“Microservices” - yet another new term on the crowded streets of software architecture. Although our natural inclination is to pass such things by with a contemptuous glance, this bit of terminology describes a style of software systems that we are finding more and more appealing. We’ve seen many projects use this style in the last few years, and results so far have been positive, so much so that for many of our colleagues this is becoming the default style for building enterprise applications. Sadly, however, there’s not much information that outlines what the microservice style is and how to do it.
“微服务” - 软件架构拥挤街道上的另一个新术语。虽然我们的自然倾向是轻蔑地忽略这些东西，但这个术语描述了一种我们发现越来越吸引人的软件系统风格。在过去的几年里，我们看到许多项目都使用这种风格，到目前为止，结果是积极的，以至于对于我们的许多同事来说，这正在成为构建企业应用程序的默认风格。然而，遗憾的是，没有太多信息概述微服务风格是什么以及如何做到这一点。
In short, the microservice architectural style  is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API. These services are built around business capabilities and independently deployable by fully automated deployment machinery. There is a bare minimum of centralized management of these services, which may be written in different programming languages and use different data storage technologies.
简而言之，微服务架构风格  是一种将单个应用程序开发为一套小型服务的方法，每个服务都在自己的进程中运行并与轻量级机制（通常是 HTTP 资源 API）进行通信。这些服务围绕业务功能构建，并可通过全自动部署机制独立部署。对这些服务进行最低限度的集中管理，这些服务可能用不同的编程语言编写并使用不同的数据存储技术。
Such a monolithic server is a natural way to approach building such a system. All your logic for handling a request runs in a single process, allowing you to use the basic features of your language to divide up the application into classes, functions, and namespaces. With some care, you can run and test the application on a developer’s laptop, and use a deployment pipeline to ensure that changes are properly tested and deployed into production. You can horizontally scale the monolith by running many instances behind a load-balancer.
Monolithic applications can be successful, but increasingly people are feeling frustrations with them - especially as more applications are being deployed to the cloud . Change cycles are tied together - a change made to a small part of the application, requires the entire monolith to be rebuilt and deployed. Over time it’s often hard to keep a good modular structure, making it harder to keep changes that ought to only affect one module within that module. Scaling requires scaling of the entire application rather than parts of it that require greater resource.
整体式应用程序可以成功，但越来越多的人对它们感到沮丧 - 特别是随着越来越多的应用程序被部署到云中。更改周期捆绑在一起 - 对应用程序的一小部分所做的更改需要重建和部署整个整体。随着时间的推移，通常很难保持良好的模块化结构，这使得保持应该只影响该模块中的一个模块的更改变得更加困难。扩展需要扩展整个应用程序，而不是需要更多资源的部分。
These frustrations have led to the microservice architectural style: building applications as suites of services. As well as the fact that services are independently deployable and scalable, each service also provides a firm module boundary, even allowing for different services to be written in different programming languages. They can also be managed by different teams .
We do not claim that the microservice style is novel or innovative, its roots go back at least to the design principles of Unix. But we do think that not enough people consider a microservice architecture and that many software developments would be better off if they used it.
We cannot say there is a formal definition of the microservices architectural style, but we can attempt to describe what we see as common characteristics for architectures that fit the label. As with any definition that outlines common characteristics, not all microservice architectures have all the characteristics, but we do expect that most microservice architectures exhibit most characteristics. While we authors have been active members of this rather loose community, our intention is to attempt a description of what we see in our own work and in similar efforts by teams we know of. In particular we are not laying down some definition to conform to.
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.
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.
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 .)
微服务架构将使用库，但它们组件化自己的软件的主要方法是分解为服务。我们将库定义为链接到程序中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。（这与许多面向对象程序  中的服务对象的概念不同。
One main reason for using services as components (rather than libraries) is that services are independently deployable. If you have an application  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。如果您的应用程序  由单个进程中的多个库组成，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，如果该应用程序分解为多个服务，则许多单个服务更改只需要重新部署该服务。这不是绝对的，一些更改会改变服务接口，从而导致一些协调，但良好的微服务架构的目的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.
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，这通常使用起来更尴尬。如果需要更改组件之间的责任分配，则在跨越流程边界时，这种行为移动更难实现。
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.
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.
在寻求将大型应用程序拆分为多个部分时，管理通常侧重于技术层，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，并充分利用两害相权取其轻 - 只需将逻辑强制到他们有权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）的组织都将产生一个设计，其结构是组织通信结构的副本。- Melvin Conway, 1968—梅尔文·康威，1968年
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.
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.
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.
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.
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.
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.
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.
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.
在不同流程之间构建通信结构时，我们已经看到许多产品和方法强调在通信机制本身中投入大量智能。企业服务总线 （ESB） 就是一个很好的例子，其中 ESB 产品通常包括用于消息路由、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解耦和内聚 - 它们拥有自己的域逻辑，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。这些是使用简单的 RESTish 协议编排的，而不是复杂的协议，如 WS-Choregraphy、BPEL 或中央工具的编排。
The two protocols used most commonly are HTTP request-response with resource API’s and lightweight messaging. The best expression of the first is
Be of the web, not behind the web属于网络，而不是落后于网络- 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.
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发送消息。选择的基础设施通常是哑的（哑的，因为仅充当消息路由器） - 像 RabbitMQ 或 ZeroMQ 这样的简单实现除了提供可靠的异步结构之外并没有做更多的事情 - 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.
在整体式架构中，组件在进程中执行，它们之间的通信是通过方法调用或函数调用进行的。将单体架构更改为微服务的最大问题在于更改通信模式。从内存中方法调用到 RPC 的朴素转换会导致聊天通信，性能不佳。相反，您需要用更粗粒度的方法替换细粒度通信。
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工作，虽然整体式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. 将单体架构的组件拆分为服务，我们在构建每个组件时可以选择。您想使用 Node.js 来建立一个简单的报告页面吗？去吧。C++一个特别粗糙的近实时组件？好。您想换入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，仅仅因为您可以做某事并不意味着您应该这样做 - 但以这种方式对系统进行分区意味着您可以选择。
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不同的标准方法。与其使用写在纸上的一组定义的标准，他们更喜欢生成有用的工具的想法，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。这些工具通常从实现中获取，并与更广泛的群体共享，有时但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，最重要的是经过实战测试的代码作为库共享，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，可以选择不同的方法。共享库往往侧重于数据存储、进程间通信以及我们将在下面进一步讨论的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'[](https://martinfowler.com/articles/microservices.html#footnote-YAGNI) 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，因为它们往往更多。只是他们正在寻找管理这些合同的不同方法。宽容读取器和消费者驱动合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，允许他们定义服务的合同。这甚至在编写新服务的代码之前就成为自动生成的一部分。然后，服务仅构建到满足合同的程度 - 这是一种优雅的方法，可以在构建新软件时避免“YAGNI”困境。这些技术和围绕它们发展的工具通过减少服务之间的时间耦合来限制对集中合同管理的需求。
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[](https://martinfowler.com/articles/microservices.html#footnote-netflix-flowcon). 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最高点是亚马逊推广的构建/运行它的精神。团队负责他们构建的软件的各个方面，包括 24/7 全天候操作软件。这种级别的责任下放绝对不是常态，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。每天凌晨 3 点被寻呼机叫醒，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。
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. 数据管理的分散化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将在系统之间有所不同。这是跨大型企业集成时的常见问题，客户的销售视图将与支持视图不同。在销售视图中称为客户的某些内容可能根本不显示在支持视图中。那些这样做的人可能具有不同的属性和（更糟糕的）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，但也可能发生在应用程序中，尤其是当该应用程序划分为单独的组件时。对此的一个有用思考方法是界定上下文的域驱动设计概念。DDD 将一个复杂的域划分为多个边界上下文，并映射出它们之间的关系。此过程对于整体式架构和微服务体系结构都很有用，但服务和上下文边界之间存在自然的相关性，这有助于澄清，正如我们在业务功能部分中描述的那样，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的单个数据库 - 其中许多决策都是通过供应商围绕许可的商业模式驱动的。微服务更喜欢让每个服务管理自己的数据库，要么是同一数据库技术的不同实例，要么是完全不同的数据库系统 - 这种方法称为多语言持久性。可以在整体式架构中使用多语言持久性，但它在微服务中更频繁地出现。
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。此方法通常在整体式架构中使用。
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，但会施加重要的时间耦合，这在多个服务中存在问题。众所周知，分布式事务难以实现，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，问题通过补偿操作来处理。
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. 选择以这种方式管理不一致对许多开发团队来说是一个新的挑战，但它通常与业务实践相匹配。通常，企业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。只要在更大的一致性下，修复错误的成本低于失去业务的成本，权衡是值得的。
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发生了巨大的变化 - 特别是云和AWS的发展降低了构建，部署和运营微服务的操作复杂性。
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. 使用微服务构建的许多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设施自动化技术。下面显示的生成管道对此进行了说明。
Figure 5: basic build pipeline 图 5：基本构建管道
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，因此我们将在这里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工作，因此我们运行了许多自动化测试。在管道中“向上”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[](https://martinfowler.com/articles/microservices.html#footnote-trickycd). 一个整体式应用程序将非常愉快地构建、测试和推送这些环境。事实证明，一旦您投资了自动化单体架构的生产路径，那么部署更多应用程序似乎不再那么可怕了。请记住，CD 的目标之一是使部署变得无聊，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 。
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架构自动化的另一个领域是在生产中管理微服务时。与我们上面的断言相反，只要部署很无聊，单体架构和微服务之间就没有太大区别，每个操作环境可能会大不相同。
Figure 6: Module deployment often differs 图 6：模块部署通常不同
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结果是，需要设计应用程序，以便它们可以容忍服务的失败。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对此做出响应。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。
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. 生产中的这种自动化测试足以让大多数运营团队在下班一周前感到不寒而栗。这并不是说整体式架构风格无法进行复杂的监视设置 - 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. 由于服务可能随时失败，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（数据库每秒获得多少请求）和业务相关指标（例如每分钟收到多少订单）。语义监视可以提供出现问题的早期预警系统，从而触发开发团队跟进和调查。
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. 这对于微服务体系结构尤其重要，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涌现的价值，但事实是，涌现行为有时可能是一件坏事。监控对于快速发现不良紧急行为至关重要，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. 整体式架构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。对于同一流程中的库，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针对每个单独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操作和业务相关指标。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。
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. 微服务从业者通常来自进化设计背景，并将服务分解视为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应用程序中的更改的进一步工具。变更控制并不一定意味着减少变更 - 使用正确的态度和工具，您可以对软件进行频繁、快速且控制良好的更改。
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[](https://martinfowler.com/articles/microservices.html#footnote-RCA) - 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部分的决定 - 我们决定将应用程序切片的原则是什么？组件的关键属性是独立替换和可升级性的概念  - 这意味着我们寻找可以想象重写组件而不影响其协作者的点。事实上，许多微服务组织更进一步，明确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 网站是一个很好的示例，它被设计和构建为一个整体，但一直在向微服务方向发展。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。此方法对于本质上是临时的功能特别方便，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也看到了类似的方法，即为市场机会添加新服务，并在几个月甚至几周后放弃。
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 [](https://martinfowler.com/articles/microservices.html#footnote-beck-rate-of-change). 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，即通过变化模式来驱动模块化。您希望将同时更改的内容保留在同一模块中。系统中很少更改的部分应该与当前正在经历大量流失的服务处于不同的服务中。如果您发现自己反复将两个服务更改为一起，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规划增加了机会。对于整体式架构，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。缺点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处理此问题，但微服务世界中的偏好是仅使用版本控制作为最后的手段。我们可以通过设计尽可能容忍供应商变化的服务来避免大量版本控制。
Our main aim in writing this article is to explain the major ideas and principles of microservices. By taking the time to do this we clearly think that the microservices architectural style is an important idea - one worth serious consideration for enterprise applications. We have recently built several systems using the style and know of others who have used and favor this approach. 我们撰写本文的主要目的是解释微服务的主要思想和原则。通过花时间这样做，我们清楚地认为微服务架构风格是一个重要的想法 - 一个值得企业应用程序认真考虑的想法。我们最近使用这种风格构建了几个系统，并知道其他使用和赞成这种方法的人。
Many development teams have found the microservices architectural style to be a superior approach to a monolithic architecture. But other teams have found them to be a productivity-sapping burden. Like any architectural style, microservices bring costs and benefits. To make a sensible choice you have to understand these and apply them to your specific context. 许多开发团队发现微服务架构风格是整体架构的卓越方法。但其他团队发现它们是一种消耗生产力的负担。与任何架构风格一样，微服务也带来了成本和收益。要做出明智的选择，您必须了解这些并将它们应用于您的特定环境。
Those we know about who are in some way pioneering the architectural style include Amazon, Netflix, The Guardian, the UK Government Digital Service, realestate.com.au, Forward and comparethemarket.com. The conference circuit in 2013 was full of examples of companies that are moving to something that would class as microservices - including Travis CI. In addition there are plenty of organizations that have long been doing what we would class as microservices, but without ever using the name. (Often this is labelled as SOA - although, as we've said, SOA comes in many contradictory forms. [](https://martinfowler.com/articles/microservices.html#footnote-already)) 我们所知道的那些以某种方式开创建筑风格的人包括亚马逊，Netflix，卫报，英国政府数字服务，realestate.com.au，Forward和 comparethemarket.com。2013年的巡回会议充满了公司转向微服务的例子 - 包括Travis CI。此外，还有很多组织长期以来一直在做我们归类为微服务的事情，但从未使用过这个名称。（通常这被标记为SOA - 尽管正如我们所说，SOA有许多相互矛盾的形式。)
Despite these positive experiences, however, we aren't arguing that we are certain that microservices are the future direction for software architectures. While our experiences so far are positive compared to monolithic applications, we're conscious of the fact that not enough time has passed for us to make a full judgement. 然而，尽管有这些积极的经历，但我们并不认为微服务是软件架构的未来方向。虽然与单体应用程序相比，我们迄今为止的经验是积极的，但我们意识到，我们没有足够的时间做出全面的判断。
Often the true consequences of your architectural decisions are only evident several years after you made them. We have seen projects where a good team, with a strong desire for modularity, has built a monolithic architecture that has decayed over the years. Many people believe that such decay is less likely with microservices, since the service boundaries are explicit and hard to patch around. Yet until we see enough systems with enough age, we can't truly assess how microservice architectures mature. 通常，架构决策的真正后果仅在您做出决策几年后才显现出来。我们已经看到一些项目，一个优秀的团队，对模块化有强烈的渴望，已经建立了一个多年来已经衰败的单体架构。许多人认为，微服务不太可能出现这种衰减，因为服务边界是明确的，很难修补。然而，除非我们看到足够多的系统具有足够的年龄，否则我们无法真正评估微服务架构的成熟程度。
There are certainly reasons why one might expect microservices to mature poorly. In any effort at componentization, success depends on how well the software fits into components. It's hard to figure out exactly where the component boundaries should lie. Evolutionary design recognizes the difficulties of getting boundaries right and thus the importance of it being easy to refactor them. But when your components are services with remote communications, then refactoring is much harder than with in-process libraries. Moving code is difficult across service boundaries, any interface changes need to be coordinated between participants, layers of backwards compatibility need to be added, and testing is made more complicated. 人们可能期望微服务成熟度低下，这当然是有原因的。在任何组件化的努力中，成功都取决于软件与组件的匹配程度。很难确切地弄清楚组件边界应该在哪里。进化设计认识到正确边界的困难，因此易于重构边界的重要性。但是，当您的组件是具有远程通信的服务时，重构比使用进程内库要困难得多。跨服务边界移动代码很困难，任何接口更改都需要在参与者之间进行协调，需要添加向后兼容性层，并且测试变得更加复杂。
Another issue is If the components do not compose cleanly, then all you are doing is shifting complexity from inside a component to the connections between components. Not just does this just move complexity around, it moves it to a place that's less explicit and harder to control. It's easy to think things are better when you are looking at the inside of a small, simple component, while missing messy connections between services. 另一个问题是，如果组件没有干净地组合，那么您所做的只是将复杂性从组件内部转移到组件之间的连接。这不仅只是移动复杂性，还会将其移动到一个不那么明确且难以控制的地方。当您查看一个小而简单的组件的内部时，很容易认为事情会更好，同时缺少服务之间的混乱连接。
Finally, there is the factor of team skill. New techniques tend to be adopted by more skillful teams. But a technique that is more effective for a more skillful team isn't necessarily going to work for less skillful teams. We've seen plenty of cases of less skillful teams building messy monolithic architectures, but it takes time to see what happens when this kind of mess occurs with microservices. A poor team will always create a poor system - it's very hard to tell if microservices reduce the mess in this case or make it worse. 最后，还有团队技能的因素。新技术往往被更熟练的团队采用。但是，对于技能较强的团队更有效的技术不一定适用于技能较低的团队。我们已经看到很多不太熟练的团队构建混乱的整体架构的案例，但是当微服务发生这种混乱时会发生什么需要时间。一个糟糕的团队总是会创建一个糟糕的系统 - 很难判断在这种情况下微服务是减少了混乱还是使情况变得更糟。
One reasonable argument we've heard is that you shouldn't start with a microservices architecture. Instead begin with a monolith, keep it modular, and split it into microservices once the monolith becomes a problem. (Although this advice isn't ideal, since a good in-process interface is usually not a good service interface.)
So we write this with cautious optimism. So far, we've seen enough about the microservice style to feel that it can be a worthwhile road to tread. We can't say for sure where we'll end up, but one of the challenges of software development is that you can only make decisions based on the imperfect information that you currently have to hand. 所以我们以谨慎乐观的态度写这篇文章。到目前为止，我们已经看到了足够多的微服务风格，觉得这可能是一条值得走的道路。我们不能确定我们最终会在哪里，但软件开发的挑战之一是你只能根据你目前必须掌握的不完美的信息做出决策。