|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/continuous-feedback/
课程评论：没有评论
**课程名称：** 通过持续反馈提升你的编码技巧 **课程概述：** 您是否了解最近引入的代码库的变更？您何时会注意到问题？持续反馈（Continuous Feedback，简称 CF）是一种新的开发实践，旨在通过在开发过程中实际利用代码运行时数据来缩短反馈周期。OpenTelemetry 通过出色的库支持和用于追踪、指标等的标准规范，使这一切成为可能。 通过实践 CF，开发者可以通过更短的反馈周期来提高生产力。他们可以更早地获取有关其代码的数据，在编码过程中以更短的迭代来检测和解决问题。 本课程将超越使用开源可观测性工具和技术的“新奇感”，探讨如何真正让它们对开发者有用。我们将着眼于启用 OpenTelemetry 收集开发和测试数据的优势，并考察有助于分析应用程序运行时的开源工具。在整个课程中，我们将通过代码示例，展示常见的反模式、代码坏味、隐藏错误以及此未开发数据源可以揭示的其他类型问题。 最终，我们的目标不应仅仅是观察应用程序或创建美观的仪表板；而应在于利用可观测性数据来实现更有效的开发流程并编写更好的代码。
What do you know about the code changes that were just introduced into the codebase? When will you notice if something goes wrong?Continuous Feedback is a new dev practice that aims to make practical usage of code runtime data to shorten the feedback loop during development. OpenTelemetry makes it possible with great library support and a standard spec for tracing, metrics, and more.By practicing CF, developers can increase productivity with shorter feedback loops. Getting access to data about their code much earlier, detecting and resolving issues in shorter iterations, as-they-code.In this course, we'll look past the novelty of using OSS observability tools and technologies, to discuss how we can actually make them useful for developers. We'll look at the benefits of enabling OpenTelemetry collection for dev and test data and examine OSS tools to help analyze the application runtime. Throughout the talk, we'll go over code examples of common anti-patterns, code smells, hidden errors, and other types of problems that this untapped source of data can reveal.Ultimately, the goal should not be simply observing the application or creating nice-looking dashboards. Rather, success is in leveraging observability data in order to achieve a more effective dev process and write better code.
