validator VS Grafana

go-playground/validator

If you want to know all the available validation in Gin. Then you can look at this package because Gin uses this package under the hood. Package: https://github.com/go-playground/validator Specific-file: https://github.com/go-playground/validator/blob/master/baked_in.go#L73

Now it has most of the Playground validator's common checks and a few own tricks.

In Go I've found this package - https://github.com/go-playground/validator. It seems popular in the community, but it is tag-based. It looks like if I wanted to use it - I would have to basically duplicate structs.

so I am working on a ecommerce api as a hobby project which is mostly inspired by wtf dial project I like to use validator package to remove boilerplate over my domain package for example take a look https://github.com/mortezadadgar/ecommerce-api/blob/b0bf43d042d62fdca1c2d097ec51b05bc539cef2/domain/users.go#L33 I have to option either add validate.Struct() to my domain which is suggested to avoid by author of wtf peoject or add it to handler which I doubt is a good idea as it's not in business logic of handler and makes unit testing harder

I use https://github.com/go-playground/validator, but honestly, I am not a fan. I just haven’t found anything better.

IDE: use whatever make you productive. I personally use vscode. VCS: git, as golang communities use github heavily as base for many libraries. AFAIK Linter: use staticcheck for linting as it looks like mostly used linting tool in go, supported by many also. In Vscode it will be recommended once you install go plugin. Libraries/Framework: actually the standard libraries already included many things you need, decent enough for your day-to-day development cycles(e.g. `net/http`). But here are things for extra: - Struct fields validator: validator - Http server lib: chi router , httprouter , fasthttp (for non standard http implementations, but fast) - Web Framework: echo , gin , fiber , beego , etc - Http client lib: most already covered by stdlib(net/http), so you rarely need extra lib for this, but if you really need some are: resty - CLI: cobra - Config: godotenv , viper - DB Drivers: sqlx , postgre , sqlite , mysql - nosql: redis , mongodb , elasticsearch - ORM: gorm , entgo , sqlc(codegen) - JS Transpiler: gopherjs - GUI: fyne - grpc: grpc - logging: zerolog - test: testify , gomock , dockertest - and many others you can find here

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.

I completely agree but do feel it needs qualifying. The problems beginners run into aren't usually the same as the problems experienced devs run into when adopting a language new to them, but where I see the two overlap I know something is a serious hazard in a language.

Java as a first language: won't like the boilerplate but won't have any point of comparison anyway, will get a few NPEs, might use threads and get data races but won't experience memory unsafety.

Go as a first language: much less boilerplate, but will still get nil panics, will be encouraged to use goroutines because every tutorial shows off how "easy" they are, will get data races with full blown memory unsafety immediately.

Rust as a first language: `None` // no examples found

I think Go as a beginner language would be better if people were discouraged from using goroutines instead of actively encouraged (the myth of "CSP solves everything"), otherwise I think it needs much better tooling to save people from walking off a cliff with their goroutines. And no, -race clearly isn't it, especially not for a beginner.

And in one respect I've found Go more of a hazard for experienced devs than beginners: the function signature of append() gives you the intuition of a functional programming append that never modifies the original slice. This has literally resulted in CVEs[1] even by experienced devs, especially combined with goroutines. Beginners won't have an intuition for this and will hopefully check the documentation instead of assuming.

[1] https://github.com/grafana/grafana/security/advisories/GHSA-...