The hottest Backend Substack posts right now

And their main takeaways
Category
Top Technology Topics
Sarah's Newsletter 99 implied HN points 19 Sep 23
  1. Decide which product feature should be behind a test, read the results of an A/B test, prioritize features based on data
  2. Understand that frontend tests focus on user experience and user groups in the browser, while backend tests require business logic and user assignment in the database
  3. Choose frontend user group assignment for speed and simplicity via firing analytics events; go for backend assignment for more complete data by storing user assignment in a database model
Technology Made Simple 39 implied HN points 24 Jul 22
  1. To ace System Design Interviews, read/watch more system design mock interviews on YouTube, engineering blogs, and learn about important technologies/concepts.
  2. When designing a system like the backend for Google Photos, start with domain analysis, note requirements (functional and non-functional), expected load/performance, and user profiles for valuable solutions.
  3. Engage with the content you find helpful by liking, sharing, and offering feedback to creators. It helps them reach more people and improve their work.
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AnyCable Broadcasts 0 implied HN points 29 Sep 21
  1. AnyCable v1.2 introduces JWT identification and 'hot streams' for powering up efficient Hotwire frontends by moving functions from Ruby to Go.
  2. JWT identification standardizes authentication for WebSockets, protects from cross-site WebSocket hijacking, and boosts performance by removing the need for RPC calls.
  3. Combining JWT identification with signed streams in AnyCable allows the creation of subscriptions without touching RPC, offering improved efficiency for Hotwire and CableReady functionality.
ML Under the Hood 0 implied HN points 25 Feb 23
  1. Developing a prototype ML product for niche languages and cultures has unique challenges that are not present in more common languages.
  2. Focusing on core objectives is crucial for efficient development and achieving sprint goals.
  3. Prioritizing functionality over speed in ML inference pipelines can lead to tangible progress and real product advancements.