对于今天的组织来说，自动化评估、跟踪和预测云基础设施的运行成本是必要的。云供应商精明的定价模型，以及基于定价参数的费用激增，再加上现代架构的动态本质，常常导致让人吃惊的运行成本。例如，无服务架构 基于API访问量的费用，事件流方案中基于流量的费用，以及数据处理集群中基于运行任务数量的费用，它们都具有动态的本质，会随着架构演进而产生改变。当我们的团队在云平台上管理基础设施时， 将运行成本实现为架构适应度函数 是他们的早期活动之一。这意味着我们的团队可以观察运行服务的费用，并同交付的价值进行对比；当看到与期望或可接受的结果之间存在偏差时，他们就会探讨架构是否应该继续演进了。对运行成本的观察和计算需要被实现为自动化的函数。
We still see teams who aren't tracking the cost of running their applications as closely as they should as their software architecture or usage evolves. This is particularly true when they're using serverless, which developers assume will provide lower costs since you're not paying for unused server cycles. However, the major cloud providers are pretty savvy at setting their pricing models, and heavily used serverless functions, although very useful for rapid iteration, can get expensive quickly when compared with dedicated cloud (or on-premise) servers. We advise teams to frame a system's run cost as architecture fitness function, which means: track the cost of running your services against the value delivered; when you see deviations from what was expected or acceptable, have a discussion about whether it's time to evolve your architecture.