wild-workouts-go-ddd-example VS Grafana

Take a look at: https://github.com/ThreeDotsLabs/wild-workouts-go-ddd-exampl...

(I’m one of the authors.)

This project shows how to apply more complex patterns popular in business applications while staying true to the Go ideas, and not copying them blindly from Java.

In the Go community, you’ll often hear people say „just keep things simple” beats all patterns and is all you need. This may be true if you write a CLI tool or a small library, but if you have a team maintaining a big application, some patterns are super helpful.

Here is a reference implementation by the same authors of the blog post you referenced: https://github.com/ThreeDotsLabs/wild-workouts-go-ddd-example/tree/master/internal/trainer.

In this case I recommend Three Dots Labs blog and Ardan Labs courses and blog posts.

As a rather new developer, I'm ashamed to admit that I struggle with this. I've seen the Dave Cheney writeup about it and I agree with your reasoning, but sometimes I end up in situations like this, where they wrote a server utility, put it into the common package and imported it into the services that need it. The issue I have is the organization of it all because the folder structure seems to make a clear separation of the core services from the utility package. If you have any ideas or tips to help avoid it, that'd be awesome!

Clean architecture is not tied to some specific paradigm. It's a way of thinking about programs that is common to almost every mature developer. Many developers use it without even knowing the name - they just came to it by themselves through many tries and errors. There is a good free book about using it in Go, called Go with the Domain if you interested.

Wild Workouts should match your needs: https://github.com/ThreeDotsLabs/wild-workouts-go-ddd-example

For Event-Driven / DDD / Microservice projects, take a look at this Github org https://github.com/ThreeDotsLabs and their blog detailing the techniques used https://threedots.tech .

Nice job at taking a stab at DDD in Go! You may want to check out https://github.com/ThreeDotsLabs/wild-workouts-go-ddd-example for some inspiration and learning around DDD and Go.

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.