{"data":{"slug":"argoproj-argo-workflows","name":"argo-workflows","tagline":"Workflow Engine for Kubernetes","github_url":"https://github.com/argoproj/argo-workflows","owner":"argoproj","repo":"argo-workflows","owner_avatar_url":"https://avatars.githubusercontent.com/u/30269780?v=4","primary_language":"Go","stars":16820,"forks":3566,"topics":["airflow","argo","argo-workflows","batch-processing","cloud-native","cncf","dag","data-engineering","gitops","hacktoberfest","k8s","knative","kubernetes","machine-learning","mlops","pipelines","workflow","workflow-engine"],"archived":false,"github_pushed_at":"2026-07-10T09:15:02+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/argoproj-argo-workflows","markdown_url":"https://www.graphcanon.com/tools/argoproj-argo-workflows.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/argoproj-argo-workflows","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=argoproj-argo-workflows","description":"Workflow Engine for Kubernetes","homepage_url":"https://argo-workflows.readthedocs.io/","license":"Apache-2.0","open_issues":1450,"watchers":199,"ai_summary":null,"readme_excerpt":"## What is Argo Workflows?\n\nArgo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes.\nArgo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).\n\n* Define workflows where each step is a container.\n* Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG).\n* Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes.\n\nArgo is a [Cloud Native Computing Foundation (CNCF)](https://cncf.io/) graduated project.\n\n## Use Cases\n\n* [Machine Learning pipelines](https://argo-workflows.readthedocs.io/en/latest/use-cases/machine-learning/)\n* [Data and batch processing](https://argo-workflows.readthedocs.io/en/latest/use-cases/data-processing/)\n* [Infrastructure automation](https://argo-workflows.readthedocs.io/en/latest/use-cases/infrastructure-automation/)\n* [CI/CD](https://argo-workflows.readthedocs.io/en/latest/use-cases/ci-cd/)\n* [Other use cases](https://argo-workflows.readthedocs.io/en/latest/use-cases/other/)\n\n## Why Argo Workflows?\n\n* Argo Workflows is the most popular workflow execution engine for Kubernetes.\n* Light-weight, scalable, and easier to use.\n    * Including for Python users through [the Hera Python SDK for Argo Workflows](https://hera.readthedocs.io/en/stable/).\n* Designed from the ground up for containers without the overhead and limitations of legacy VM and server-based environments.\n* Cloud agnostic and can run on any Kubernetes cluster.\n\n[Read what people said in our latest survey](https://blog.argoproj.io/argo-workflows-events-2023-user-survey-results-82c53bc30543)\n\n## Try Argo Workflows\n\nYou can try Argo Workflows via one of the following:\n\n1. [Interactive Training Material](https://killercoda.com/argoproj/course/argo-workflows/)\n1. [Access the demo environment](https://workflows.apps.argoproj.io/workflows/argo)\n\n\n\n## Who uses Argo Workflows?\n\n[About 200+ organizations are officially using Argo Workflows](USERS.md)\n\n## Ecosystem\n\nJust some of the projects that use or rely on Argo Workflows (complete list [here](https://github.com/akuity/awesome-argo#ecosystem-projects)):\n\n* [Argo Events](https://github.com/argoproj/argo-events)\n* [Hera](https://github.com/argoproj-labs/hera)\n* [Katib](https://github.com/kubeflow/katib)\n* [Kedro](https://kedro.readthedocs.io/en/stable/)\n* [Kubeflow Pipelines](https://github.com/kubeflow/pipelines)\n* [Netflix Metaflow](https://metaflow.org)\n* [Piper](https://github.com/quickube/piper)\n* [Seldon](https://github.com/SeldonIO/seldon-core)\n* [SQLFlow](https://github.com/sql-machine-learning/sqlflow)\n\n## Client Libraries\n\nCheck out our [Java, Golang, Python (Hera), and Typescript (Juno) clients](docs/client-libraries.md).\n\n## Quickstart\n\n* [Get started here](https://argo-workflows.readthedocs.io/en/latest/quick-start/)\n* [Walk-through examples](https://argo-workflows.readthedocs.io/en/latest/walk-through/)\n\n## Documentation\n\n[View the docs](https://argo-workflows.readthedocs.io/en/latest/)\n\n## Features\n\nAn incomplete list of features Argo Workflows provides:\n\n* UI to visualize and manage Workflows\n* Artifact support (S3, Artifactory, Alibaba Cloud OSS, Azure Blob Storage, HTTP, Git, GCS, raw, plugins)\n* Workflow templating to store commonly used Workflows in the cluster\n* Archiving Workflows after executing for later access\n* Scheduled workflows using cron\n* Server interface with REST API (HTTP and GRPC)\n* DAG or Steps based declaration of workflows\n* Step level input & outputs (artifacts/parameters)\n* Loops\n* Parameterization\n* Conditionals\n* Timeouts (step & workflow level)\n* Retry (step & workflow level)\n* Resubmit (memoized)\n* Suspend & Resume\n* Cancellation\n* K8s resource orchestration\n* Exit Hooks (notifications, cleanup)\n* Garbage collection of completed workflow\n* Scheduling (affinity/tolerations/node selectors)\n* Volumes (ephemeral/existing)\n* Parallelism li","github_created_at":"2017-08-21T18:50:44+00:00","created_at":"2026-07-11T23:30:03.760746+00:00","updated_at":"2026-07-11T23:30:21.236364+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"argo-workflows","name":"argo-workflows"},{"slug":"dag","name":"dag"},{"slug":"batch-processing","name":"batch-processing"},{"slug":"data-engineering","name":"data-engineering"},{"slug":"cloud-native","name":"cloud-native"},{"slug":"airflow","name":"airflow"},{"slug":"cncf","name":"cncf"},{"slug":"argo","name":"argo"}],"trust":{"provenance":{"is_fork":false,"github_id":100982449,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:30:05.852Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":6,"days_since_push":1,"last_release_at":"2026-07-07T11:15:44Z"},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:30:06.346Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:30:05.507Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-07-11T23:30:05.507Z","managed_saas":false},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-07-11T23:30:05.507Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-07-11T23:30:05.507Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T23:30:05.507Z"}}}}