Our verdict
We have not reviewed Argo Workflows yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Argo Workflows
Argo Workflows is an open-source workflow engine for Kubernetes that orchestrates multi-step jobs using YAML-defined DAGs (directed acyclic graphs). It runs natively on Kubernetes clusters and provides visibility into job execution, resource usage, and failure states through a web UI.
Best for
Teams running workloads on Kubernetes who need declarative, auditable job orchestration without external services
Use cases
- Orchestrating multi-stage ML training and inference pipelines
- Coordinating parallel batch processing jobs across Kubernetes nodes
- Building CI/CD workflows with complex dependencies and conditional logic
Notes
16,728 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
Pros
- Native Kubernetes integration eliminates external infrastructure
- YAML-based workflow definitions enable version control and GitOps practices
- Handles complex DAGs with parallelization, retries, and conditional branching
Cons
- Requires Kubernetes cluster to run, adding operational overhead for small teams
- Learning curve for YAML syntax and Kubernetes-specific concepts
- Debugging failed workflows requires familiarity with Kubernetes logs and events
Key facts
What we have checked
- Latest version
- 4.0.15 (released 22 Oct 2026)
- GitHub stars
- 17,004
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Argo Workflows is growing
16,728 to 17,004
Alternatives
Alternatives to Argo Workflows
| Record | Type | How we know | Checked |
|---|---|---|---|
| AirflowAlternative to this | Open source | Named in the listing | Not dated |
| aqueductAlternative to this | Open source | Named in the listing | Not dated |
| FlyteAlternative to this | Open source | Named in the listing | Not dated |
| HamiltonAlternative to this | Open source | Named in the listing | Not dated |
| MetaflowAlternative to this | Open source | Named in the listing | Not dated |
| PAIAlternative to this | Open source | Named in the listing | Not dated |
| PolyaxonAlternative to this | Open source | Named in the listing | Not dated |
| PrefectAlternative to this | Open source | Named in the listing | Not dated |
| PrimehubAlternative to this | Open source | Named in the listing | Not dated |
| VDPAlternative to this | Open source | Named in the listing | Not dated |
Compare
Compare Argo Workflows side by side
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 4.0.15
Released 4.1.6
Released 4.0.14
Released 4.1.5
Released 4.0.13
Released 4.1.4
Released 4.0.12
Released 4.1.3
Released 4.0.11
Released 4.1.2
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Airflow
Community
Platform created by the community to programmatically author, schedule and monitor workflows.
aqueduct
Community
Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure.
Flyte
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Dynamic, resilient AI orchestration. Coordinate data, models, and compute as you build AI workflows.
Hamilton
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Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere pytho
Metaflow
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Build, Manage and Deploy AI/ML Systems
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Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
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VDP
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🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications
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