workerd VS go

Standards bodies only standardize things after they've been proven to work. You can't standardize a new idea before offering it to the market. It's hard enough to get just one vendor to experiment with an idea (it literally took me years to convince everyone inside Cloudflare that we should build Durable Objects). Getting N competing vendors to agree on it -- before anything has been proven in the market -- is simply not possible.

But the Durable Objects API is not complicated and there's nothing stopping competing platforms from building a compatible product if they want. Much of the implementation is open source, even. In fact, if you build an app on DO but decide you don't want to host it on Cloudflare, you can self-host it on workerd:

https://github.com/cloudflare/workerd

In any case, I welcome this initiative with my open hands and look forward all the cool apps that people will now build with this!

[1] https://pyodide.org/

[2] https://github.com/cloudflare/workerd/blob/main/docs/pyodide...

[3] https://github.com/cloudflare/workerd/pull/1875

For ref:

- https://blog.cloudflare.com/workerd-open-source-workers-runt...

- https://github.com/cloudflare/workerd

workerd

I think this is for people who want to run their own cloudflare workers (sort of) and since nobody wants to run full node for that, they want a small runtime that just executes js/wasm in an isolated way. But I wonder why they don't tell me how I can be sure that this is safe or how it's safe. Surely I can't just trust them and it explicitly mentions that it still has file IO so clearly there is still work I need to do customize the isolation further. But then they don't show any info on that core usecase. But then that's probably because they don't really want you to use this to run it on your own, they are selling you on running things on their edge platform called "Wasmer Edge". So that's probably why this is so light on information.. the motivation isn't to get you to use this yourself, just to use this their hosted edge platform. But then I wonder why I wouldn't just use https://github.com/cloudflare/workerd which is also open source. Surely that is fast enough? If not then it should show some benchmarks?

i love how the main reference for workerd can be just one capnp file.

https://github.com/cloudflare/workerd/blob/main/src/workerd/...

this changed my world how i think about computing on the web.

if there was just a good enough js library as for lua and you could directly send capnp messages to workerd instead of always going through files. I guess one day i have to relearn c++ and understand how the internals actually work.

A significant chunk of it is open source: https://github.com/cloudflare/workerd/

Some of the configuration files for applications wind up being an entire language unto themselves, e.g., https://github.com/cloudflare/workerd/blob/1b5057f2bfcfedf146f6f79ff04e99903d55412b/src/workerd/io/compatibility-date.capnp

Edge runtimes are very good alternatives to containers that shouldn't be dismissed for "not being containers". They're often faster, more scalable, and cheaper than containers. Them being so lightweight also enable a "nanoservice architecture" – being able to run every service on a single computer instead of running different services on different computers and having to deal with network latency and unreliability.

The description indicates it is not production ready, and is archived at the same time.

If you pull all stops in each respective language, C# will always end up winning at parsing text as it offers C structs, pointers, zero-cost interop, Rust-style struct generics, cross-platform SIMD API and simply has better compiler. You can win back some performance in Go by writing hot parts in Go's ASM dialect at much greater effort for a specific platform.

For example, Go has to resort to this https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f... in order to efficiently scan memory, while in C# you write the following once and it compiles to all supported ISAs with their respective SIMD instructions for a given vector width: https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (there is a lot of code because C# covers much wider range of scenarios and does not accept sacrificing performance in odd lengths and edge cases, which Go does).

Another example is computing CRC32: you have to write ASM for Go https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f..., in C# you simply write standard vectorized routine once https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (its codegen is competitive with hand-intrinsified C++ code).

There is a lot more of this. Performance and low-level primitives to achieve it have been an area of focus of .NET for a long time, so it is disheartening to see one tenth of effort in Go to receive so much spotlight.

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/.