HTTP IPC FFI Rust Python

Calling Rust from Python

I recently watched GOTO conferences' talk Calling Functions Across Languages by Richard Feldman. I’m afraid I have to disagree with using the term 'language' in this context. It’s a no-brainer to call Java from Kotlin or Scala or to call Java from Kotlin. Hence, in the rest, I’ll use 'stack'. In the talk, the speaker cites two main reasons to go on this road: Gradual migration from one stack to the otherUsing a library that has no equivalent in one’s stack under the ass

HTTP REST

Leverage the richness of HTTP status codes

If you’re not a REST expert, you probably use the same HTTP codes over and over in your responses, mostly 200, 404, and 500. If using authentication, you might perhaps add 401 and 403; if using redirects 301 and 302, that might be all. But the range of possible status codes is much broader than that and can improve semantics a lot. While many discussions about REST focus on entities and methods, using the correct response status codes can make your API stand out. 201: Created Many appli

web HTTP cache performance

Web resource caching: Server-side

The subject of Web resource caching is as old as the World Wide Web itself. However, I’d like to offer an as-exhaustive-as-possible catalog of how one can improve performance by caching. Web resource caching can happen in two different places: client-side - on the browser and server side. In the previous post, I explained the former; this post focuses on the latter. While client-side caching works well, it has one central issue: to serve the resource locally, it must first have it in the

web HTTP cache performance

Web resource caching: Client-side

The subject of Web resource caching is as old as the World Wide Web itself. However, I’d like to offer an as-exhaustive-as-possible catalog of how one can improve performance by caching. Web resource caching can happen in two different places: client-side - on the browser and server-side. This post is dedicated to the former; the next post will focus on the latter. Caching 101 The idea behind caching is simple: if a resource is a time- or resource-consuming to compute, do it once and st

microservice Spring Framework Spring Cloud Kotlin HTTP monitoring Sleuth

HTTP headers forwarding in microservices

Microservices are not a trend anymore. Like it or not, they are here to stay. Yet, there’s a huge gap before embracing the microservice architecture and implementing them right. As a reminder, one might first want to check the many fallacies of distributed computed. Among all requirements necessary to overcome them is the ability to follow one HTTP request along microservices involved in a specific business scenario - for monitoring and debugging purpose. One possible implementation of it