Declarative Orchestration with Kestra
Bring Infrastructure as Code Best Practices to All Workflows
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.
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.
