Java-Quarkus-Reactive-CQRS-EventSourcing VS Grafana

Source code you can find in GitHub repository. The main idea of this project is the implementation of Event Sourcing and CQRS using Java, Quarkus with reactive Vertx, Postgresql and Kafka. Previously have written same articles where implemented the same microservice using Go and EventStoreDB, and Spring,as written before, repeat here, think EventStoreDB is the best choice for event sourcing, but in real life at some projects we usually have business restrictions and for example usage of the EventStoreDB can be not allowed, in this case, think postgres and kafka is good alternative for implementing our own event store. Didn't write in this article about Event Sourcing and CQRS patterns, the best place to read is microservices.io,blog and documentation of this article is very good too, and as written in the previous article, highly recommend Alexey Zimarev "Hands-on Domain-Driven Design with .NET Core" book and also his blog.

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: