如何估算GAE的托管服务成本？ [英] How to estimate hosting services cost on GAE?
问题描述
我正在构建一个计划部署在 Google App Engine 上的系统。目前的定价描述如下：
我需要估算每个由webapp管理的客户端的成本。在我完成开发之前，成本将不会很准确。 GAE使用如READs和WRITE这样的细粒度价格计算，估算每个用户的运营成本变得非常艰巨。
我有一个敏捷开发。这个过程让我更难以确定我的成本。我一直在利用我的用户故事创建每个用户故事的成本基准。然后，我粗略估计用户将如何执行每个故事工作流以最终计算出一个简单的估计值。
据我所知，对于初创公司来说，计算Datastore API的估计过于复杂项目。其他成本更容易掌握。不幸的是，我需要给我的经理一个近似的成本！
有没有人接受过这样的任务？任何指针都会很棒，包括工具，示例或其他相关信息。
谢谢。
是的，可以为应用引擎应用进行成本估算分析。根据我的经验，我在分析过程中遇到的三大成本领域是实例小时成本，数据存储读/写成本以及数据存储存储的数据成本。
当然，YMMV基于您正在开发的应用类型。如果它是一个强大的OLTP应用程序，可以处理简单但频繁的CRUD到您的数据记录，则大部分成本将用于数据存储读/写操作，因此我建议您开始对此资源进行估算。
对于数据存储读/写来说，写入的成本通常比读取数据的成本昂贵得多。这是因为写入成本不仅考虑编写实体的成本，还要编写与实体相关的所有索引。我建议您阅读Google撰写的关于数据存储编写生活的文章 ，尤其是关于Apply阶段的部分，以了解如何根据您的数据模型计算每个实体的写入次数。
要估计您将要执行的实例小时数需要，最简单的方法（但并非总是可行）将部署一个简单的应用程序来测试某个特定请求需要多长时间。如果这种方法不可取，那么您也可以根据 Google App Engine系统状态页面（例如，为特定大小的实体写入数据存储的延迟是多少）以获得（处理）请求需要多长时间的（非常）粗略的图片。
在我看来，成本的第三大领域是数据存储的数据存储成本。当然，这会根据您的数据模型而有所不同，但是您所做的任何估计也需要考虑实体索引将采用的存储空间。快速浏览数据存储统计页面，我认为这些索引可以将存储大小增加40％到400％，具体取决于您对特定实体有多少索引。
I'm building a system which I plan to deploy on Google App Engine. Current pricing is described here:
Google App Engine - Pricing and Features
I need an estimate of cost per client managed by the webapp. The cost won't be very accurate until I have completed the development. GAE uses such fine grained price calculation such as READs and WRITEs that it becomes a very daunting task to estimate operation cost per user.
I have an agile dev. process which leaves me even more clueless in determining my cost. I've been exploiting my users stories to create a cost baseline per user story. Then I roughly estimate how will the user execute each story workflow to finally compute a simplistic estimation.
As I see it, computing estimates for Datastore API is overly complex for a startup project. The other costs are a bit easier to grasp. Unfortunately, I need to give an approximate cost to my manager!
Has anyone undergone such a task? Any pointers would be great, regarding tools, examples, or any other related information.
Thank you.
Yes, it is possible to do cost estimate analysis for app engine applications. Based on my experience, the three major areas of cost that I encountered while doing my analysis are the instance hour cost, the datastore read/write cost, and the datastore stored data cost.
YMMV based on the type of app that you are developing, of course. If it is an intense OLTP application that handle simple-but-frequent CRUD to your data records, most of the cost would be on the datastore read/write operations, so I would suggest to start your estimate on this resource.
For datastore read/write, the cost for writing is generally much more expensive than the cost for reading the data. This is because write cost take into account not only the cost to write the entity, but also to write all the indexes associated with the entity. I would suggest you to read an article by Google about the life of a datastore write, especially the part about Apply Phase, to understand how to calculate the number of write per entity based on your data model.
To do an estimate of instance hours that you would need, the simplest approach (but not always feasible) would be to deploy a simple app to test how long would a particular request took. If this approach is undesirable, you might also base your estimate on the Google App Engine System Status page (e.g. what would be the latency for a datastore write for a particularly sized entity) to get a (very) rough picture on how long would it take to process your request.
The third major area of cost, in my opinion, is the datastore stored data cost. This would vary based on your data model, of course, but any estimate you made need to also take into account the storage that would be taken by the entity indexes. Taking a quick glance on the datastore statistic page, I think the indexes could increase the storage size between 40% to 400%, depending on how many index you have for the particular entity.
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