Happy New Year, Reader! π We hope you had some great holidays and could recharge with your loved ones. In this update, we will show you the table of contents of the CloudWatch Book and give you some insights into a lesser-known feature of CloudWatch - Evidently. As always, we love to hear your feedback. If you have any topics that you are missing or think are completely useless, let us know! Table of Contents
These are all the high-level chapters. The major part of the book will be in Chapters 4 - 8. Because we think these are the most important ones. All checked (β ) chapters are already done, in an initial draft version. Everything else is still in the works. The chapters are not pure theory! They will include a lot of code and examples from the example project. You can use your own AWS Account and reproduce everything we explain in the book. Additional ChapterDavid Yanacek (Engineer @CloudWatch) has an amazing talk about Observability from the last re:Invent. We recommend you check this one out! ββ He structured his talk around diagnosing issues, uncovering hidden issues, and preventing future issues. This got us thinking about adding a second part to the book. The second part would all be about applying the CloudWatch Fundamentals on detecting, finding, and preventing issues. Let's dive into one small part of the upcoming book: CloudWatch Evidently. Evidently - Feature Flags and Dark LaunchesAmazon CloudWatch Evidently is a feature within the CloudWatch suite designed to help you run experiments and gain insights into your experimental features or proof-of-concepts before releasing them to the full audience of your application. You can decide which features are activated for which part of your users and you can measure the impact by collecting metrics. The key components of Evidently are:
In our book's application, we'll also go in-depth with Evidently by implementing several feature flags that steer some features. We'll also show you how Evidently helps to collect metrics on the different feature flag configurations so we can make sense of the experiments we run. Previous Updates Our goal is to let you participate in the creation of the CloudWatch Book as best as possible. For that, we want to send 1-2 emails per month. If you've missed the last ones, you can find them here:
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β Reading time: 14 minutes π Main Learning: Feature Flags with AWS AppConfig πΎ GitHub Repository βοΈ Read the Full Post Online π Hey Reader ππ½ There's no other field where it's so common to have "a small side-project" like in the software industry. Even though it's possible to build things as quickly as ever before due to cloud providers, tools, platforms, and AI, many indie founders (and also large enterprises) tend to fall into the same trap: they tend to build features that users do not...
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β Reading time: 9 minutes π Main Learning: Polling or WebSockets: Choosing with Amazon API Gateway πΎ GitHub Repository βοΈ Read the Full Post Online π Hey Reader ππ½ What would you use for quick and regular data updates inside your web app? Or let's phrase it another way: how would you choose between Polling and WebSockets? π Understanding the nuances between these two communication methods is important, as they both come with their own advantages, gotchas, and side effects that are not very...