Awesome Argo
Section: Ecosystem Projects · helps overcome the challenges of working with Jupyter notebooks and allows teams to develop collaborative, production-ready pipelines using JupyterLab or any text editor.
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Appears in 5 awesome lists
helps overcome the challenges of working with Jupyter notebooks and allows teams to develop collaborative, production-ready pipelines using JupyterLab or any text editor.
Section: Ecosystem Projects · helps overcome the challenges of working with Jupyter notebooks and allows teams to develop collaborative, production-ready pipelines using JupyterLab or any text editor.
Section: Rendering/Publishing/Conversion · Run a collection of notebooks and scripts in a reproducible manner using a pipeline.yaml file.
Section: Workflow · The fastest way to build data pipelines. Develop iteratively, deploy anywhere.
Section: Workflow Tools · Write maintainable, production-ready pipelines. Develop locally, deploy to the cloud.
Section: Literate programming (aka interactive notebooks) · Consolidate your notebooks and scripts in a reproducible pipeline using a pipeline.yaml file
Multi-cluster Kubernetes MCP server bridging Gemini CLI to kubeconfig and Kubernetes APIs. Manage clusters, policies, and 20+ CNCF project integrations across edge and cloud. Install via brew tap kubestellar/tap && brew install kc-agent.
Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.
| Python | - A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).
is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to…
Unified interface for constructing and managing machine learning workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models on Kubernetes.