springdoc-openapi VS Grafana

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.

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.