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Ruby on Rails is the most popular web framework in the Ruby ecosystem and has a large user base, ranging from freelancers to large established companies. With an active user community and wide-ranging documentation, it can be used to build everything from simple applications to complex web platforms. That said, a new contestant is taking on Rails’ dominance for the full-stack Ruby framework title: Hanami.

Erlang is renowned for its remarkable fault tolerance and high concurrency. Erlang's scheduler efficiently handles many lightweight processes. The scheduler plays a crucial role in managing processes, concurrency, and system resources, efficiently coordinating these elements to help Erlang maintain fault tolerance and support high levels of concurrency in its applications. This post will dissect some of the scheduler's key components and shed light on how it works internally. Let's get started!

Rate limiting is a fundamental mechanism for controlling the number of requests a client can make to a server in a given time frame. In a world where more than 30% of web traffic comes from malicious bots, that proactive strategy is critical to protect servers from abuse. In this tutorial, you'll delve into the concept of rate limiting and understand why you need it in your Node.js backend. Then, you'll learn how to implement it in Express to block or slow down incoming excess requests.

As your Elixir app grows, you might need advanced control over how and where to perform background tasks or pull them off queues to manage back pressure. In this post, you will learn how to handle background jobs with Flume, a job processing system that uses GenStage and Redis. It provides durability, back pressure, job scheduling, rate limiting, and batch processing, among other things. We will expand on each of these features in detail.