现实世界的Windows Azure的成本计算的例子，有人吗？ [英] Real World Windows Azure Costing Examples, Anyone?

问题描述

OK，我们在2010年12月，天蓝色到现在已经出一个像样的时期。当然，我已经遇到无聊的文章predicting可能是什么费用与天青（http://robburke.net/2010/01/28/windows-azures-pricing-model-discourages-small-scale-apps运行/）。但我真的很想知道是谁跑了现实世界的Azure直播应用？什么了您的应用程序看起来像 - ？哪些服务，有多少角色，哪些存储，有多少用户等，最终也花了多少钱买你

OK, we're in Dec 2010, azure has been out now for a decent period. Sure I've come across silly articles predicting what it might costs to run with Azure (http://robburke.net/2010/01/28/windows-azures-pricing-model-discourages-small-scale-apps/). But what I'd really like to know is who has run Real World Live Azure Apps? What did your applications looks like - which services, how many roles, what storage, how many users etc. and ultimately how much did it cost you?

现在，想弄清楚是否投资6个月开发的蔚蓝程序是面色凝重，因为它是这样一个黑盒子predicting是什么力量成本运行一个应用程序。

Right now, trying to figure out whether to invest 6 months in developing an azure app is looking grim because it's such a black box predicting what is might costs to run an application.

我很惊讶，我找不到的例子一个良好的世界组，这将有助于开发人员有更多的可视性，帮助他们购买到平台...

I'm surprised I couldn't find a good real world set of examples that would help developers have more visibility into helping them buy into the platform...

推荐答案

我认为这是一个很好的问题，但任何人都将很难给你一个答案，因为结果总是会有所不同，在该领域的人回答会太具体到他们的特殊情况。

I think its a fair question to ask, but anyone will struggle to give you an answer, as your results will always vary and replies from people in the field would be too specific to their particular situation.

我有，我们在Azure上运行一个真实世界的解决方案。事实上，如果你决定去与天青，可以考虑用它来优化您的Azure的计算实例分配：的http：// www.paraleap.com ：）

I have a real-world solution that we run in Azure. In fact, if you do decide to go with Azure, consider using it to optimize your compute-instance allocation for Azure: http://www.paraleap.com :)

我只能告诉你，你想要的预算，由于不同时间至少20％的额外计算时间，当你需要部署/重新部署/并重新部署的环境中进入临时区域（以小时为增量费用另计）找出这是别的东西在云中时，它在开发布料工作不起作用。这是你的应用程序的初始不稳定时​​尤其如此。如果你有一个大的QA团队刘海到底出你​​的Azure-QA环境中，否则你会以客户为beta测试，他们正在测试你的Azure的正式版环境没关系。您将需要重新部署可为他们安静频繁。
此外，正如我前面提到的，计划调整您的实例计算需求 - 希望自动或按计划。如果你打算写自己的监控要做到这一点，添加/串/开发成本，存储成本，只是为交易成本。这外包仍将花费一点点，作为性能指标将需要至少保存一次，至少装回一次。这将节省您在计算实例的成本很容易高达50-80％，这取决于你的需求如何变量。

I can tell you that you want to budget at least 20% extra computing hours due to various times when you need to deploy/redeploy/and re-deploy again an environment into staging area (which costs extra in hourly increments) only to find out that's something else in the cloud does not work when it worked in the dev fabric. This is especially true in the initial unstable time of your application. It does not matter if you have a large QA team that bangs the heck out of your Azure-QA environment or you're going to customers for beta-testing and they're testing your Azure-Prod environment. You will need to be redeploying for them quiet often. Furthermore, as I already mentioned, plan to adjust your instance counts to demand - hopefully automatically or on a schedule. If you're going to write your own monitoring to do this, add a /bunch/ to development costs, storage costs, and transaction costs just for that. Outsourcing this will still cost a little bit, as performance metrics will need to be at least saved once and at least loaded back once. This will save you in the compute-instance costs easily as much as 50-80%, depending on how variable your demand is.

存储成本 - 这应该很容易，如果你知道你的使用模式和目标模式估计......问题是，如果你已经与前关系型数据库工作，现在将使用表存储，计划将有3-4倍，你会想到你的关系数据库有大小。随着表存储你非规范化很多更。 3-4倍甚至太小事半功倍的 - 你的结果可能会有所不同。

Storage costs - those should be easy to estimate if you know your usage patterns and target schema... Problem is, if you've worked with Relational databases before and now will be using table Storage, plan to have 3-4 times the size that you would have thought your relational database to have. With table-storage you get to denormalize ALOT more. 3-4x maybe even too small of a multiplier - your results may vary.

交易成本。我找到了我的估计，有了这些，我已经进一步降。从关系世界的到来，我并不完全$ ppared因为我需要做非规范化的水平p $。非规范化，不仅导致了更高的存储成本，而且也更加呼叫（很多更多的呼叫）到存储 - 导致更高的交易计数

Transaction costs. I'm finding out that with these, I've been further-off in my estimates. Coming from relational world, I wasn't totally prepared for the level of denormalization I needed to do. Denormalization not only leads to higher storage costs, but also to more calls (alot more calls) to the storage - resulting in higher transaction count.

不幸的是，我的应用程序的性质，我不能很好地用交易模式。如果您可以使用交易，其中一堆东西存储在一个PartitionKey一个表内，并承诺一个交易 - 那么成本要少得多。
所以，无论你认为你的交易成本将是 - 乘以10左右上悲观的一面。

Unfortunately, my nature of the app, I can't very well use transactional model. If you can use transactions, where a bunch of stuff is stored in one PartitionKey within one table and committed with one transaction - then the costs are much less. So, whatever you think your transaction costs will be - multiply that by 10 or so to be on the pessimistic side.

我发现，转移成本是最简单的计划，可能是因为这些都是接口的一部分，并且更好的定义前期。你的情况可能会有所不同。

I found that transfer costs were easiest to plan for, probably because those are part of the interfaces and are much better defined upfront. Your mileage may vary.

最后，诊断数据 - 你想节省一些跟踪/性能计数器/等。信息。不要忘了应对措施。这有点不规范，可以采取足够的空间。

And lastly, diagnostic data - you will want to save some trace/performance counter/etc. information. Don't forget to plan for it. It's somewhat denormalized and can take plenty of space.

SQL Azure是很大的，因为它不通过交易成本，并且如果相同的数据中心内没有传送费用收取 - 而是由空间和存储数据的成本是非常有限的。所以，我用它经常查询的，但小的数据项。

SQL Azure is great as it does not charge by transaction cost and no transfer costs if inside the same data center - but is very limited by space and cost to store the data. So, I use it for frequently queried for, but small data items.

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