内容简介：The retry pattern is an extremely important pattern to make applications and services more resilient to transient failures. A transient failure is a common type of failure in a cloud-based distributed architecture. This is often due to the nature of the ne
The retry pattern is an extremely important pattern to make applications and services more resilient to transient failures. A transient failure is a common type of failure in a cloud-based distributed architecture. This is often due to the nature of the network itself (loss of connectivity, timeout on requests, and so on). Transient faults occur when services are hosted separately and communicate over the wire, most likely over a HTTP protocol. These faults are expected to be short-lived. Repeating such a request that has previously failed could succeed on a subsequent attempt.
Retry Strategies
The different retry strategies are
Retry – The source application can immediately retry to send the request to the service. If the specific fault is unusual or rare, the probability of success when repeating the request is very high.
Retry after a delay – The source application can retry to send the request to the cloud service after a period of time (that normally increases exponentially). This is a common practice when the failure event is due to reasons such as cloud service busy and so on.If the fault is caused by one of the more commonplace connectivity or busy failures, then the application has to wait for some time and try again.
Sliding Retry – The source application will retry repeatedly based on schedule and keeps adding an incremental delay in subsequent tries. For example, the retry logic may multiply the waiting period of 60 seconds by increment a try count from 1 to the number of tries and so on. This helps in reducing the overall number of retries.
Retry With Jitter – The sliding retry and the exponential backoff retry add a predictable sequence in their retry and backoff timelines. If there are multiple calls to the service at the same time and the same retry policy is applied then all the calls will retry and back off at the same time. To prevent this we need to add a certain randomness to the retry logic. This can be one by introducing a jitter to the retry policy. The jitter is a random calculation that results in different retry and backoff timelines for various calls.
Cancel – The source application can cancel the request to the cloud service and throw an exception. This is a common practice when the failure is not transient or is likely to be unsuccessful if repeated.
A real world example of policies based on retry strategy is at this Azure guidance .
Polly is an example of a library which provides retry policies in .Net core. I will be writing a future blog post using polly to demonstrate both retry and circuit breaker patterns .
Summary
Article Name
Retry pattern - A systems resilience pattern
Author
Pradeep Loganathan
Publisher Name
pradeeploganathan.com
以上就是本文的全部内容，希望本文的内容对大家的学习或者工作能带来一定的帮助，也希望大家多多支持 码农网
猜你喜欢:
本站部分资源来源于网络，本站转载出于传递更多信息之目的，版权归原作者或者来源机构所有，如转载稿涉及版权问题，请联系我们。
用户思维+：好产品让用户为自己尖叫
[美] Kathy Sierra / 石航 / 人民邮电出版社 / 2017-9 / 69.00元
畅销产品与普通产品的本质区别是什么？若没有巨额预算、不爱营销噱头、不开奢华的产品发布会，如何打造可持续成功的产品？本书针对上述问题提出了新颖的观点：用户并不关心产品本身有多棒，而是关心使用产品时自己有多棒。作者利用其多年的交互设计经验，生动阐释了这一观点背后的科学。可贵的是，本书并不止步于解释“为什么”，还清晰呈现了“怎么做”。 本书风格活泼、图文并茂，其对话式内容既引人入胜，又引人深思，适......一起来看看 《用户思维+：好产品让用户为自己尖叫》 这本书的介绍吧!
