go-cloud VS go

Even when going multi-cloud you can employ different strategies. Vault is definitely one of them, but you can also use federation to exchange one cloud's credentials for another's, giving you the ability to centralize secrets in one of them. You can use a layer of abstraction like GoCloud [0]. You can also build for each cloud separately and decide either not to centralize secrets at all, or build some trivial bespoke tooling to synchronize some of them. I'm not endorsing any of the options, just pointing out that Vault isn't the only one.

https://github.com/google/go-cloud

> If Google started adding Google Cloud specific primitives natively to Go would you call that forward thinking as well?

Go actually ships with a quite forward thinking SQL interface. It's an abstract interface over a DB, and you just import the "driver" that powers it. The driver conforms to a standard interface, so all of them behave roughly the same.

I think this is what everyone wants from Deno/etc - why can't there also be a KV interface that's universal, or a Queue interface that's universal?

People attempted this w/ go [1], where it attempts to use the same nice experience of the SQL logic, but it never seemed to gain traction.

https://gocloud.dev

github.com/google/go-cloud/pubsub package provides a set of interfaces and tools to work with publish/subscribe messaging. This package allows easy communication between independent components by decoupling the sender and the receiver.

I'm guessing this is a reasonable example of what they're using it for? server.go

https://github.com/google/go-cloud probably out of context, but not IaC but agnostic backend development with Go across multiple clouds

The plan is to have a process for generating AWS CDK targeting Lambda (pluggable providers, but start with AWS CDK, because it's what I use), and to use the Google Cloud Development Kit (also called CDK, but not the same) https://github.com/google/go-cloud to abstract the services.

In this post, I will talk about an exciting project maintained by the team that develops the Go language: the Go Cloud Development Kit, also known as the Go CDK.

The API of gocloud.dev, is stable. We are at ariga.io, already use gocloud.dev for internal service, and even in the public for easy adopt multi-clouds provider: https://github.com/ariga/atlas/commit/ef0b0eae65a61375482497ceb9ed9790a469b56e

On Go, which has a community focused on the cloud, there is even GoCloud, a library with a single, common, and high-level API that allows an application to support any of those clouds and even on-premise alternatives for those services. All can be configurable at deploy time by the infrastructure team.

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/.

The Go Programming Language

When Go first shipped, it was already well-documented that the only stable ABI on some platforms was via dynamic libraries (such as libc) provided by said platforms. Go knowingly and deliberately ignored this on the assumption that they can get away with it. And then this happened:

https://github.com/golang/go/issues/16606

If that's not "getting burned", I don't know what is. "Trying to provide a nice feature" is an excuse, and it can be argued that it is a valid one, but nevertheless they knew that they were using an unstable ABI that could be pulled out from under them at any moment, and decided that it's worth the risk. I don't see what that has to do with "not being as broadly compatible as they had hoped", since it was all known well in advance.

Sadly, I think that is indeed radically different from Go’s design. Go lacks anything like sum types, and proposals to add them to the language have revealed deep issues that have stalled any development. See https://github.com/golang/go/issues/57644

I've been writing a lot about Go and gRPC lately: