jwt VS Grafana

To add JWT authentication to our ToDo application, we'll be using the Golang-jwt library. The golang-jwt package simplifies the implementation of JWTs in Go applications, offering a suite of convenient functions that abstract away the complexities associated with token creation, verification, and management.

golang-jwt/jwt - GitHub

To create a secure Role-based authentication scheme, we need to generate a unique token when the user authenticates. This is then used to track their assigned role as they consume the availed resources. In this project we are going to use the jwt-go package to generate a JWT token that will encapsulate the user details, assigned role and permissions.

Yes. Currently maintained version is here: https://github.com/golang-jwt/jwt

Libraries used bcrypt: https://pkg.go.dev/golang.org/x/crypto/bcrypt golang-jwt: https://github.com/golang-jwt/jwt Gin (Http framework): https://github.com/gin-gonic/gin

We will implement Golang JWT authentication using a go-jwt package.

Authorization jwt

At least template-wise, I've developed pongo2 mimicking Django's template engine which I use myself for various projects. For the rest I usually stick with the standard library (net/http), golang-jwt, the Gorilla toolkit (note that it's been archived recently) and some software architecture patterns for middlewares, database abstraction, etc.

Either way, you will need to validate the signature of the JWT. You can do this with the public key and a library such as https://github.com/golang-jwt/jwt.

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.