cost-model VS go

Kubecost gives you insight into where your Kubernetes spend is going. You can view your spend per namespace, service, or even team, and you can set budgets and get real-time alerts. Kubecost can also track other cloud spend from things like RDS and S3, and it also works with on-prem k8s clusters. Kubecost also offers an open source version.

kubecost - analyse cost of the cluster https://kubecost.com/

> No inheritance - no more digging through the massive world-tree of objects to find the code that actually does things.

That's not 100% accurate; as a concrete example, tell me which files (to say nothing of the actual downstream types!) contain the implementations of this interface method: https://github.com/kubecost/cost-model/blob/v1.88.0/pkg/clou... (err, without using github's fancy new SourceGraph-lite integration, of course, that'd be cheating)

I find the sibling "No declared interfaces - they are defined at the point of use, not declared elsewhere" similarly suspicious, but suspect we'd having a nomenclature mismatch

Kubecost (Stackwatch) | Senior Support Engineer | Remote (US-East/Central preferred) | https://kubecost.com

Our tooling and intelligence empowers teams to efficiently operate Kubernetes at scale—helping them manage cost, performance, and reliability. We're avid contributors to the open source community.

We're looking to add a second Senior Support Engineer to help us build a scalable, user-first support process, troubleshoot complex infrastructure issues, and influence the direction of our product by tracking and communicating user needs. Be one of our first 20 teammates!

Feel free to apply or reach out to us directly with your CV at [email protected] if you're interested!

Check out all of our open roles here: https://angel.co/company/kubecost/jobs

Kubecost (Stackwatch) | Senior Support Engineer | Remote (US-East/Central preferred) | Full time | https://kubecost.com

Stackwatch is a tight-knit, fast-growing team on the leading edge of cloud infrastructure technology. Starting with our flagship product Kubecost, we build tooling and intelligence that empowers teams to efficiently operate Kubernetes at scale—helping them manage cost, performance, and reliability.

As our second Senior Support Engineer, you’ll help us build a scalable, customer-first support process, troubleshoot complex infrastructure issues for our users, and influence the direction of our product by tracking and communicating customer needs. We’re looking for someone who is as passionate about our product and customers as we are—as one of our first 20 employees, you’ll have the opportunity to shape the future of our support organization and technology.

Feel free to reach out to us directly with your CV at [email protected] if you're interested!

NB: also hiring for Senior Software Engineers and Go-to-market!

Lens is the most powerful IDE for those who need to deal with Kubernetes clusters on a daily basis. It allows you to manage your cluster and view important health metrics. A Kubecost and Lens integration allows you to also visualize Kubernetes costs directly in the Lens UI. With Lens and Kubecost you can view costs and spend efficiency by namespace, pod, deployment and more!

First you have to be aware of your costs :) This open source project can help https://kubecost.com, `helm install` and get started in 5 minutes

Happy to share some of the lessons we've learned if you want to reach out to team [at] kubecost.com. We worked on this problem at Google before launching Kubecost open source.

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: