k0s VS go

I am myself studying it and going through the official documentation and toying with k8s flavors like kind, k3s and k0s.

There's a whole community of hobbyists building Raspberry Pi clusters, porting things to work on various Arm processors, exploring and contributing to minimalist distros like k0s and microk8s, etc.

root@localhost:~# curl -sSLf https://get.k0s.sh | sudo sh Downloading k0s from URL: https://github.com/k0sproject/k0s/releases/download/v1.25.4+k0s.0/k0s-v1.25.4+k0s.0-amd64 k0s is now executable in /usr/local/bin root@localhost:~# k0s install controller --single root@localhost:~# k0s start root@localhost:~# k0s status Version: v1.25.4+k0s.0 Process ID: 1064 Role: controller Workloads: true SingleNode: true Kube-api probing successful: true Kube-api probing last error: root@localhost:~# k0s kubectl cluster-info Kubernetes control plane is running at https://localhost:6443 CoreDNS is running at https://localhost:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'. 443/TCP 97s root@localhost:~# k0s kubectl get nodes -o wide NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME localhost Ready control-plane 100s v1.25.4+k0s 172.105.131.23 Ubuntu 22.04.1 LTS 5.15.0-47-generic containerd://1.6.9 root@localhost:~# curl -LO https://storage.googleapis.com/kubernetes-release/release/v1.25.4/bin/linux/amd64/kubectl && chmod +x kubectl && mv kubectl /usr/bin/ % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 42.9M 100 42.9M 0 0 75.2M 0 --:--:-- --:--:-- --:--:-- 75.3M root@localhost:~# k0s kubeconfig admin > ~/.kube/config root@localhost:~# type kubectl kubectl is hashed (/usr/bin/kubectl) root@localhost:~# kubectl get po,svc -A NAMESPACE NAME READY STATUS RESTARTS AGE kube-system pod/kube-proxy-clxh7 1/1 Running 0 3m56s kube-system pod/kube-router-88x25 1/1 Running 0 3m56s kube-system pod/coredns-5d5b5b96f9-4xzsl 1/1 Running 0 4m3s kube-system pod/metrics-server-69d9d66ff8-fxrt7 1/1 Running 0 4m2s NAMESPACE NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE default service/kubernetes ClusterIP 10.96.0.1 443/TCP 4m20s kube-system service/kube-dns ClusterIP 10.96.0.10 53/UDP,53/TCP,9153/TCP 4m8s kube-system service/metrics-server ClusterIP 10.98.18.100 443/TCP 4m2s

I use k0s btw ,and it is fantastic.

Here is link number 1 - Previous text "k0s"

So for example, in my own personal infra repos and for projects I do, Make orchestrates Pulumi, dnscontrol (Holy shit is that tool underrated), ansible, k0s/k0sctl (I run that distro), and all the kubernetes stuff.

I wasn’t able to run Kubernetes in NAS last time I tried it. https://github.com/k0sproject/k0s/issues/1184. As for public access you don’t want to do it for security reasons and instead rely on vpn. Tailscale and ZeroTier are easy to setup.

I prefer k0s, https://k0sproject.io/ .

actually that is not really true - i strongly urge you to try out http://k3s.io/ or https://k0sproject.io/

these are full-fledged, certified k8s distributions that run on raspberry pi as well as all the way in production.

https://www.youtube.com/results?search_query=raspberry+pi+k3...

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/.