jwt-go VS Grafana

My only suggestion, because I haven't seen anyone else mention it, is researching your dependencies. In the app you're using https://github.com/dgrijalva/jwt-go, which isn't maintained anymore and in their repo they state that you should use https://github.com/golang-jwt/jwt instead.

There are so many tools created tools using golang like the gh-cli, cockrach-db, jwt, etc. You can see a whole list of applications/tools/frameworks written in Go from this awesome list

If it is using "github.com/golang-jwt/jwt" under the hood than all you have to do is override the Valid() method on your claims object.

The code logic is query user record from database by input parameter username, if not found, return Incorrect username or password error, if password was correct, issue token. The jwt library used here is golang-jwt/jwt

Abandon https://github.com/dgrijalva/jwt-go library due security issues. Now I use https://github.com/golang-jwt/jwt#jwt-go

Use jwt (jwt.io, https://github.com/golang-jwt/jwt) shoveling the params into a MapClaims.

Go JWT Implementation Link

The boilerplate application uses the dgrijalva / jwt-go library to work with JWTs. Besides the standard set of claims fields, this library allows you to describe additional fields. In the application, this makes it possible to write to the token the ID of the user to whom it was issued. The library supports the NewWithClaims () and Parse () functions used in the AuthHandler application to create and validate tokens. Also, the Echo framework has a JWT middleware that uses the specified library to validate tokens. This middleware is hooked up in the ConfigureRoutes () function of the template application that declares the routing.

There might be many different packages, but I think this one is the most popular: https://github.com/dgrijalva/jwt-go. So let’s copy its URL, and run go get in the terminal to install the package:

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.