Declarative Orchestration with Kestra

Bring Infrastructure as Code Best Practices to All Workflows

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Simple Workflow Definition in YAML

YAML is a popular data serialization language designed to be easy to read and write by both humans and machines. Using YAML to declaratively define workflows brings a number of benefits.

Simple Workflow Creation

YAML is easy to learn. The simple syntax allows more people in the organization to collaborate on building workflows together.

Fewer Bugs in Production

Kestra's built-in syntax validation ensures that your YAML code is error-free before execution, reducing the risk of runtime errors in production.

Easy to Read by Humans and Machines

YAML is a superset of JSON, therefore it works extraordinaly well with REST APIs, while remaining human-readable and easy to understand.

Simple Version Control

Since you describe your workflow in a single YAML configuration, it's easy to track changes over time, collaborate on pull request reviews, and roll back when needed.

Platform Independence

Due to separation of your orchestration logic from the business logic, you don't need any modifications to your existing code to orchestrate it with Kestra.

Reduced Maintenance Effort

Need to adjust your workflow? Just edit the YAML file. No need for redeploying code and complex code packaging in CI/CD.

Simple Yet Powerful

The declarative syntax in a YAML format significantly reduces the barrier to entry. You can onboard new team members quickly, and maintain your workflows with minimal effort.

In just a few lines of YAML configuration, anyone in your team can build their first scheduled workflow. With that first success, your team members can start automating more advanced use cases with confidence.

code
id: hello_world
namespace: dev
tasks:
- id: greeting
type: io.kestra.core.tasks.log.Log
message: Hello from a declarative workflow!
triggers:
- id: schedule
type: io.kestra.core.models.triggers.types.Schedule
cron: "@hourly"

Faster Development Cycles

Easily adapt workflows by updating your declarative configuration. No need for complex CI/CD pipelines.

Reduced Complexity

Simplifies your codebase by eliminating boilerplate code. No need to write code to deploy code — each Kestra flow includes everything it needs to run.

Enhanced Collaboration

Build workflows that are easy to read and understand for both technical and non-technical team members.

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

YAML for Declarative Orchestration

  • 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.
  • Speed up your development cycles: By using a declarative approach, data teams can quickly adapt to changing business requirements without the need to overhaul complex procedural code.
  • Reduce maintenance burden: 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

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Getting Started with Declarative Orchestration

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