wolfv/dask-gateway-feedstock — explained in plain English
Analysis updated 2026-07-18 · repo last pushed 2025-05-03
Install Dask Gateway with a simple conda install command instead of building it from source.
Automatically rebuild and test new versions of Dask Gateway across Linux and macOS when maintainers push updates.
Reference the recipe to see how Dask Gateway variants for Kerberos, local, or Kubernetes backends are packaged.
Deploy Dask Gateway in a shared research or engineering environment so multiple users can queue jobs securely.
| wolfv/dask-gateway-feedstock | 0verflowme/alarm-clock | 0verflowme/seclists | |
|---|---|---|---|
| Language | — | CSS | — |
| Last pushed | 2025-05-03 | 2022-10-03 | 2020-05-03 |
| Maintenance | Stale | Dormant | Dormant |
| Setup difficulty | hard | easy | easy |
| Complexity | 4/5 | 2/5 | 1/5 |
| Audience | ops devops | vibe coder | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires choosing the right variant for your security model (e.g. Kerberos) and backend (local, job scheduler, Kubernetes).
This repository is a packaging configuration for Dask Gateway, a tool that manages multiple Dask computing clusters securely in shared environments. Think of it like a front desk for a busy computing lab, it controls who gets access to what resources and keeps different users' work isolated from each other. The core purpose of Dask Gateway is to let teams deploy and run distributed computing jobs without stepping on each other's toes. Instead of everyone directly launching their own cluster, they request resources through the gateway server, which handles the complexity of provisioning, authentication, and cleanup. The gateway can work with different backend systems, local machines, job schedulers, or cloud platforms like Kubernetes. This specific repository isn't the gateway itself, but rather a "feedstock", a packaging recipe that tells the conda package manager how to build and distribute the gateway software. Conda is a popular tool for Python developers to install pre-compiled packages. The feedstock contains the instructions for compiling the code on different operating systems (Linux, macOS) and architecture types, along with configuration to automatically test and upload new versions. When maintainers update the gateway software, this automation rebuilds it, tests that nothing broke, and makes the new version available for anyone to install with a simple command like conda install dask-gateway. Who uses this? Data scientists and engineers working in organizations where multiple people share the same computing resources. For example, a research team running machine learning experiments on a shared cluster would use Dask Gateway to queue up their jobs fairly and securely. The repository includes variations for different security models (like Kerberos for enterprise networks) and different backend systems (local machines, job queues, or Kubernetes cloud platforms), so teams can pick the version that matches their infrastructure.
A conda packaging recipe (feedstock) that builds and distributes Dask Gateway, a tool for securely managing shared Dask computing clusters across teams.
Stale — no commits in 1-2 years (last push 2025-05-03).
License information is not specified in the explanation.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
double-check against the repo, no cap.