ExpansionCards VS orchest

I think the SD module won't be able to have the card flush, as the modules are only and SD cards are 32mm long, and you need some PCB space for the socket cage and the USB-C on the other side. The retrofit PCB outline they provide is only 26.9mm from front edge to back edge, so an SD card will stick out a little bit.

So perhaps they decided to go for the one that lets users have the card flush for use like an expansion bay as well as for data transfer to/from devices.

https://github.com/FrameworkComputer/ExpansionCards/tree/mai...

There are many laptops and desktops that fit the bill.

Frame.work: https://frame.work/

Dell: https://www.dell.com/support/kbdoc/en-us/000138246/linux-on-...

System76: https://system76.com/laptops

Kubuntu Focus: https://kfocus.org/land/business

I am sure there are more, this is only what I have found in less than 5 minutes of searching.

I'll buy a frame.work long before I touch system76. Their prices are too high for the general feedback I keep seeing on the quality control. I'm not spending 3k+ to be out a laptop until support responds. Especially, considering they still don't make these in house..

No they didn't, companies just mostly gave up on it.

A Framework Laptop (https://frame.work)

You could get a Framework 13 which comes with your choice of a 7840U or 7640U and a Radeon 780M iGPU. They do officially support Linux, and you don't have to pay for a Windows license, if you go the DIY option and chose to not get a Windows license.

Take a look at the Framework laptops. They're 100% modular so if stuff like that goes bad you can simply order the replacement part and do it yourself. I'm using a desktop right now but Ithink my next laptop is gonna be a framework.

a couple of days ago I tried to order a Framework laptop (13 inch AMD). I chose to create an account during the checkout process and provided my email address. After entering my shipping details, I authorized the transfer of the deposit fee via Giropay. The deposit was deducted from my bank account but when I was sent back to the frame.work website I was greeted by an error message. Unfortunately I could neither complete the checkout process nor continue my account registration.

You can check out our OSS https://github.com/orchest/orchest

The code example is part of our ELT/data pipeline tool called Orchest: https://github.com/orchest/orchest/

First want to say congrats to the Patterns team for creating a gorgeous looking tool. Very minimal and approachable. Massive kudos!

Disclaimer: we're building something very similar and I'm curious about a couple of things.

One of the questions our users have asked us often is how to minimize the dependence on "product specific" components/nodes/steps. For example, if you write CI for GitHub Actions you may use a bunch of GitHub Action references.

Looking at the `graph.yml` in some of the examples you shared you use a similar approach (e.g. patterns/openai-completion@v4). That means that whenever you depend on such components your automation/data pipeline becomes more tied to the specific tool (GitHub Actions/Patterns), effectively locking in users.

How are you helping users feel comfortable with that problem (I don't want to invest in something that's not portable)? It's something we've struggled with ourselves as we're expanding the "out of the box" capabilities you get.

Furthermore, would have loved to see this as an open source project. But I guess the second best thing to open source is some open source contributions and `dcp` and `common-model` look quite interesting!

For those who are curious, I'm one of the authors of https://github.com/orchest/orchest

Haven't tried it. In its favor, Argo is vendor neutral and is really easy to set up in a local k8s environment like docker for desktop or minikube. If you already use k8s for configuration, service discovery, secret management, etc, it's dead simple to set up and use (avoiding configuration having to learn a whole new workflow configuration language in addition to k8s). The big downside is that it doesn't have a visual DAG editor (although that might be a positive for engineers having to fix workflows written by non-programmers), but the relatively bare-metal nature of Argo means that it's fairly easy to use it as an underlying engine for a more opinionated or lower-code framework (orchest is a notable one out now).

If you’d like to try something for you data workflows that’s vendor agnostic (k8s based) and open source you can check out our project: https://github.com/orchest/orchest

You can find it here: https://github.com/orchest/orchest Convenience install script: https://github.com/orchest/orchest#installation

We automatically provide container level parallelism in Orchest: https://github.com/orchest/orchest

For people in this thread interested in what this tool is an alternative to: Airflow, Luigi, Kubeflow, Kedro, Flyte, Metaflow, Sagemaker Pipelines, GCP Vertex Workbench, Azure Data Factory, Azure ML, Dagster, DVC, ClearML, Prefect, Pachyderm, and Orchest.

Disclaimer: author of Orchest https://github.com/orchest/orchest