我试图基于以下理由将云计算（在 EC2 上）与传统托管进行比较，以确定这些功能与更传统的托管策略相比是否在云计算领域具有独特的优势：
- 实时监控
- 服务器虚拟化
- 部署自动化
- 高性能计算
- 按需弹性
据我所知，（1）监控在这两个方面都同样容易； (2) 服务器虚拟化也存在于这两个领域，这要归功于服务器场，它允许传统主机随意增强资源——当然，这同样适用于云； (3) 部署可以在这两个领域同样实现自动化，因为相同的工具通常可以应用于这两个领域； （4）在高性能计算领域，理论上也许你会从云中获得额外的提升，但我不太确定——无论是否是云，你都必须为这种提升付费； (5) 弹性是我认为迁移到云的唯一真正好处 - 只需轻轻一按开关即可增加资源。
所以我的问题是，这真的是这个列表中云计算比传统托管提供真正优势的唯一优势吗？还是我的分析有缺陷？
I am trying to compare cloud computing (on EC2) against traditional hosting on the following grounds to determine whether any of these features present unique benefits in the world of cloud computing versus more traditional hosting strategies:
- Real-time monitoring
- Server virtualization
- Deployment automation
- High performance computing
- On-demand elasticity
As far as I can see, (1) monitoring is just as easy in both areas; (2) server virtualization is also present in both areas thanks to server farms which allow traditional hosts to beef up resources at will - and of course the same applies in the cloud; (3) deployment can be equally automated in both areas since the same tools often can be applied to both; (4) in the area of high performance computing maybe you get an extra boost from the cloud theoretically but I'm not so sure - you have to pay for that boost whether it's the cloud or not; (5) elasticity is the only real benefit that i can see of moving to the cloud - resources can be pumped up at the flick of a switch.
So my question is, is this really the only benefit of cloud computing from this list that offers a real benefit over traditional hosting or is my analysis flawed?
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这里的主要区别在于成本模型。 虽然您确实可以通过云计算和传统托管从您的列表中获得所有相同的好处，但您需要预先为传统托管付费。 你必须购买和维护自己的服务器，而云计算允许你支付可变成本。
这就是云计算对初创公司如此有吸引力的原因。
The main difference here is the cost model. While it's true you can gain all of the same benefits from your list with both Cloud Computing and traditional hosting, you pay up front for traditional hosting. You have to buy and maintain your own servers, while cloud computing allows you to pay a variable cost.
This is the reason cloud computing is so attractive for startup companies.
您不仅具有弹性，而且至少在理论上，您拥有比任何静态托管解决方案更多的可用资源总量。
此外，弹性的副作用是用电量减少，这可能是也可能不是您的一个因素。
Not only do you have elasticity, but you have, in theory at least, a greater total amount of resources available than you could have with any static hosting solution.
Also, a side effect of elasticity is decreased electricity usage, which may or may not be a factor for you.
我工作的公司正准备从自托管迁移到云提供商 (EC2)。 我非常期待的一件事是不必担心管理硬件。 我不需要担心订购零件的交货时间。 不再需要现有备件来应对意外的硬件故障。 我不需要担心 UPS 或任何电源。 我们的规模还不够大，不足以让冷却成为一个问题……但现在我们也不必担心这个问题了。
The company I work for is getting ready to move from self-hosting to a cloud provider (EC2). One thing I am greatly looking forward to is not having to worry about managing hardware. I don't need to worry about lead time for ordering parts. The need to have spare parts on-hand to cover unexpected hardware failures is gone. I don't need to worry about UPS or any power. We aren't big enough for cooling to be a concern... but now we never will have to worry about that either.
根据您自己的数据中心成本，云计算平台可能便宜得多，因为您不需要任何人来管理物理设备。 云服务可以提供大量计算资源，其成本可能比您购买机器并自己连接的成本低。
Depending on your own datacenter costs, a cloud computing platform can be much cheaper, as you don't need anybody to manage physical devices. Cloud services can provide bulk computing resources at likely a lower cost than you can provide if you bought the machines and hooked them up yourself.
假设您的“传统托管”涉及单个服务器，那么云/网格环境中的高性能计算会带来非常实际的好处。 具体来说，性能几乎是无限的，因为您可以有 n 个核心同时工作，而使用单个服务器时，您会受到最大服务器容量的限制。
更清楚地说，如果世界上最强大的计算机是具有 20 TB RAM 的 1000 核系统，那么这就是托管服务器上可以拥有的最大功率。 然而，由 100 台这样的机器组成的云可以在几乎相同的时间内完成 100 倍的工作。
此外，将工作分配到多台较小的机器上通常比使用一个能够完成相同工作的强大系统更便宜（财务上）。
如果您想谈论灾难恢复......云可以在地理上分布，这意味着如果龙卷风将您的数据中心从地面上撕下来，将服务器撕成金属和塑料的小碎片，并将它们嵌入电话中极点...您的性能略有下降，因为您的其他 99 台服务器仍在运行。
Assuming your "traditional hosting" involves a single server, there is a very real benefit to high-performance computing in cloud / grid environments. Specifically, virtually unlimited performance, since you can have n cores working at the same time, whereas with a single server, you are limited by the maximum server capacity.
To put it more clearly, if the most powerful computer in the world is a 1000 - core system with 20 terabytes of RAM, then that's the most power you could have on a hosted server. However, a cloud consisting of 100 of these machines could do 100x the work in almost the same amount of time.
Additionally, it's generally less expensive (financially) to distribute work across multiple smaller machines than it is to get one powerful system capable of doing the same work.
And if you'd like to talk about disaster recovery....clouds can be geographically distributed, meaning if a tornado rips your data center out of the ground, plucks the server into little shards of metal and plastic, and embeds them in telephone poles...you experience a slight dip in your performance because your other 99 servers are still operating.
计算、存储和网络容量的弹性只是一个特性。 然而，它带来了大量的 Cloud Bursting小型 SaaS 公司可以轻松、廉价地处理可能导致昂贵的托管解决方案瘫痪的流量和使用高峰。
Elasticity of the computing, storage and network capacities is just a feature. Yet, it brings a huge number of economical benefits for the companies. For example, by implementing a Cloud Bursting scenario a small SaaS company could easily and cheaply handle traffic and usage spikes that might take an expensive hosted solution down.
只有当你有一个可以横向解决的问题时，弹性才有用。 例如，为静态站点提供服务的 Web 服务器，如果负载增加，请添加更多 Web 服务器来提供完全相同的内容。 另一方面，即使是一个简单的博客网站也会在这种情况下崩溃，因为输入一台服务器数据库的评论不会反映在其他计算机中。
可扩展的资源与可扩展的能力不同。 云计算不会解决应用程序的可扩展性问题。
视频托管网站就是一个很好的例子：使用 AWS 传输视频会导致令人失望的体验，因为 EC2 无法提供传输视频所需的 I/Ops。 使用更多的机器来解决问题并不能解决数据如何从磁盘到网络的问题。 （是的，我知道高 iops 实例的价格昂贵得离谱）
Elasticity is only useful if you have a problem that can be solved horizontally. For example a web server to serve a static site, if the load increases, add more web servers to server the exact same content. On the other hand, even a simple blog site breaks under that scenario as comments entered into one server's database are not reflected in the other machines.
The resources to scale is not the same thing as the ability to scale. Cloud computing will not solve scalability issues with your application.
A good example of this is a video hosting site: using AWS to deliver the videos results in a disappointing experience since the EC2 cannot deliver the I/Ops necessary to deliver video. Throwing more machines at the problem won't solve the issue with how data gets from disk to network. (Yes I'm aware of the ridiculously expensive high-iops instances)