workerd VS helm

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.

Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.

helm

Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...

Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.

Helm (Get from here https://helm.sh/)

It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.

Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!

Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.

We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).

Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.

Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.