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π CloudWatch Book Progress: Explore the Chapters & Learn About Evidently
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! β 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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AWS for the Real World
Join our community of over 8,800 readers delving into AWS. We highlight real-world best practices through easy-to-understand visualizations and one-pagers. Expect a fresh newsletter edition every two weeks.
β Reading time: 10 minutes π Main Learning: Building a Serverless Platform With SST, Lambda & Next.js βοΈ Read the Full Post Online π Hey Reader ππ½ In this post, we want to guide you through our complete setup for our custom video platform. Our CloudWatch Book's Video Section This starts from the purchase to actually accessing our custom build video-access platform. Overview about our CloudWatch Book Landing Page & Video Platform Architecture We'll explain why we decided against a third-party...
β Reading time: 11 minutes π Main Learning: Step Functions - Express vs. Standard πΎ GitHub Code βοΈ Blog Post Hey Reader while Sandro is learning something new at the AWS Community Day in Munich today, we'll explore Express and Standard Step Functions, the two types of workflows offered by AWS Step Functions. Weβll break down their differences, when to use each, and the benefits of both. Example Application: running both workflow types to see their performance differences If you want to try...
Hey Reader First things first: we apologize for not providing updates on The CloudWatch Book for a while! π’ Sometimes, things don't go as planned and unexpected obstacles arise. But now, we're back in action, creating videos and putting the final touches on the book's content! π₯ Don't just take our word for it! As an early subscriber, here's a free video from one of our favorite chapters: Anomaly Detection π In this deep-dive, you'll learn how to detect unusual patterns in metrics without...