aid: argo-workflows
name: Argo Workflows
description: Argo Workflows is an open-source, container-native workflow engine for orchestrating parallel jobs on Kubernetes.
  It is a CNCF graduated project that allows you to define workflows where each step is a container, model multi-step workflows
  as sequences of tasks or DAGs, and run compute-intensive jobs for machine learning, data processing, and CI/CD pipelines
  natively on Kubernetes. Governed by the Linux Foundation and the CNCF.
type: Index
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
- CNCF
- Containers
- Data Processing
- Kubernetes
- Machine Learning
- Open Source
- Workflow Engine
url: https://raw.githubusercontent.com/api-evangelist/argo-workflows/refs/heads/main/apis.yml
created: '2026-03-27'
modified: '2026-05-19'
specificationVersion: '0.19'
apis:
- aid: argo-workflows:argo-workflows
  name: Argo Workflows API
  description: The Argo Workflows REST API provides programmatic access to workflow lifecycle management, workflow templates,
    cron scheduling, archived workflow history, events, and cluster workflow templates. Authentication uses JWT bearer tokens
    from service account secrets.
  humanURL: https://argo-workflows.readthedocs.io/en/latest/swagger/
  tags:
  - Kubernetes
  - REST API
  - Workflow Engine
  properties:
  - type: Documentation
    url: https://argo-workflows.readthedocs.io/en/latest/
  - type: OpenAPI
    url: openapi/argo-workflows-openapi.json
  - type: GettingStarted
    url: https://argo-workflows.readthedocs.io/en/latest/quick-start/
  - type: APIReference
    url: https://argo-workflows.readthedocs.io/en/latest/swagger/
  - type: Authentication
    url: https://argo-workflows.readthedocs.io/en/latest/access-token/
  - type: NaftikoCapability
    url: capabilities/argo-workflows-archivedworkflowservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-artifactservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-clusterworkflowtemplateservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-cronworkflowservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-eventservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-eventsourceservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-infoservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-sensorservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-syncservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-workflowservice.yaml
  - type: NaftikoCapability
    url: capabilities/argo-workflows-workflowtemplateservice.yaml
common:
- type: LinkedIn
  url: https://www.linkedin.com/company/argoproj
- type: Website
  url: https://argoproj.github.io/workflows/
- type: Documentation
  url: https://argo-workflows.readthedocs.io/en/latest/
- type: GettingStarted
  url: https://argo-workflows.readthedocs.io/en/latest/quick-start/
- type: GitHubOrganization
  url: https://github.com/argoproj
- type: GitHubRepository
  url: https://github.com/argoproj/argo-workflows
- type: ReleaseNotes
  url: https://github.com/argoproj/argo-workflows/releases
- type: ChangeLog
  url: https://argo-workflows.readthedocs.io/en/latest/new-features/
- type: CLI
  url: https://argo-workflows.readthedocs.io/en/latest/cli/
- type: SDK
  url: https://hera.readthedocs.io/en/stable/
- type: Support
  url: https://github.com/argoproj/argo-workflows/issues
- type: SpectralRules
  url: rules/argo-workflows-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/argo-workflows-vocabulary.yaml
- type: Features
  data:
  - name: Container-Native Workflows
    description: Every workflow step runs as a Kubernetes container, providing complete isolation and reproducibility.
  - name: DAG and Step-Based Orchestration
    description: Define multi-step workflows as sequential steps or directed acyclic graphs (DAGs) with dependencies.
  - name: Parallel Execution
    description: Run multiple workflow steps in parallel to maximize compute utilization and reduce execution time.
  - name: Workflow Templates
    description: Store and reuse workflow definitions as templates across the cluster.
  - name: Cron Workflows
    description: Schedule workflows to run on cron schedules directly on Kubernetes.
  - name: Artifact Support
    description: Pass artifacts between workflow steps via S3, GCS, Azure Blob, Artifactory, and more.
  - name: Workflow Archive
    description: Persist workflow history to a database for long-term retention and querying.
  - name: Web UI
    description: Monitor and manage workflows through a rich graphical interface.
  - name: Multi-Tenancy
    description: Namespace-based isolation with RBAC for multi-team environments.
  - name: Event-Driven Triggers
    description: Trigger workflows from Kubernetes events, webhooks, and custom event sources.
  - name: Python SDK (Hera)
    description: Define workflows in Python using the Hera SDK, the official Python SDK.
  - name: Plugin Architecture
    description: Extend with custom executor plugins and artifact driver plugins.
- type: UseCases
  data:
  - name: Machine Learning Pipelines
    description: Orchestrate data preparation, model training, evaluation, and deployment as containerized steps.
  - name: Data Processing and ETL
    description: Run parallel data transformation and ETL jobs at scale on Kubernetes.
  - name: CI/CD on Kubernetes
    description: Run CI/CD pipelines natively on Kubernetes without external CI tools.
  - name: Batch Processing
    description: Process large datasets in parallel with automatic resource management.
  - name: Infrastructure Automation
    description: Automate infrastructure provisioning, testing, and validation workflows.
  - name: Scientific Computing
    description: Orchestrate complex scientific computation and simulation jobs with dependencies.
- type: Integrations
  data:
  - name: Python Hera SDK
    description: Official Python SDK for defining and submitting workflows programmatically.
  - name: Argo CD
    description: Use Argo CD to deploy and manage Argo Workflows resources via GitOps.
  - name: Prometheus
    description: Expose workflow metrics for Prometheus monitoring and alerting.
  - name: Grafana
    description: Visualize workflow performance metrics in Grafana dashboards.
  - name: HashiCorp Vault
    description: Inject secrets into workflow containers securely via Vault integration.
  - name: Amazon S3
    description: Use S3 as artifact storage for passing data between workflow steps.
  - name: Google GCS
    description: Use Google Cloud Storage as artifact backend.
  - name: Azure Blob Storage
    description: Use Azure Blob Storage for artifact persistence.
  - name: Kubeflow
    description: Run Kubeflow ML pipelines using Argo Workflows as the underlying engine.
  - name: Apache Spark
    description: Orchestrate Apache Spark jobs as Argo Workflow steps.
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com