Orchest
Visual pipeline editor and workflow orchestrator based on Kubernetes.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Orchest?
Orchest is a visual pipeline editor and workflow orchestrator that provides an easy-to-use UI for managing machine learning workflows, built on top of Kubernetes. It simplifies the process of creating, deploying, and monitoring ML pipelines without deep knowledge of Kubernetes.
Key differentiator
“Orchest stands out by providing a visual interface for managing ML workflows on Kubernetes, making it accessible to users without deep Kubernetes expertise while still leveraging the power of Kubernetes for orchestration.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development and community support focus on Python, with minimal support for other languages
Documentation assumes familiarity with Kubernetes concepts; non-trivial to set up without prior experience
Fit analysis
Who is it for?
✓ Best for
Teams that need a user-friendly interface for managing complex machine learning workflows on Kubernetes.
Developers who want to avoid the complexity of manual Kubernetes setup while deploying ML pipelines.
✕ Not a fit for
Projects requiring real-time data processing and streaming, as Orchest focuses more on batch processing.
Teams with limited computational resources, as it requires a Kubernetes cluster for deployment.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with Orchest
Step-by-step setup guide with code examples and common gotchas.