# argoproj/argo-workflows

Workflow Engine for Kubernetes

Repository: https://github.com/argoproj/argo-workflows
Canonical: https://ross.abutalabs.com/products/argo-workflows
Homepage: https://argo-workflows.readthedocs.io/
Language: Go
License: Apache-2.0
License Family: permissive
Topics: workflow, kubernetes, argo, dag, knative, airflow, machine-learning, argo-workflows, workflow-engine, hacktoberfest, cloud-native, cncf, k8s, gitops, mlops, batch-processing, data-engineering, pipelines
Last push: 2026-08-26T22:34:45+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 98, longevity 100
- inputs: {"age_days": 3299, "days_push": 7, "days_rel": 12, "gap_med": 7, "n_releases_24m": 58}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 16939, forks 3631 (observed 2026-08-28T04:11:17.438119+00:00)

## What it is
Argo Workflows is an open-source, container-native workflow engine for orchestrating parallel jobs on Kubernetes, implemented as a Kubernetes CRD. It lets users define multi-step workflows as sequences of tasks or DAGs where each step is a container, and is a CNCF graduated project.

## Use cases
- run machine learning pipelines on kubernetes
- orchestrate data and batch processing jobs
- automate infrastructure tasks as workflows
- build ci/cd pipelines with containers
- run parallel compute-intensive jobs on k8s
- define dag-based task dependencies in kubernetes

## When to choose
- you need to orchestrate container-based parallel jobs on Kubernetes
- you want DAG or step-sequence workflows with artifact support (S3, GCS, Git, etc.)
- you run ML pipelines or batch data processing at scale on k8s
- you want a CNCF graduated, widely adopted workflow engine with a UI and Python SDK

## When to avoid
- you are not running Kubernetes and need a VM or server-based scheduler
- you only need simple cron-style scheduling without DAG dependencies
- you need event-driven automation rather than workflow orchestration (consider Argo Events)

## Facets
- artifact type: application
- maturity: stable
- function: workflow-automation, scheduling, ci-cd, container-orchestration, etl
- domain: machine-learning, cloud-computing
- platform: cloud, self-hosted, go
- tags: workflow-engine, dag, kubernetes-crd, batch-processing, mlops, pipelines, cncf, cloud-native, devops, data-engineering, containers, automation, kubernetes, docker

## Member repositories
- argoproj/argo-workflows (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:17.438119+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:03:41.480767+00:00, confidence not recorded.
  - readme: https://github.com/argoproj/argo-workflows (fetched 2026-08-28T04:11:17.438119+00:00, sha 979d60f18a3b)
  - homepage: https://argo-workflows.readthedocs.io/ (fetched 2026-08-29T08:01:41.669814+00:00, sha 23ae3bcf5fd5)
- Data as of 2026-08-30T08:39:29.467469+00:00.