The Differences Between Kestra and AWS Step Functions

About Kestra & AWS Step Functions

Kestra is an open-source workflow orchestrator that applies Infrastructure as Code principles to automation workflows. Users define workflows using a YAML-based configuration while keeping everything as code—fully declarative, extensible, and API-driven. This allows for greater flexibility and seamless integration across cloud, on-prem, and hybrid environments without relying on proprietary languages.

AWS Step Functions, on the other hand, is a proprietary AWS service designed for orchestrating workflows within the AWS ecosystem. It uses Amazon States Language (ASL), a JSON-based DSL, to define workflows and provides a low-code visual editor. While it integrates deeply with AWS services, it remains tightly coupled with the AWS infrastructure and pricing model.

Installation and Setup

AWS Step Functions is a managed service, meaning there is no installation required, but it is only available within AWS. Users must configure IAM permissions, integrate with other AWS services, and deploy workflows using ASL.

Kestra, being self-hosted can be deployed with Docker, Kubernetes, or Terraform in any environment. Installation is straightforward, allowing full control over execution and data residency.

Workflow Definition

Kestra uses a simple YAML format that is easy to read and modify. It supports inline scripting in multiple languages such as Python, JavaScript, SQL, and Shell, without external dependencies.

AWS Step Functions uses ASL, a JSON-based format that is less readable and harder to manage at scale. More complex workflows require additional AWS services like Lambda for logic execution.

Kestra provides a language-agnostic approach, while AWS Step Functions locks users into ASL and AWS Lambda for advanced logic.

Orchestration Flexibility

Kestra is designed to be technology-agnostic and can orchestrate cloud, on-prem, and hybrid workflows.

AWS Step Functions is tightly integrated with AWS services but limited in multi-cloud and hybrid setups.

Kestra’s event-driven architecture allows workflows to trigger based on external APIs, message queues, or scheduled events. AWS Step Functions requires AWS-native services for triggering workflows, making external integrations more complex.

Execution, Scalability, and Performance

Kestra runs on any cloud provider, allowing users to scale workflows dynamically. It is designed for high-throughput data processing and long-running workflows.

AWS Step Functions is serverless but limited to AWS infrastructure. Workflow execution is billed per state transition, which can become costly for large-scale automation.

Kestra offers full control over execution and costs, while AWS Step Functions scales automatically but locks users into AWS pricing models.

Monitoring and Observability

Kestra comes with built-in workflow monitoring, logs, and real-time execution tracking.

AWS Step Functions relies on AWS CloudWatch for logging and monitoring, which requires additional configuration and costs.

Kestra provides out-of-the-box observability, while AWS Step Functions requires additional AWS services for logging and monitoring.

Open-Source vs. Proprietary

Kestra is fully open-source, with an active community and enterprise options for advanced needs.

AWS Step Functions is a proprietary AWS service, locking workflows within the AWS ecosystem.

Kestra allows for vendor independence, while AWS Step Functions ties users to AWS infrastructure and pricing.

Cost Considerations

Kestra is self-hosted, offering predictable costs.

AWS Step Functions uses a pay-per-state transition pricing model, making it difficult to estimate costs upfront.

Kestra provides cost-effective orchestration, while AWS Step Functions can become expensive depending on workflow complexity.