pkgsite VS Grafana

Reading the standard library will give you ideas/insight about various Go idiomatic patterns/approaches, and you can see a full website/API implementation in the pkg.go.dev repository (https://github.com/golang/pkgsite). Projects like https://github.com/etcd-io/etcd may be interesting too.

Let's look at some real codebase for an example on how to write database tests without mocking. The source code for the Go package discovery site(https://pkg.go.dev/) is available at[1] That site uses postgres as its primary database[2]. The database package has a method called GetLatestInfo[3] that fetches the latest versions of a module. That method is called from the frontend http handlers[4] via an interface[5] When it comes to testing that frontend handler, you would expect the tests to use a mock implementation of that interface method. But that's not what they do, instead they use a real postgres database in the test[6].

The code behind pkg.go.dev is also open-source and might be an interesting read.

BTW, the number of dependencies of pkgsite surprises me: https://github.com/golang/pkgsite/blob/master/go.mod

The source for Go's pkg site has been helpful to me https://github.com/golang/pkgsite

In my unpopular opinion, the go net/http is good enough to develop the web http application. The standard API is clean and well-documented. One of example is the pkgsite (https://github.com/golang/pkgsite).

It's also available as a mirror at https://github.com/golang/pkgsite. All the golang.org/x/* packages are thankfully available there, making them pretty easy to find.

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.