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Economies of scale in the cloud have one thing going for them: massive reliability. As someone responsible for my company's data, I cannot make a sound argumen

Economies of scale in the cloud have one thing going for them: massive reliability. As someone responsible for my company's data, I cannot make a sound argument to convince management (or myself) to use anything but Amazon S3 (or Google or Microsoft) cloud. The data is simply too important to trust to a smaller entity. Maybe coin storage can boost Storj's reputation. And I certainly favor decentralization for Crypto.

capableweb 6y ago
So granted the durability and availability is better than centralized solutions, you'd go with the distributed/decentralized solution? If that's the case, I think you could argue that open source and distributed solutions are much easier to make more reliable than centralized solutions. With a centralized solution, you're stuck with trusting their reliability or implement some reusable API (or use some 3rd party's API that abstract that away, introducing more error surface) so you can also store the data in multiple places with the same API. Or, you can just use a open source decentralized solutions and run it locally geographically, hosted on dedicated servers and "in the cloud" (meaning other users who host it) with the same API without really caring about _where_ the files are, just _which_ files you need. And that's the beauty of content-addressable networks like many of these are. It doesn't really matter where the data is as long as you know what data you need. That makes it easier to provide reliability for yourself, not harder. Once you dig down in the details and compare them both carefully, I think you can make sound arguments both ways, it's not as black & white as you make it. Ultimately it depends on one's use case.
- SavantIdiot 6y ago
  I don't see how this addresses the reliability claim. There's a big difference between explaining that the data is stored in a Google cloud with certified 11-nines reliability, versus stored on a N number of machines in multiple clouds with unknown specs. How do I communicate the reliability of a distributed cloud that is essentially a collection of random servers? Is there a way that each of these server's reliability is accounted for by the high-level service?
  - capableweb 6y ago
    You'd say something like "This content is hosted by 100 providers, with each having individual average uptime of 99.9%"
    - SavantIdiot 6y ago
      I see. But how do I verify that 99.9%? Aren't the distributed services anonymous?
  - wmf 6y ago
    If you're willing to assume that each invididual server has some level of reliability (e.g. "one nine") and you assume failures are uncorrelated you can build a more reliable system using erasure coding and reason mathematically about the resulting reliability. http://www.suaybarslan.com/Reliability_Systems_14.pdf http://www.suaybarslan.com/Reliability_Systems_14.pdf

capableweb 6y ago

So granted the durability and availability is better than centralized solutions, you'd go with the distributed/decentralized solution? If that's the case, I think you could argue that open source and distributed solutions are much easier to make more reliable than centralized solutions. With a centralized solution, you're stuck with trusting their reliability or implement some reusable API (or use some 3rd party's API that abstract that away, introducing more error surface) so you can also store the data in multiple places with the same API. Or, you can just use a open source decentralized solutions and run it locally geographically, hosted on dedicated servers and "in the cloud" (meaning other users who host it) with the same API without really caring about _where_ the files are, just _which_ files you need. And that's the beauty of content-addressable networks like many of these are. It doesn't really matter where the data is as long as you know what data you need. That makes it easier to provide reliability for yourself, not harder. Once you dig down in the details and compare them both carefully, I think you can make sound arguments both ways, it's not as black & white as you make it. Ultimately it depends on one's use case.

SavantIdiot 6y ago
I don't see how this addresses the reliability claim. There's a big difference between explaining that the data is stored in a Google cloud with certified 11-nines reliability, versus stored on a N number of machines in multiple clouds with unknown specs. How do I communicate the reliability of a distributed cloud that is essentially a collection of random servers? Is there a way that each of these server's reliability is accounted for by the high-level service?
- capableweb 6y ago
  You'd say something like "This content is hosted by 100 providers, with each having individual average uptime of 99.9%"
  - SavantIdiot 6y ago
    I see. But how do I verify that 99.9%? Aren't the distributed services anonymous?
- wmf 6y ago
  If you're willing to assume that each invididual server has some level of reliability (e.g. "one nine") and you assume failures are uncorrelated you can build a more reliable system using erasure coding and reason mathematically about the resulting reliability. http://www.suaybarslan.com/Reliability_Systems_14.pdf http://www.suaybarslan.com/Reliability_Systems_14.pdf