible that Hetzner or someone similar is now the leader in leased hardware?
  - user5994461 9y ago
    CPUs are in the same ballpark. They are all recent generation Intel Xeon with a lot of cores. The providers each have a few different builds, you'd need to provision the machine and check the model number if you want the details. SoftLayer is a disaster on lower tier servers. You only go to them for higher tiers. The market is very competitive and moving fast. Both Google Cloud and AWS have been rolling out high memory hardware recently at a reasonable rate. Hetzner is amateur tier. It's cheap second hands servers with no ECC. It's not comparable to enterprise infrastructure.
- guitarbill 9y ago
  I think you misunderstand, I agree Softlayer is terrible - I was merely pointing out that when their pricing wasn't bad, their tooling has always been pants. (But then they were bought by a company who's "cloud strategy" is to put the word "cloud" in as many DB2 and mainframe contracts as possible.)
geofft 9y ago
> Turns out it's hard running with minimal downtime, or engineering hardware + software to be fault-tolerant. It's hard to do that with cloud too. Your instances can go down at any time. What you're trading off is a small number of people on-site at the data center (and it can in fact be small!) plus some slightly-old-school sysadminning versus new-school cloud-native development. Maybe the latter is easier to hire for (although I doubt that) or your current people find it more fun. But it's not like physical hardware dies all the time, or that you're immune from seeing the effects of physical hardware dying just because you're on the cloud. You might save on hiring one person to replace disks when they fail and one person to write some PXE boot automation, but you'll need more than two people to run a Kubernetes at the same scale of compute capacity than those two people could have run for you.
tedchs 9y ago
> if you have a specialised workload (CPU heavy, storage heavy, etc) there's definitely cost savings at scale for DIY I wasn't sure what your use "heavy" means here -- is it "a lot of" or "disproportionate"? Years ago there was much less flexibility with IaaS machine shapes, but I was super impressed when Google launched "custom machine types". There's a little slider to scale up/down your RAM/CPU independently, and of course storage is already independent. In fairness, there is some correlation between CPU allocation and storage IOPS, but that's inherent to scheduling a portion of the host machine reasonably. https://cloud.google.com/compute/docs/instances/creating-instance-with-custom-machine-type https://cloud.google.com/compute/docs/instances/creating-ins...
- guitarbill 9y ago
  Yeah, if you're using loads of CPU, but not all the RAM or block storage. This usually happens if your problem isn't really parallelisable. Then scaling out isn't really something you can do easily or quickly, so the cloud loses it's appeal a bit. In those cases, it might make sense to go DIY/in-house.

IgorPartola 9y ago

First I don’t mean SoftLayer’s cloud. I mean their physical boxes. A dual processor Xeon that is all your own is a lot. Second, it depends on your expertise. And you don’t need scale. I ran a successfully bit of infrastructure on SL with seven servers that was quite a bit cheaper than an equivalent AWS setup. I was pretty much solely responsible for the infrastructure and still my responsibilities included more than 80% coding and later management. Given my salary at the time, it was quite cost effective.

imbkr 9y ago
was the comparison based on on-demand instances or reserved instances? we reserve almost all of our instances within our company for 3 years and also get an extra discount on top of it. based on my calculations, i've seen AWS cheapest out of all. would like to know if i'm missing anything
- IgorPartola 9y ago
  This was a few years ago so prices have changed on both sides. What I advocate is doing exactly what you did: do a comparison with actual numbers and performance stats instead of hand waving that the cloud is always best.
  - mgkimsal 9y ago
    another factor that gets overlooked some is on-hand skills and hireable skills. if you have experience (and/or your team does) with dedicated, that should probably be for a non-trivial in decision making. likewise if you have more aws/cloud experience (or have those skills available on staff), there's benefits to that. cloud skills don't magically happen - someone with minimal AWS skills can provide you with a setup that is more expensive to run, and possibly more insecure than a locked down dedicated box.
    - IgorPartola 9y ago
      Exactly. If you have expertise to run your own servers, and you don't have a spiky workload, maybe it's worth it. If you have cloud expertise, that may be the winner.

user5994461 9y ago

Well, you and the poster are about to be disappointed. I did the comparison recently for 512GB memory servers and Google Cloud is now the same price as SoftLayer, while AWS is a bit more. https://thehftguy.com/2018/01/15/the-inevitable-demise-of-ibm-softlayer-by-aws/ https://thehftguy.com/2018/01/15/the-inevitable-demise-of-ib... If you are willing to pay a lot of money upfront, which you are since you're talking about building your own datacenter, AWS and Google will both give you huge discount and be significantly cheaper than SoftLayer.

IgorPartola 9y ago
I don’t see any performance details in your write up. Is the SL server actually comparable to the GC one? I don’t know how to equate vCPUs to real world performance. Memory is easy to compare. But how does it stack up CPU-wise. Another question is whether lower tier servers compare favorably or not. How does a $200-500/month server compare? Lastly, is it possible that SL is just not competitive anymore, but another provider is? I have gotten out of that gig a few years ago so I honestly don’t know, but is it possible that Hetzner or someone similar is now the leader in leased hardware?
- user5994461 9y ago
  CPUs are in the same ballpark. They are all recent generation Intel Xeon with a lot of cores. The providers each have a few different builds, you'd need to provision the machine and check the model number if you want the details. SoftLayer is a disaster on lower tier servers. You only go to them for higher tiers. The market is very competitive and moving fast. Both Google Cloud and AWS have been rolling out high memory hardware recently at a reasonable rate. Hetzner is amateur tier. It's cheap second hands servers with no ECC. It's not comparable to enterprise infrastructure.
guitarbill 9y ago
I think you misunderstand, I agree Softlayer is terrible - I was merely pointing out that when their pricing wasn't bad, their tooling has always been pants. (But then they were bought by a company who's "cloud strategy" is to put the word "cloud" in as many DB2 and mainframe contracts as possible.)

geofft 9y ago

> Turns out it's hard running with minimal downtime, or engineering hardware + software to be fault-tolerant. It's hard to do that with cloud too. Your instances can go down at any time. What you're trading off is a small number of people on-site at the data center (and it can in fact be small!) plus some slightly-old-school sysadminning versus new-school cloud-native development. Maybe the latter is easier to hire for (although I doubt that) or your current people find it more fun. But it's not like physical hardware dies all the time, or that you're immune from seeing the effects of physical hardware dying just because you're on the cloud. You might save on hiring one person to replace disks when they fail and one person to write some PXE boot automation, but you'll need more than two people to run a Kubernetes at the same scale of compute capacity than those two people could have run for you.

tedchs 9y ago

> if you have a specialised workload (CPU heavy, storage heavy, etc) there's definitely cost savings at scale for DIY I wasn't sure what your use "heavy" means here -- is it "a lot of" or "disproportionate"? Years ago there was much less flexibility with IaaS machine shapes, but I was super impressed when Google launched "custom machine types". There's a little slider to scale up/down your RAM/CPU independently, and of course storage is already independent. In fairness, there is some correlation between CPU allocation and storage IOPS, but that's inherent to scheduling a portion of the host machine reasonably. https://cloud.google.com/compute/docs/instances/creating-instance-with-custom-machine-type https://cloud.google.com/compute/docs/instances/creating-ins...

guitarbill 9y ago
Yeah, if you're using loads of CPU, but not all the RAM or block storage. This usually happens if your problem isn't really parallelisable. Then scaling out isn't really something you can do easily or quickly, so the cloud loses it's appeal a bit. In those cases, it might make sense to go DIY/in-house.