我们正在使用akka及其camel插件为twimpact.com分发我们的分析和趋势处理。我们必须每秒处理50到1000条消息。除了使用camel进行多节点处理外，它还用于将单个处理器上的工作分配给多个工作人员，以获得最大性能。工作得很好，但需要了解如何处理拥塞。

免责声明:我是Akka的采购订单

此外，它还提供了一个更容易推理和纠正的并发大杂烩(参与者、代理、数据流并发)，并以STM的形式进行并发控制。

下面是一些你可以考虑的用例:

Transaction processing (online gaming, finance, statistics, betting, social media, telecom, ...) scale up, scale out, fault-tolerance / HA Service backend (any industry, any app) service REST, SOAP, cometd etc act as message hub / integration layer scale up, scale out, fault-tolerance / HA Snap-in concurrency/parallelism ( any app ) Correct Simple to work with and understand Just add the jars to your existing JVM project (use Scala, Java, Groovy or JRuby) Batch processing ( any industry ) Camel integration to hook up with batch data sources Actors divide and conquer the batch workloads Communications hub ( telecom, web media, mobile media ) scale up, scale out, fault-tolerance / HA Game server (online gaming, betting) scale up, scale out, fault-tolerance / HA BI/datamining/general purpose crunching scale up, scale out, fault-tolerance / HA insert other nice use cases here

到目前为止，我已经在两个实际项目中非常成功地使用了它。两者都在接近实时的交通信息领域(就像高速公路上的汽车一样)，分布在几个节点上，集成各方之间的消息，可靠的后端系统。我现在还不能透露客户的具体情况，当我得到批准的时候，也许可以把它作为参考。

Akka确实完成了这些项目，尽管我们在0.7版本时就开始了。(顺便说一下，我们正在使用scala)

最大的优势之一是，你可以轻松地用角色和消息组成一个系统，几乎没有样板，它的伸缩性非常好，没有手摇线程的复杂性，你几乎可以免费地在对象之间传递异步消息。

It is very good in modeling any type of asynchronous message handling. I would prefer to write any type of (web) services system in this style than any other style. (Have you ever tried to write an asynchronous web service (server side) with JAX-WS? that's a lot of plumbing). So I would say any system that does not want to hang on one of its components because everything is implicitly called using synchronous methods, and that one component is locking on something. It is very stable and the let-it-crash + supervisor solution to failure really works well. Everything is easy to setup programmatically and not hard to unit test.

还有一些优秀的附加模块。 Camel模块可以很好地插入到Akka中，并且可以使用可配置的端点轻松开发异步服务。

我对这个框架非常满意，它正在成为我们所构建的连接系统的事实上的标准。

我最近在Akka中实现了规范的map-reduce示例:Word count。所以这是Akka的一个用例:更好的性能。它更像是JRuby和Akka的参与者的一个实验，但它也表明Akka不仅仅是Scala或Java:它可以在JVM之上的所有语言上工作。

An example of how we use it would be on a priority queue of debit/credit card transactions. We have millions of these and the effort of the work depends on the input string type. If the transaction is of type CHECK we have very little processing but if it is a point of sale then there is lots to do such as merge with meta data (category, label, tags, etc) and provide services (email/sms alerts, fraud detection, low funds balance, etc). Based on the input type we compose classes of various traits (called mixins) necessary to handle the job and then perform the work. All of these jobs come into the same queue in realtime mode from different financial institutions. Once the data is cleansed it is sent to different data stores for persistence, analytics, or pushed to a socket connection, or to Lift comet actor. Working actors are constantly self load balancing the work so that we can process the data as fast as possible. We can also snap in additional services, persistence models, and stm for critical decision points.

在JVM上传递的Erlang OTP风格的消息对于在现有库和应用程序服务器的肩膀上开发实时系统来说是一个很棒的系统。

Akka允许您像在传统esb中那样进行消息传递，但速度更快!它还为您提供了框架中的工具，以管理解决方案所需的大量参与者池、远程节点和容错。

我们在工作中的几个项目中使用了Akka，其中最有趣的是与车辆碰撞修复有关。主要在英国，但现在扩展到美国，亚洲，大洋洲和欧洲。 我们使用参与者来确保实时提供碰撞修复信息，以实现安全且具有成本效益的车辆修复。

关于Akka的问题其实更多的是“你不能用Akka做什么”。它与强大的框架集成的能力、强大的抽象性和所有的容错能力使它成为一个非常全面的工具包。