springdoc-openapi VS PostgreSQL

The issue is that the springdoc-openapi BOM brings an old version of the Spring Framework 6.0, which is incompatible with Spring Boot 3.2. There are several ways to solve this problem: update springdoc, change the order of BOM imports, but the best, in my opinion, is to avoid using the io.spring.dependency-management plugin.

I would suggest using Springdoc

The SpringDoc library comes with lots of annotations to tune your REST API specification precisely. Anyway, that's out of context of this article.

I found SpringDoc, a library that automates the generation of the spec from the source code. It relies on annotations for textual bits (like tags and descriptions), but it also infers stuff from Spring annotations.

This is an API made with Spring Web, uses springdoc-openapi-ui to expose a swagger-ui on http://localhost:8080/swagger-ui/index.html

Libraries like Springdoc or Springfox can do this. These libraries generate the OpenAPI documentation based on your controllers (+ you can apply the OpenAPI annotations on your controllers). This documentation is then exposed as a REST API, for Springdoc these can be found at /v3/api-docs.

Retrieving all endpoints of a service isn't the goal of a service registry like Eureka, so no, you can't get all endpoints of a service. You can use a library like Springfox or Springdoc to enable Swagger/OpenAPI for your project. These libraries generate a JSON REST API (and a user interface) to view all your endpoints. You can even provide additional information (eg. default values, descriptions, ...) by adding some additional annotations on your controllers.

The springdoc-openapi helps automating the generation of API documentation using Spring Boot projects GitHub - springdoc/springdoc-openapi

Our microservice accept http requests: For swagger used Swagger OpenAPI 3. The bank account REST controller, which accept requests, validate it using Hibernate Validator, then call command or query service. The main reason for CQRS gaining popularity is the ability to handle reads and writes separately due to severe differences in optimization techniques for those much more distinct operations.

SQL (Structured Query Language) databases are relational databases. They organize data into tables with rows and columns, and they use SQL for querying and managing data. Examples include MySQL, PostgreSQL, and SQLite.

Node.js, MySQL and PostgreSQL servers installed on your machine

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

I've used MySQL for years. But recently, I found myself working PostgreSQL and simple things like dumping and restoring a database are different enough that I decided to document the process. It's straightforward enough once I knew how.

A running Rails application needs a database to connect to. You may already have your database of choice installed, but if not, I recommend PostgreSQL, or Postgres for short. On a Mac, probably the easiest way to install it is with Posrgres.app. Another option, the one I prefer, is to use Homebrew. With Homebrew installed, this command will install PostgreSQL version 16 along with libpq:

PostgreSQL

PostgreSQL: Offers a robust feature set and strong compliance with SQL standards, making it suitable for a wide range of applications, from simple to complex, particularly where data integrity and extensibility are key.

FerretDB is an open source document database that adds MongoDB compatibility to other database backends, such as Postgres and SQLite. By using FerretDB, developers can access familiar MongoDB features and tools using the same syntax and commands for many of their use cases.

To better understand how SQL injection works, let's quickly create a vulnerable app using Node.js, Express, and a PostgreSQL database. The application takes user input from a form, constructs a SQL query, and executes it against the database to fetch some data.

We'll use PostgreSQL, and first of all, you need to install PostgreSQL if you haven't installed it yet. https://www.postgresql.org/