caddy-docker VS go

The official Caddy documentation of their Docker image: https://hub.docker.com/_/caddy

I use https://static-web-server.net/

Cross-platform, written in Rust, straightforward configuration, secure defaults, also has a hardened container image and a hardened NixOS module.

I wouldn't recommend Caddy. Their official docker image runs as root unnecessarily (and the reasoning suggests a lack of understanding) [1], and they don't provide a properly sandboxed systemd unit file [2].

[1]: https://github.com/caddyserver/caddy-docker/issues/104

There is also a short section about it on the Docker hub page under the "Adding custom Caddy modules" section: https://hub.docker.com/_/caddy

Caddy uses a number of volumes. Two point directly at files within our project, first our Caddyfile, then our public folder which Caddy will serve live files. The other two are virtual filesystems Docker will create as defined by the master volumes parameters. We can assume the caddy_config volume is where active configuration is stored as it is not discussed on the Caddy Docker Official Image page, so we're copying their parameter exactly, but the caddy_data volume needs some extra discussion. It is used to store a number of things including SSL certificates. By default Docker creates and destroys volumes upon startup and exit. As we want to persist our certificate across sessions we can take advantage of an external Docker volume. These virtual filesystems are created before starting the Docker session for the first time. This can ve done from the command line or more easily from within the Docker Desktop app. Simply choose "Volumes", click the "Create" button and specify caddy_data.

I've been able to create a network with no issues (that I know of yet) but when I try to create the volumes I run into trouble. This specific example is from Caddy2...

For a reverse proxy I would suggest Caddy. The configuration is super easy and it handles SSL for you out of the box using LetsEncrypt! There’s also an official docker image like PHP and MySQL here https://hub.docker.com/_/caddy

Their image is dead simple to use, the config is fine, and auto-https is baked in. You can use it as a sidecar, proxy for multiple images, or just as a base to add your app into, depending on the complexity of your existing config.

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.