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Declarative Data Orchestration with Kestra

Simplified Data Workflow Creation and Execution with YAML

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Build Your Flows in YAML

Benefits of Using YAML for Declarative Orchestration

YAML is a human-readable data serialization language designed for simplicity and ease of use. By using YAML to define declarative data workflows, Kestra offers numerous benefits:

Simplified Workflow Creation

YAML syntax allows more people in the organization to collaborate on data workflows.

Reduced Maintenance Effort

Changes can be made directly within the YAML file, eliminating the need for CI/CD.

Enhanced Readability

YAML format works well with REST APIs while remaining human-readable and easy to understand.

Version Control

Track changes, collaborate on updates, and maintain a history of modifications.

Platform Agnostic

Easily switch between tools by swapping plugins in your workflow.

Reduced error rates

YAML workflow definition validates syntax during creation, ensuring correctness before execution.

Simple Yet Powerful

Kestra's declarative data orchestrator simplifies data orchestration by using YAML (Yet Another Markup Language) to define workflows. This approach simplifies the creation, execution, and maintenance of data pipelines, making them accessible to both technical and non-technical team members.

id: "each_parallel"
type: io.kestra.core.tasks.flows.EachParallel
value:
- value 1
- value 2
- value 3
tasks:
id: each-value
type: io.kestra.core.tasks.debugs.Return
format: "{{ taskrun.value }}"

Improved Workflow Flexibility

Easily adapt workflows by updating YAML; Kestra adjusts execution automatically.

Reduced Complexity

Simplifies data pipelines by eliminating intricate code, enhancing maintainability.

Enhanced Collaboration

Easy-to-read workflows for both technical and non-technical team members.

A YAML sample of code for declarative language and construction of Kestra's flows

Deep Dive into YAML's Features

  • Data Structures: YAML supports various data structures, such as mappings, sequences, and scalars, allowing for the flexible representation of complex data workflows.
  • Comments: Inline comments in YAML files facilitate better communication and documentation within data teams, ensuring clarity and understanding of workflow logic.
  • Custom Tags and Types: YAML allows for the definition of custom tags and types, enabling the creation of domain-specific languages and abstractions tailored to your data orchestration needs.

Empower Your Team with Declarative Orchestration

  • Accelerate Time to Value: Declarative orchestration modernized the creation and maintenance of data pipelines, enabling data teams to deliver results faster and more efficiently.
  • Increase Agility: By using a declarative approach, data teams can quickly adapt to changing business requirements without the need to overhaul complex procedural code.
  • Reduce Error Rates: Declarative workflows help minimize errors by allowing data teams to focus on defining the desired outcome, while Kestra's orchestrator takes care of the execution.
Image of execution of a task on Kestra with event or time based triggering
Logos of tools that integrate with Kestra such as Snowflake, Airbyte, DBT or Fivetran and Kestra at the center of It

Over 300 plugins

Plugins are at the core of Kestra's extensibility. Many plugins are available from the Kestra core team, and creating your own is easy. With plugins, you can add new functionality to Kestra.

Getting Started with Kestra's Declarative Orchestrator

Kickstart your journey with Kestra's declarative data orchestrator and unlock the full potential of your data.

Get Started with Kestra