Microservices 微服务

Componentization via Services
通过服务实现组件化

For as long as we've been involved in the software industry, there's been a desire to build systems by plugging together components, much in the way we see things are made in the physical world. During the last couple of decades we've seen considerable progress with large compendiums of common libraries that are part of most language platforms.
自从我们涉足软件行业以来，人们就一直希望通过将组件插入在一起来构建系统，就像我们看到的东西在物理世界中制造的方式一样。在过去的几十年里，我们看到了在大多数语言平台中常见的大型库纲要方面取得了相当大的进展。

When talking about components we run into the difficult definition of what makes a component. Our definition is that a component is a unit of software that is independently replaceable and upgradeable.
在谈论组件时，我们遇到了组件构成的困难定义。我们的定义是，组件是可独立更换和可升级的软件单元。

Microservice architectures will use libraries, but their primary way of componentizing their own software is by breaking down into services. We define libraries as components that are linked into a program and called using in-memory function calls, while services are out-of-process components who communicate with a mechanism such as a web service request, or remote procedure call. (This is a different concept to that of a service object in many OO programs [3].)
微服务架构将使用库，但它们将自己的软件组件化的主要方式是分解为服务。我们将库定义为链接到程序并使用内存中函数调用调用的组件，而服务是与 Web 服务请求或远程过程调用等机制进行通信的进程外组件。（这与许多 OO 程序 [3] 中的服务对象概念不同。

One main reason for using services as components (rather than libraries) is that services are independently deployable. If you have an application [4] that consists of a multiple libraries in a single process, a change to any single component results in having to redeploy the entire application. But if that application is decomposed into multiple services, you can expect many single service changes to only require that service to be redeployed. That's not an absolute, some changes will change service interfaces resulting in some coordination, but the aim of a good microservice architecture is to minimize these through cohesive service boundaries and evolution mechanisms in the service contracts.
使用服务作为组件（而不是库）的一个主要原因是服务是可独立部署的。如果应用程序 [4] 在单个进程中由多个库组成，则对任何单个组件的更改都会导致必须重新部署整个应用程序。但是，如果将该应用程序分解为多个服务，则可以预期许多单个服务更改只需要重新部署该服务。这不是绝对的，一些变化会改变服务接口，导致一些协调，但一个好的微服务架构的目标是通过服务契约中的内聚服务边界和演进机制来最小化这些变化。

Another consequence of using services as components is a more explicit component interface. Most languages do not have a good mechanism for defining an explicit Published Interface. Often it's only documentation and discipline that prevents clients breaking a component's encapsulation, leading to overly-tight coupling between components. Services make it easier to avoid this by using explicit remote call mechanisms.
使用服务作为组件的另一个结果是更明确的组件接口。大多数语言没有很好的机制来定义显式发布接口。通常，只有文档和规则才能防止客户端破坏组件的封装，从而导致组件之间的耦合过于紧密。通过使用显式远程调用机制，服务可以更轻松地避免这种情况。

Using services like this does have downsides. Remote calls are more expensive than in-process calls, and thus remote APIs need to be coarser-grained, which is often more awkward to use. If you need to change the allocation of responsibilities between components, such movements of behavior are harder to do when you're crossing process boundaries.
使用这样的服务确实有缺点。远程调用比进程内调用更昂贵，因此远程 API 需要更粗粒度，这通常使用起来更笨拙。如果您需要更改组件之间的责任分配，那么当您跨越流程边界时，这种行为移动就更难做到。

At a first approximation, we can observe that services map to runtime processes, but that is only a first approximation. A service may consist of multiple processes that will always be developed and deployed together, such as an application process and a database that's only used by that service.
在第一次近似时，我们可以观察到服务映射到运行时进程，但这只是第一次近似。服务可以由多个进程组成，这些进程将始终一起开发和部署，例如应用程序进程和仅由该服务使用的数据库。

Organized around Business Capabilities
围绕业务能力进行组织

When looking to split a large application into parts, often management focuses on the technology layer, leading to UI teams, server-side logic teams, and database teams. When teams are separated along these lines, even simple changes can lead to a cross-team project taking time and budgetary approval. A smart team will optimise around this and plump for the lesser of two evils - just force the logic into whichever application they have access to. Logic everywhere in other words. This is an example of Conway's Law in action.
在希望将大型应用程序拆分为多个部分时，管理层通常将重点放在技术层，从而导致 UI 团队、服务器端逻辑团队和数据库团队。当团队沿着这些思路分开时，即使是简单的更改也可能导致跨团队项目需要时间和预算批准。一个聪明的团队会围绕这一点进行优化，并为两害相权取其轻而生 - 只需将逻辑强制到他们可以访问的任何应用程序中即可。换句话说，逻辑无处不在。这是康威定律的一个例子。

Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization's communication structure.
任何设计系统（广义定义）的组织都会产生一个设计，其结构是组织通信结构的副本。

-- Melvin Conway, 1968
——梅尔文·康威，1968年

Figure 2: Conway's Law in action
图 2：康威定律的实际应用

The microservice approach to division is different, splitting up into services organized around business capability. Such services take a broad-stack implementation of software for that business area, including user-interface, persistant storage, and any external collaborations. Consequently the teams are cross-functional, including the full range of skills required for the development: user-experience, database, and project management.
微服务的划分方法则不同，它拆分为围绕业务能力组织的服务。此类服务采用该业务领域的软件的广泛堆栈实现，包括用户界面、持久存储和任何外部协作。因此，这些团队是跨职能的，包括开发所需的全方位技能：用户体验、数据库和项目管理。

Figure 3: Service boundaries reinforced by team boundaries
图 3：由团队边界强化的服务边界

One company organised in this way is www.comparethemarket.com. Cross functional teams are responsible for building and operating each product and each product is split out into a number of individual services communicating via a message bus.
以这种方式组织的一家公司是 www.comparethemarket.com。跨职能团队负责构建和运营每个产品，每个产品被拆分为多个单独的服务，通过消息总线进行通信。

Large monolithic applications can always be modularized around business capabilities too, although that's not the common case. Certainly we would urge a large team building a monolithic application to divide itself along business lines. The main issue we have seen here, is that they tend to be organised around too many contexts. If the monolith spans many of these modular boundaries it can be difficult for individual members of a team to fit them into their short-term memory. Additionally we see that the modular lines require a great deal of discipline to enforce. The necessarily more explicit separation required by service components makes it easier to keep the team boundaries clear.
大型单体式应用程序也可以围绕业务功能进行模块化，尽管这种情况并不常见。当然，我们会敦促一个构建单体应用程序的大型团队按照业务线进行划分。我们在这里看到的主要问题是，它们往往围绕着太多的上下文进行组织。如果单体跨越了许多这样的模块化边界，那么团队中的单个成员可能很难将它们放入他们的短期记忆中。此外，我们看到模块化生产线需要大量的纪律来执行。服务组件需要的必然更明确的分离使得保持团队边界清晰变得更加容易。

Products not Projects 产品而非项目

Most application development efforts that we see use a project model: where the aim is to deliver some piece of software which is then considered to be completed. On completion the software is handed over to a maintenance organization and the project team that built it is disbanded.
我们看到的大多数应用程序开发工作都使用项目模型：目标是交付一些软件，然后被认为已经完成。完成后，软件将移交给维护组织，构建它的项目团队将被解散。

Microservice proponents tend to avoid this model, preferring instead the notion that a team should own a product over its full lifetime. A common inspiration for this is Amazon's notion of "you build, you run it" where a development team takes full responsibility for the software in production. This brings developers into day-to-day contact with how their software behaves in production and increases contact with their users, as they have to take on at least some of the support burden.
微服务的支持者倾向于避免这种模式，而是更喜欢团队应该在整个生命周期内拥有产品的概念。一个常见的灵感来自亚马逊的“你构建，你运行它”的概念，即开发团队对生产中的软件负全部责任。这使开发人员能够日常接触他们的软件在生产中的行为方式，并增加与用户的联系，因为他们必须至少承担一些支持负担。

The product mentality, ties in with the linkage to business capabilities. Rather than looking at the software as a set of functionality to be completed, there is an on-going relationship where the question is how can software assist its users to enhance the business capability.
产品心态与业务能力的联系息息相关。与其将软件视为一组要完成的功能，不如将软件视为一组有待完成的功能，而是存在一种持续的关系，问题是软件如何帮助其用户增强业务能力。

There's no reason why this same approach can't be taken with monolithic applications, but the smaller granularity of services can make it easier to create the personal relationships between service developers and their users.
没有理由不能对单体应用程序采用相同的方法，但是较小的服务粒度可以使在服务开发人员与其用户之间创建个人关系变得更加容易。

Smart endpoints and dumb pipes
智能端点和哑管道

When building communication structures between different processes, we've seen many products and approaches that stress putting significant smarts into the communication mechanism itself. A good example of this is the Enterprise Service Bus (ESB), where ESB products often include sophisticated facilities for message routing, choreography, transformation, and applying business rules.
在构建不同流程之间的沟通结构时，我们看到许多产品和方法强调在沟通机制本身中投入大量智慧。一个很好的例子是企业服务总线 （ESB），其中 ESB 产品通常包含用于消息路由、编排、转换和应用业务规则的复杂工具。

The microservice community favours an alternative approach: smart endpoints and dumb pipes. Applications built from microservices aim to be as decoupled and as cohesive as possible - they own their own domain logic and act more as filters in the classical Unix sense - receiving a request, applying logic as appropriate and producing a response. These are choreographed using simple RESTish protocols rather than complex protocols such as WS-Choreography or BPEL or orchestration by a central tool.
微服务社区倾向于另一种方法：智能端点和哑管道。从微服务构建的应用程序旨在尽可能地解耦和有凝聚力 - 它们拥有自己的领域逻辑，并且更多地充当经典Unix意义上的过滤器 - 接收请求，适当地应用逻辑并产生响应。这些都是使用简单的 RESTish 协议编排的，而不是复杂的协议，如 WS-Choreography 或 BPEL，或者由中央工具编排。

The two protocols used most commonly are HTTP request-response with resource API's and lightweight messaging[7]. The best expression of the first is
最常用的两种协议是带有资源API的HTTP请求-响应和轻量级消息传递[7]。第一个最好的表达是

Be of the web, not behind the web
成为网络，而不是网络后面

-- Ian Robinson ——伊恩·罗宾逊

Microservice teams use the principles and protocols that the world wide web (and to a large extent, Unix) is built on. Often used resources can be cached with very little effort on the part of developers or operations folk.
微服务团队使用万维网（在很大程度上是 Unix）所基于的原则和协议。开发人员或运维人员只需很少的工作即可缓存经常使用的资源。

The second approach in common use is messaging over a lightweight message bus. The infrastructure chosen is typically dumb (dumb as in acts as a message router only) - simple implementations such as RabbitMQ or ZeroMQ don't do much more than provide a reliable asynchronous fabric - the smarts still live in the end points that are producing and consuming messages; in the services.
常用的第二种方法是通过轻量级消息总线进行消息传递。所选择的基础设施通常是哑的（哑的，就像只充当消息路由器一样）——像 RabbitMQ 或 ZeroMQ 这样的简单实现除了提供可靠的异步结构之外，别无他法——智能仍然存在于生成和使用消息的端点中;在服务中。

In a monolith, the components are executing in-process and communication between them is via either method invocation or function call. The biggest issue in changing a monolith into microservices lies in changing the communication pattern. A naive conversion from in-memory method calls to RPC leads to chatty communications which don't perform well. Instead you need to replace the fine-grained communication with a coarser -grained approach.
在单体架构中，组件在进程内执行，它们之间的通信通过方法调用或函数调用进行。将单体架构转变为微服务的最大问题在于改变通信模式。从内存中方法调用到 RPC 的幼稚转换会导致性能不佳的聊天通信。相反，您需要用更粗粒度的方法替换细粒度的通信。

Decentralized Governance
去中心化治理

One of the consequences of centralised governance is the tendency to standardise on single technology platforms. Experience shows that this approach is constricting - not every problem is a nail and not every solution a hammer. We prefer using the right tool for the job and while monolithic applications can take advantage of different languages to a certain extent, it isn't that common.
集中式治理的后果之一是倾向于在单一技术平台上进行标准化。经验表明，这种方法是有局限性的——不是每个问题都是钉子，也不是每个解决方案都是锤子。我们更喜欢使用正确的工具来完成这项工作，虽然单体应用程序可以在一定程度上利用不同的语言，但它并不常见。

Splitting the monolith's components out into services we have a choice when building each of them. You want to use Node.js to standup a simple reports page? Go for it. C++ for a particularly gnarly near-real-time component? Fine. You want to swap in a different flavour of database that better suits the read behaviour of one component? We have the technology to rebuild him.
将单体组件拆分为服务，我们在构建每个组件时都有一个选择。您想使用 Node.js 来建立一个简单的报告页面吗？去吧。C++ 用于一个特别粗糙的近乎实时的组件？好。您想换成一种更适合一个组件读取行为的不同风格的数据库吗？我们有技术来重建他。

Of course, just because you can do something, doesn't mean you should - but partitioning your system in this way means you have the option.
当然，仅仅因为你可以做某事，并不意味着你应该做 - 但以这种方式对系统进行分区意味着你有选择权。

Teams building microservices prefer a different approach to standards too. Rather than use a set of defined standards written down somewhere on paper they prefer the idea of producing useful tools that other developers can use to solve similar problems to the ones they are facing. These tools are usually harvested from implementations and shared with a wider group, sometimes, but not exclusively using an internal open source model. Now that git and github have become the de facto version control system of choice, open source practices are becoming more and more common in-house .
构建微服务的团队也更喜欢采用不同的标准方法。他们更喜欢使用写在纸上的一套定义的标准，而不是生产有用的工具，其他开发人员可以使用这些工具来解决与他们面临的类似问题。这些工具通常是从实现中收集的，有时与更广泛的群体共享，但并不完全使用内部开源模型。现在 git 和 github 已经成为事实上的版本控制系统，开源实践在内部变得越来越普遍。

Netflix is a good example of an organisation that follows this philosophy. Sharing useful and, above all, battle-tested code as libraries encourages other developers to solve similar problems in similar ways yet leaves the door open to picking a different approach if required. Shared libraries tend to be focused on common problems of data storage, inter-process communication and as we discuss further below, infrastructure automation.
Netflix 是遵循这一理念的组织的一个很好的例子。将有用的代码（尤其是经过实战测试的代码）共享为库，可以鼓励其他开发人员以类似的方式解决类似的问题，但如果需要，则可以选择不同的方法。共享库往往关注数据存储、进程间通信以及基础设施自动化等常见问题。

For the microservice community, overheads are particularly unattractive. That isn't to say that the community doesn't value service contracts. Quite the opposite, since there tend to be many more of them. It's just that they are looking at different ways of managing those contracts. Patterns like Tolerant Reader and Consumer-Driven Contracts are often applied to microservices. These aid service contracts in evolving independently. Executing consumer driven contracts as part of your build increases confidence and provides fast feedback on whether your services are functioning. Indeed we know of a team in Australia who drive the build of new services with consumer driven contracts. They use simple tools that allow them to define the contract for a service. This becomes part of the automated build before code for the new service is even written. The service is then built out only to the point where it satisfies the contract - an elegant approach to avoid the 'YAGNI'[8] dilemma when building new software. These techniques and the tooling growing up around them, limit the need for central contract management by decreasing the temporal coupling between services.
对于微服务社区来说，开销尤其没有吸引力。这并不是说社区不重视服务合同。恰恰相反，因为往往有更多的人。只是他们正在寻找管理这些合同的不同方式。宽容读取器和消费者驱动契约等模式通常应用于微服务。这些援助服务合同独立发展。在构建过程中执行消费者驱动的合同可以增强信心，并提供有关服务是否正常运行的快速反馈。事实上，我们知道澳大利亚有一个团队，他们通过消费者驱动的合同来推动新服务的构建。他们使用简单的工具来定义服务的协定。这甚至在编写新服务的代码之前就成为自动构建的一部分。然后，服务只在满足合同的程度上构建 - 这是一种优雅的方法，可以在构建新软件时避免“YAGNI”[8]困境。这些技术和围绕它们成长的工具通过减少服务之间的时间耦合来限制对中央合同管理的需求。

Perhaps the apogee of decentralised governance is the build it / run it ethos popularised by Amazon. Teams are responsible for all aspects of the software they build including operating the software 24/7. Devolution of this level of responsibility is definitely not the norm but we do see more and more companies pushing responsibility to the development teams. Netflix is another organisation that has adopted this ethos[10]. Being woken up at 3am every night by your pager is certainly a powerful incentive to focus on quality when writing your code. These ideas are about as far away from the traditional centralized governance model as it is possible to be.
也许去中心化治理的顶峰是亚马逊推广的构建/运行精神。团队负责他们构建的软件的所有方面，包括 24/7 全天候操作软件。这种责任的下放绝对不是常态，但我们确实看到越来越多的公司将责任推给开发团队。Netflix是另一个采用这种精神的组织[10]。每天凌晨 3 点被寻呼机吵醒，这无疑是在编写代码时关注质量的强大动力。这些想法与传统的集中式治理模式相去甚远。

Decentralized Data Management
分散式数据管理

Decentralization of data management presents in a number of different ways. At the most abstract level, it means that the conceptual model of the world will differ between systems. This is a common issue when integrating across a large enterprise, the sales view of a customer will differ from the support view. Some things that are called customers in the sales view may not appear at all in the support view. Those that do may have different attributes and (worse) common attributes with subtly different semantics.
数据管理的权力下放以多种不同的方式呈现。在最抽象的层面上，这意味着世界的概念模型在系统之间会有所不同。这是跨大型企业集成时的常见问题，客户的销售视图与支持视图不同。在销售视图中称为客户的某些内容可能根本不会出现在支持视图中。那些这样做的人可能具有不同的属性和（更糟的）具有微妙不同语义的共同属性。

This issue is common between applications, but can also occur within applications, particular when that application is divided into separate components. A useful way of thinking about this is the Domain-Driven Design notion of Bounded Context. DDD divides a complex domain up into multiple bounded contexts and maps out the relationships between them. This process is useful for both monolithic and microservice architectures, but there is a natural correlation between service and context boundaries that helps clarify, and as we describe in the section on business capabilities, reinforce the separations.
此问题在应用程序之间很常见，但也可能在应用程序中发生，特别是当该应用程序被划分为单独的组件时。思考这个问题的一个有用方法是 Bounded Context 的 Domain-Driven Design 概念。DDD 将复杂域划分为多个有界上下文，并映射出它们之间的关系。这个过程对于单体架构和微服务架构都很有用，但服务和上下文边界之间存在着自然的相关性，这有助于澄清，正如我们在业务功能一节中所描述的那样，加强了分离。

As well as decentralizing decisions about conceptual models, microservices also decentralize data storage decisions. While monolithic applications prefer a single logical database for persistant data, enterprises often prefer a single database across a range of applications - many of these decisions driven through vendor's commercial models around licensing. Microservices prefer letting each service manage its own database, either different instances of the same database technology, or entirely different database systems - an approach called Polyglot Persistence. You can use polyglot persistence in a monolith, but it appears more frequently with microservices.
除了分散有关概念模型的决策外，微服务还分散了数据存储决策。虽然整体式应用程序更喜欢使用单个逻辑数据库来存储持久性数据，但企业通常更喜欢跨一系列应用程序使用单个数据库 - 其中许多决策都是由供应商围绕许可的商业模式驱动的。微服务更愿意让每个服务管理自己的数据库，可以是同一数据库技术的不同实例，也可以是完全不同的数据库系统，这种方法称为多语言持久性。可以在单体架构中使用多语言持久性，但它在微服务中出现得更频繁。

Decentralizing responsibility for data across microservices has implications for managing updates. The common approach to dealing with updates has been to use transactions to guarantee consistency when updating multiple resources. This approach is often used within monoliths.
跨微服务分散数据责任对管理更新有影响。处理更新的常用方法是在更新多个资源时使用事务来保证一致性。这种方法通常用于单体系统。

Using transactions like this helps with consistency, but imposes significant temporal coupling, which is problematic across multiple services. Distributed transactions are notoriously difficult to implement and as a consequence microservice architectures emphasize transactionless coordination between services, with explicit recognition that consistency may only be eventual consistency and problems are dealt with by compensating operations.
使用这样的事务有助于保持一致性，但会带来显著的时间耦合，这在多个服务中是有问题的。众所周知，分布式事务很难实现，因此微服务架构强调服务之间的无事务协调，并明确认识到一致性可能只是最终的一致性，并且问题通过补偿操作来解决。

Choosing to manage inconsistencies in this way is a new challenge for many development teams, but it is one that often matches business practice. Often businesses handle a degree of inconsistency in order to respond quickly to demand, while having some kind of reversal process to deal with mistakes. The trade-off is worth it as long as the cost of fixing mistakes is less than the cost of lost business under greater consistency.
对于许多开发团队来说，选择以这种方式管理不一致是一个新的挑战，但它通常与业务实践相匹配。通常，企业会处理一定程度的不一致，以便快速响应需求，同时有某种逆转过程来处理错误。只要修复错误的成本低于在更高的一致性下失去业务的成本，这种权衡是值得的。

Infrastructure Automation
基础设施自动化

Infrastructure automation techniques have evolved enormously over the last few years - the evolution of the cloud and AWS in particular has reduced the operational complexity of building, deploying and operating microservices.
基础设施自动化技术在过去几年中取得了巨大的发展，尤其是云和 AWS 的发展降低了构建、部署和运营微服务的运营复杂性。

Many of the products or systems being build with microservices are being built by teams with extensive experience of Continuous Delivery and it's precursor, Continuous Integration. Teams building software this way make extensive use of infrastructure automation techniques. This is illustrated in the build pipeline shown below.
许多使用微服务构建的产品或系统都是由具有丰富持续交付经验的团队构建的，其前身是持续集成。以这种方式构建软件的团队广泛使用基础架构自动化技术。如下所示的生成管道对此进行了说明。

Figure 5: basic build pipeline
图 5：基本生成管道

Since this isn't an article on Continuous Delivery we will call attention to just a couple of key features here. We want as much confidence as possible that our software is working, so we run lots of automated tests. Promotion of working software 'up' the pipeline means we automate deployment to each new environment.
由于这不是一篇关于持续交付的文章，我们在这里只提请注意几个关键功能。我们希望尽可能多地相信我们的软件正在运行，因此我们进行了大量的自动化测试。在管道中推广工作软件意味着我们可以自动部署到每个新环境。

A monolithic application will be built, tested and pushed through these environments quite happlily. It turns out that once you have invested in automating the path to production for a monolith, then deploying more applications doesn't seem so scary any more. Remember, one of the aims of CD is to make deployment boring, so whether its one or three applications, as long as its still boring it doesn't matter[11].
一个整体式应用程序将非常愉快地在这些环境中构建、测试和推送。事实证明，一旦您投资了单体的生产路径自动化，那么部署更多应用程序似乎就不再那么可怕了。请记住，CD 的目标之一是让部署变得无聊，所以无论是一个还是三个应用程序，只要它仍然无聊就没关系 [11]。

Another area where we see teams using extensive infrastructure automation is when managing microservices in production. In contrast to our assertion above that as long as deployment is boring there isn't that much difference between monoliths and microservices, the operational landscape for each can be strikingly different.
我们看到团队使用广泛的基础设施自动化的另一个领域是在生产环境中管理微服务时。与我们上面的断言相反，只要部署是无聊的，单体和微服务之间就没有太大区别，两者的运营环境可能会截然不同。

Figure 6: Module deployment often differs
图 6：模块部署通常不同

Design for failure 为失败而设计

A consequence of using services as components, is that applications need to be designed so that they can tolerate the failure of services. Any service call could fail due to unavailability of the supplier, the client has to respond to this as gracefully as possible. This is a disadvantage compared to a monolithic design as it introduces additional complexity to handle it. The consequence is that microservice teams constantly reflect on how service failures affect the user experience. Netflix's Simian Army induces failures of services and even datacenters during the working day to test both the application's resilience and monitoring.
使用服务作为组件的后果是，需要设计应用程序，以便它们能够容忍服务的失败。由于供应商不可用，任何服务呼叫都可能失败，客户必须尽可能优雅地响应这一点。与单片设计相比，这是一个缺点，因为它引入了额外的复杂性来处理它。其结果是，微服务团队不断反思服务故障如何影响用户体验。Netflix 的 Simian Army 在工作日内诱发服务甚至数据中心的故障，以测试应用程序的弹性和监控能力。

This kind of automated testing in production would be enough to give most operation groups the kind of shivers usually preceding a week off work. This isn't to say that monolithic architectural styles aren't capable of sophisticated monitoring setups - it's just less common in our experience.
这种在生产中的自动化测试足以让大多数操作团队在下班一周前感到不寒而栗。这并不是说单体架构风格不能进行复杂的监控设置 - 它只是在我们的经验中不太常见。

Since services can fail at any time, it's important to be able to detect the failures quickly and, if possible, automatically restore service. Microservice applications put a lot of emphasis on real-time monitoring of the application, checking both architectural elements (how many requests per second is the database getting) and business relevant metrics (such as how many orders per minute are received). Semantic monitoring can provide an early warning system of something going wrong that triggers development teams to follow up and investigate.
由于服务随时可能发生故障，因此能够快速检测故障并在可能的情况下自动还原服务非常重要。微服务应用程序非常重视对应用程序的实时监控，检查架构元素（数据库每秒获取多少请求）和业务相关指标（例如每分钟收到多少订单）。语义监控可以提供一个早期预警系统，以触发开发团队的跟进和调查。

This is particularly important to a microservices architecture because the microservice preference towards choreography and event collaboration leads to emergent behavior. While many pundits praise the value of serendipitous emergence, the truth is that emergent behavior can sometimes be a bad thing. Monitoring is vital to spot bad emergent behavior quickly so it can be fixed.
这对于微服务架构尤为重要，因为微服务对编排和事件协作的偏好会导致紧急行为。虽然许多专家称赞偶然出现的价值，但事实是，紧急行为有时可能是一件坏事。监控对于快速发现不良的紧急行为至关重要，因此可以对其进行修复。

Monoliths can be built to be as transparent as a microservice - in fact, they should be. The difference is that you absolutely need to know when services running in different processes are disconnected. With libraries within the same process this kind of transparency is less likely to be useful.
单体可以构建为像微服务一样透明 - 事实上，它们应该是透明的。不同之处在于，您绝对需要知道在不同进程中运行的服务何时断开连接。如果图书馆处于同一流程中，这种透明度不太可能有用。

Microservice teams would expect to see sophisticated monitoring and logging setups for each individual service such as dashboards showing up/down status and a variety of operational and business relevant metrics. Details on circuit breaker status, current throughput and latency are other examples we often encounter in the wild.
微服务团队希望看到每个单独的服务的复杂监控和日志记录设置，例如显示启动/关闭状态的仪表板以及各种与运营和业务相关的指标。有关断路器状态、电流吞吐量和延迟的详细信息是我们在野外经常遇到的其他示例。

Evolutionary Design 进化设计

Microservice practitioners, usually have come from an evolutionary design background and see service decomposition as a further tool to enable application developers to control changes in their application without slowing down change. Change control doesn't necessarily mean change reduction - with the right attitudes and tools you can make frequent, fast, and well-controlled changes to software.
微服务从业者通常具有演进设计背景，并将服务分解视为一种进一步的工具，使应用程序开发人员能够在不减慢更改速度的情况下控制其应用程序中的更改。变更控制并不一定意味着减少变更 - 通过正确的态度和工具，您可以对软件进行频繁、快速且可控的更改。

Whenever you try to break a software system into components, you're faced with the decision of how to divide up the pieces - what are the principles on which we decide to slice up our application? The key property of a component is the notion of independent replacement and upgradeability[12] - which implies we look for points where we can imagine rewriting a component without affecting its collaborators. Indeed many microservice groups take this further by explicitly expecting many services to be scrapped rather than evolved in the longer term.
每当您尝试将软件系统分解为组件时，您都会面临如何划分各个部分的决定 - 我们决定对应用程序进行分割的原则是什么？组件的关键属性是独立替换和可升级性的概念[12]，这意味着我们寻找可以想象在不影响其协作者的情况下重写组件的点。事实上，许多微服务组织更进一步，明确地期望许多服务被废弃，而不是长期发展。

The Guardian website is a good example of an application that was designed and built as a monolith, but has been evolving in a microservice direction. The monolith still is the core of the website, but they prefer to add new features by building microservices that use the monolith's API. This approach is particularly handy for features that are inherently temporary, such as specialized pages to handle a sporting event. Such a part of the website can quickly be put together using rapid development languages, and removed once the event is over. We've seen similar approaches at a financial institution where new services are added for a market opportunity and discarded after a few months or even weeks.
Guardian 网站就是一个很好的例子，它设计和构建为一个整体，但一直在朝着微服务方向发展。单体仍然是网站的核心，但他们更喜欢通过构建使用单体 API 的微服务来添加新功能。这种方法对于本质上是临时性的功能特别方便，例如用于处理体育赛事的专用页面。网站的这一部分可以使用快速开发语言快速组合在一起，并在活动结束后删除。我们在一家金融机构看到了类似的方法，即为市场机会添加新服务，并在几个月甚至几周后被丢弃。

This emphasis on replaceability is a special case of a more general principle of modular design, which is to drive modularity through the pattern of change [13]. You want to keep things that change at the same time in the same module. Parts of a system that change rarely should be in different services to those that are currently undergoing lots of churn. If you find yourself repeatedly changing two services together, that's a sign that they should be merged.
这种对可替换性的强调是模块化设计更一般原则的一个特例，即通过变化模式来推动模块化[13]。您希望将同时更改的内容保留在同一个模块中。系统中很少更改的部分应该与当前正在经历大量流失的系统处于不同的服务中。如果您发现自己反复将两个服务更改在一起，则表明它们应该合并。

Putting components into services adds an opportunity for more granular release planning. With a monolith any changes require a full build and deployment of the entire application. With microservices, however, you only need to redeploy the service(s) you modified. This can simplify and speed up the release process. The downside is that you have to worry about changes to one service breaking its consumers. The traditional integration approach is to try to deal with this problem using versioning, but the preference in the microservice world is to only use versioning as a last resort. We can avoid a lot of versioning by designing services to be as tolerant as possible to changes in their suppliers.
将组件放入服务中为更精细的发布计划增加了机会。对于单体架构，任何更改都需要完整构建和部署整个应用程序。但是，对于微服务，只需重新部署修改的服务。这可以简化和加快发布过程。不利的一面是，您必须担心对一项服务的更改会破坏其使用者。传统的集成方法是尝试使用版本控制来解决这个问题，但微服务世界的偏好是只使用版本控制作为最后的手段。我们可以通过设计服务来尽可能容忍供应商的变化，从而避免大量的版本控制。