In their new release, Spring decided to change the logic behind loading configuration files.

To represent elements that may contribute to the environment, a ConfigDataEnvironmentContributor is introduced, each contributor would be replaced during the process.

Spring decided to use a tree as a data structure in order to process/apply the configuration data.

I will refer to ConfigDataEnvironmentContributor as CDEContributor.

Contributors tree

Each contributor can imports some properties (more on that later), and it will be appended as children, thus creating a whole tree.

Each contributor will contain some metadata describing the node:

1. location: a configDataLocation that will be resolved using a…


In Reactive Programming (Reactor)- Part 1, we explored the fundamentals of Reactive programming and discussed briefly Reactor Project.

In this article we will explore one of the most important and complex operator, FlatMap.

I highly recommend spending some time reading part 1 or any article explaining the basic principle of reactive programming (Reactor or RxJava doesn’t matter), so that you can follow easily.

QueueSubscription

It is basically just queue and subscription under one interface. it allows negotiating the fusion mode between subsequent operators.

The idea is that upstream can provide not only subscription but also allows subscribers to directly access…


Numerous components on a network, such as DNS servers, switches, load balancers, and others can generate errors anywhere in the life of a given request. A common way to handle theses failures is through the use of retries, and retries with backoff and jitter.

As an engineer, your should clearly enforce these practices when dealing with network connectivity or similar communication protocols over the internet.

Retries, as mentioned previously, are a nice way for dealing with transient remote API errors in client applications. …


Introduction

In Traditional API servers, to deal with a large number of concurrent users, requests handling are made asynchronous. These solutions are based on several options (Callbacks, Future, CompletableFuture …).
We may think that using this kind of approach we can be completely asynchronous and be always available and performant, remember that each thread requires stack memory, there is always a limitation (error handling, call-back hell …), not to say that these are bad solutions, I just want to emphasize that it has not been designed to deal with operation that requires latency.

Idea behind the Reactive programming is to move…

Kondah Mouad

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