Workflow orchestration · Kestra Technologies

Kestra

Open-source, event-driven orchestration platform defining workflows declaratively in YAML, with 800+ plugins for data, infra, and AI tasks.

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Kestra is an open-source orchestration platform that defines workflows (called 'flows') declaratively in YAML rather than in a general-purpose programming language, which lowers the barrier for non-Python users while still allowing embedded scripts (Python, Shell, Node.js) inside a flow. It is built around event-driven triggers as a first-class concept, alongside traditional cron scheduling, so flows can react to files landing, messages arriving, or API calls, not only fixed schedules. Kestra ships with a large plugin catalog (800+) covering data warehouses, cloud infrastructure, CI/CD, and AI/agentic tasks, plus a built-in code and no-code editor and a namespace-based multi-tenancy model. The open-source edition runs unlimited flows and executions for free; Kestra Cloud is a managed, usage-based SaaS, and Enterprise Edition adds SSO/LDAP, worker groups, and audit logging under an annual subscription.

At a glance

Vendor Kestra Technologies
Pricing model Free tier + paid plans
Free tier Yes
Deployment Cloud, Self-hosted
Open source Yes (Apache-2.0)
Best for Teams wanting event-driven, declarative orchestration accessible to both engineers and non-Python users.

Pricing

The open-source edition is free with unlimited flows; Kestra Cloud is usage-based, and Enterprise Edition is an annual custom subscription.

Plan Price Notes
Open Source Free Unlimited flows and executions, 2,000+ plugins
Kestra Cloud Pay only for what you use Managed hosting, automatic scaling, SOC2 compliant
Enterprise Edition Annual subscription, contact sales SSO/LDAP/SCIM, worker groups, audit logging, multi-tenancy

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Declarative YAML flow definitions with embedded scripting
  • Event-driven triggers alongside cron scheduling
  • 800+ plugin catalog for data, infrastructure, and AI tasks
  • Built-in code and no-code (drag-and-drop) editors
  • Namespace-based multi-tenancy
  • Version-controlled flows exportable as code
  • Agentic AI copilot for flow authoring

Integrations

Profile last reviewed September 21, 2026

Alternatives

Apache Airflow The de facto standard open-source workflow orchestrator, defining pipelines as Python DAGs of scheduled, dependent tasks. Prefect Python-native workflow orchestrator built around plain functions and dynamic flows, with a managed cloud control plane for scheduling and observability. Mage Notebook-style, open-source pipeline builder combining ingestion, transformation, and orchestration with a block-based visual editor.

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Terms to know

Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. ETL (extract, transform, load) A data integration pattern that transforms data before loading it, unlike ELT which transforms after loading. ELT (extract, load, transform) A data integration pattern that loads raw data first and transforms it afterward using the warehouse's own compute. AI copilot An AI tool embedded in a work application that assists a human with suggestions or drafts, rather than working unsupervised. Workflow orchestration Scheduling, sequencing and monitoring interdependent data tasks so each step runs only after the ones it depends on succeed.

Related guides

How to choose a workflow orchestrator Pick a workflow orchestrator by pipeline shape, who owns it, and whether you already run Kubernetes — not by the demo DAG.