Memoization is a caching technique to make your Ruby application run more efficiently and faster. In this post, we'll look at the benefits of memoization and when to use it in your Ruby application. We'll also look at some memoization mistakes to avoid. Let's first start by looking at code optimization — what it is and some of the different optimization techniques available.
In an Elixir application, you might need to access certain data frequently, which can be costly. The access time involved in retrieving data at every step can cause high latency, or even make the application crash (due to an increased workload on the database). Caching is the best technique to store the most frequently accessed data and minimize database data retrieval, improving the overall performance of the application.
Web applications usually rely heavily on databases, for the most part. And as applications grow, databases grow too. We keep scaling web servers and background workers to keep up with the heavy load. But eventually, the database needs to keep up with all the new connections from these processes. One way to tackle this is to grow a database with an app using vertical scaling. This means adding more CPU power and memory to the database server. But this is usually slow.
Changes in the upcoming Phoenix 1.7 release have led us to re-think how AppSignal for Phoenix works. AppSignal for Phoenix version 2.2.0 introduces our changes to make upgrading to Phoenix 1.7 easier. In this blog post, we'll outline what's changed and why.
As of today (06/12/2022), Hanami 2.0.1 has been released. Read more about the enhancements, bug fixes and gems in release 2.0.1. Hanami 2 was released on 22 November, concluding four years of work on this version. It brings a breath of fresh air into Ruby's web development community. Version 2.0 is not just an incremental upgrade. One could say it's a project written anew, with bright ideas from version one rebuilt on top of a solid dry-rb libraries ecosystem.
