4 ms·

That's just not true. - Network ist worse than the competition for sure, just benchmark it and you will see it. And if you benchmark it over a certain time per

by nik736 9y ago

That's just not true. - Network ist worse than the competition for sure, just benchmark it and you will see it. And if you benchmark it over a certain time period you will see that it's very unpredictable. If you only need 5mbit all the time, sure it's the same as anyone elses. The good thing is that you don't pay for traffic, but I would rather have a stable system/network. Also, the AMS network has a bad carrier mix which is why they route a lot of the traffic through Paris, which adds latency because their network is bad. - The storage system is a joke. Max 150 GB per volume, it's very slow depending where your VM lands. If you only look at the price, sure it's quite good, but that doesn't make it production ready. - How is an additional automated backup system vendor lock in? It's quite nice to restore backups with a click, how is that a bad thing? You can still do your own backups, but at least the option would be great. - No, the ARM CPUs don't statisfy 99% of projects. Because most web projects need single thread performance and that's exactly where ARM CPUs are garbage.

kureikain 9y ago
I can confirm this. That's my experience as well. I run an uptime monitoring tools[1] and the node run on Scaleway is the most unreliable one due to network issues. It happens randomly once in 2 weeks when the instance experience 3-5minutes of disconnecting from internet completely. They are also very slow when you stopping instance. Mine take hours to just stopping instance. --- [1] noty.im
eropple 9y ago
> most web projects need single thread performance What makes you say that? Near as I can tell, most web projects need I/O more than anything else. You're waiting on one end or another of a socket, a disk device, or a memory bus way more than you're doing anything chewy. (I agree with you that Scaleway isn't serious, however.)
- nik736 9y ago
  I/O is important, I agree. RAM is important as well, and both are probably more important than the CPU. But as soon as the CPU comes into play a proper single thread performance is in most cases better than multiple slow threads. And if you have the choice, why would you choose ARM cores if you can have the better single thread performance?
  - sqeaky 9y ago
    You are generalizing much and citing no sources. You claim these are unsuitable in every case. Please provide concrete examples, links to benchmarks and other reasons to believe what you say. I ask because you appear very biased and you experience contradicts mine, you could be right though. If you are right I would want to know, because I might make mistakes if you don't correct me in an objective way.
    - remline 9y ago
      I think your instincts are correct, I use scaleway for clusters of mediocrity feeding fat clients and to feed cloudflare for vanity sites.. Needing the fastest cpu, great networks and accepting backup lock-in are examples of laziness in design. Sourcing commodity materials and already having a few nodes in every role is my preferred bet. Being able to upgrade the node performance by 10 times if scaling plans fail wont hurt either..
      - sqeaky 9y ago
        I agree with you , I do disagree with one tiny part. I agree with your entirely on any sort of lock-in, lock-in is bad and constrains future options. Known cost up front for unknown cost in the future should generally be seen as a business risk. The tiny place where I disagree is that some tasks might take unbounded CPU/GPU time and network bandwidth. Your task clearly does not and I agree your workload looks like a common workload. When working for the Air Force Weather Wing, it seemed clear that our decision to use the super computers we used was a budgetary decision and that is what bounded the size of the data we fed into our systems. Because we generated forecasts we had tight time constraints to meet, a 72 hour forecast that takes 100 hours to make is useless. Weather modeling and forecasting is still advancing and even the latest models are not stable simulations (small fluctuations in inputs can cause large fluctuations in output) and this makes the most nuanced data possible desirable. While most commercial systems used 25km polygons covering the earth, ours used 17km polygons when I left. This meant that we had more precise sims and could accurately model further in the future, perhaps by several days. Even faster CPUs and networking might lead to a drop to 8-11km polygons allowing even better predictions. Ideally the meteorologists want to skip the rounding to regional polygons and use the parcels or air model that local forecasters use for the entire world. Presuming Moore's law holds up and weather modeling is amenable to newer GPUs I do not see weather modeling backing away from needing the fastest hardware money can buy in the foreseeable future.

by nik736 9y ago

kureikain 9y ago

I can confirm this. That's my experience as well. I run an uptime monitoring tools[1] and the node run on Scaleway is the most unreliable one due to network issues. It happens randomly once in 2 weeks when the instance experience 3-5minutes of disconnecting from internet completely. They are also very slow when you stopping instance. Mine take hours to just stopping instance. --- [1] noty.im

eropple 9y ago

> most web projects need single thread performance What makes you say that? Near as I can tell, most web projects need I/O more than anything else. You're waiting on one end or another of a socket, a disk device, or a memory bus way more than you're doing anything chewy. (I agree with you that Scaleway isn't serious, however.)

nik736 9y ago
I/O is important, I agree. RAM is important as well, and both are probably more important than the CPU. But as soon as the CPU comes into play a proper single thread performance is in most cases better than multiple slow threads. And if you have the choice, why would you choose ARM cores if you can have the better single thread performance?
- sqeaky 9y ago
  You are generalizing much and citing no sources. You claim these are unsuitable in every case. Please provide concrete examples, links to benchmarks and other reasons to believe what you say. I ask because you appear very biased and you experience contradicts mine, you could be right though. If you are right I would want to know, because I might make mistakes if you don't correct me in an objective way.
  - remline 9y ago
    I think your instincts are correct, I use scaleway for clusters of mediocrity feeding fat clients and to feed cloudflare for vanity sites.. Needing the fastest cpu, great networks and accepting backup lock-in are examples of laziness in design. Sourcing commodity materials and already having a few nodes in every role is my preferred bet. Being able to upgrade the node performance by 10 times if scaling plans fail wont hurt either..
    - sqeaky 9y ago
      I agree with you , I do disagree with one tiny part. I agree with your entirely on any sort of lock-in, lock-in is bad and constrains future options. Known cost up front for unknown cost in the future should generally be seen as a business risk. The tiny place where I disagree is that some tasks might take unbounded CPU/GPU time and network bandwidth. Your task clearly does not and I agree your workload looks like a common workload. When working for the Air Force Weather Wing, it seemed clear that our decision to use the super computers we used was a budgetary decision and that is what bounded the size of the data we fed into our systems. Because we generated forecasts we had tight time constraints to meet, a 72 hour forecast that takes 100 hours to make is useless. Weather modeling and forecasting is still advancing and even the latest models are not stable simulations (small fluctuations in inputs can cause large fluctuations in output) and this makes the most nuanced data possible desirable. While most commercial systems used 25km polygons covering the earth, ours used 17km polygons when I left. This meant that we had more precise sims and could accurately model further in the future, perhaps by several days. Even faster CPUs and networking might lead to a drop to 8-11km polygons allowing even better predictions. Ideally the meteorologists want to skip the rounding to regional polygons and use the parcels or air model that local forecasters use for the entire world. Presuming Moore's law holds up and weather modeling is amenable to newer GPUs I do not see weather modeling backing away from needing the fastest hardware money can buy in the foreseeable future.