大型单体库的持续部署
Uber’s business runs on a myriad of microservices. Ensuring that changes to all of these services are deployed safely and in a timely manner is critical. By utilizing continuous deployment to automate this process, we ensure that new features, library updates, and security patches are all delivered to production without unnecessary delays, improving the overall quality of code serving our business.
Uber的业务运行在众多微服务上。确保所有这些服务的更改能够安全地和及时地部署是至关重要的。通过利用持续部署来自动化这个过程，我们确保新功能、库更新和安全补丁都能够在不必要的延迟下交付到生产环境，提高了为我们业务提供服务的代码的整体质量。
In this article, we share how we reimagined continuous deployment of microservices at Uber to improve our deployment automation and the user experience of managing microservices, while tackling some of the peculiar challenges of working with large monorepos with increasing commit volumes.
在本文中，我们分享了Uber如何重新构想微服务的持续部署，以改进我们的部署自动化和管理微服务的用户体验，同时解决了与处理大型单体代码库和不断增加的提交量相关的一些特殊挑战。
Over the last few years we have invested heavily in maturing our tools to accommodate the continued growth of our business, while reducing production incidents. With a steady growth in code output, and more than 50% of all incidents being caused directly by code changes, our ability to enable continuous, safe deployments without impeding productivity as the business scales, is crucial for Uber’s success.
在过去几年中，我们在成熟我们的工具方面投入了大量的精力，以适应我们业务的持续增长，同时减少生产事故。随着代码产出的稳定增长，超过50%的所有事故直接由代码更改引起，我们能够在业务规模扩大的同时实现持续、安全的部署，而不会妨碍生产力，这对Uber的成功至关重要。
It is commonly known and evident in the industry [1] [2] that continuous deployment (CD) of code to production intrinsically reduces the risk of introducing bugs or defects. This is not only due to the use of CD itself ensuring that bugs and vulnerabilities are patched in a timely manner, but more so the best practices, culture, and discipline that must be in place before engineers gain enough confidence to let a machine automatically deploy their code. Before enabling CD, engineers tend to ensure they have adopted good engineering practices, such as: