Kestra vs. AWS Step Functions: Any Cloud, Any Language, Any Workflow

AWS Step Functions is reliable inside the AWS ecosystem. Kestra covers the rest: data pipelines, infrastructure, and business processes across any cloud, any language, and any team.

Try for Free - 26k GitHub Stars Book a Demo

Two Platforms, Two Architectures

Universal Orchestration: Any Cloud, Any Language

Open-source orchestration platform built on declarative YAML. Orchestrate data pipelines, infrastructure automation, and business processes across AWS, Azure, GCP, or on-premises. Bring your existing scripts in any language without refactoring.

"How do I automate workflows across my whole stack without locking into one cloud?"

AWS Service Orchestration

Managed AWS service for orchestrating AWS services using Amazon States Language (ASL). Ideal for serverless workflows within the AWS ecosystem, with tight integration across Lambda, ECS, and other AWS-native services.

"How do I coordinate my AWS Lambda functions and services reliably?"

AWS Automation Optimizes Infrastructure.
Workflow Orchestration Transforms a Business.

Business-critical Workflows

Automate how your entire company operates
Cross-functional: data + ops + business + IT
Multi-cloud and on-premises without vendor lock-in
Developer self-service with enterprise guardrails
Serves the entire organization

AWS Service Coordination

Orchestrate Lambda, ECS, and AWS-native services
AWS-native scope only
Requires IAM configuration per workflow
Per-state-transition pricing compounds at scale
Serves AWS-focused engineering teams

AWS Step Functions is a strong choice if your workflows live entirely within AWS and you need reliable Lambda orchestration without managing infrastructure. For teams that need to orchestrate across clouds, run existing Python or SQL scripts without Lambda wrappers, or automate beyond AWS services, Kestra provides a broader platform with open-source flexibility and predictable pricing.

Time to First Workflow

AWS Step Functions requires an AWS account, IAM roles with least-privilege policies, and workflows written in Amazon States Language (a JSON-based DSL that defines states, transitions, and error handling separately from your business logic).

~5

Minutes

curl -o docker-compose.yml \
https://raw.githubusercontent.com/kestra-io/kestra/develop/docker-compose.yml
docker compose up

# Open localhost:8080
# Pick a Blueprint, run it. Done.

Download the Docker Compose file, spin it up, and you're ready—database and config included. Open the UI, pick a Blueprint, run it. No cloud account required, no IAM policies to configure.

~45

Minutes

# 1. Create IAM execution role with trust policy
aws iam create-role --role-name StepFunctionsRole \
  --assume-role-policy-document file://trust-policy.json

# 2. Attach permissions for each AWS service you need
aws iam attach-role-policy --role-name StepFunctionsRole \
  --policy-arn arn:aws:iam::aws:policy/AWSLambdaRole

# 3. Write Amazon States Language definition (JSON)
# 4. Create state machine
aws stepfunctions create-state-machine \
  --name my-workflow \
  --definition file://state-machine.json \
  --role-arn arn:aws:iam::123456789012:role/StepFunctionsRole

Requires AWS account setup, IAM role creation with trust and permission policies, learning Amazon States Language, and deploying via console or CloudFormation before running a first workflow.

Workflows Your Whole Team Can Read

Kestra: Readable by Your Whole Team

id: daily_etl
namespace: analytics

triggers:
  - id: daily
    type: io.kestra.plugin.core.trigger.Schedule
    cron: "0 6 * * *"

tasks:
  - id: extract_and_process
    type: io.kestra.plugin.scripts.python.Script
    script: |
      import boto3, pandas as pd
      s3 = boto3.client('s3')
      df = pd.read_parquet('s3://my-bucket/raw/data.parquet')
      df.to_csv('/tmp/processed.csv')
      s3.upload_file('/tmp/processed.csv', 'my-bucket', 'processed/data.csv')

  - id: notify
    type: io.kestra.plugin.notifications.slack.SlackIncomingWebhook
    url: "{{ secret('SLACK_WEBHOOK') }}"
    messageText: "Daily ETL complete"

YAML is readable on day 1. The AI Copilot writes workflows for you, or start with our library of Blueprints. Run Python, SQL, Bash, or any language directly. No Lambda wrappers, no deployment packages.

AWS Step Functions: State Machine JSON with Lambda Wrappers

{
  "Comment": "Daily ETL workflow",
  "StartAt": "ExtractAndProcess",
  "States": {
    "ExtractAndProcess": {
      "Type": "Task",
      "Resource": "arn:aws:lambda:us-east-1:123456789012:function:extract-process",
      "Next": "Notify",
      "Catch": [
        {
          "ErrorEquals": ["States.ALL"],
          "Next": "HandleError"
        }
      ]
    },
    "Notify": {
      "Type": "Task",
      "Resource": "arn:aws:lambda:us-east-1:123456789012:function:send-notification",
      "End": true
    },
    "HandleError": {
      "Type": "Fail",
      "Error": "ETLFailed",
      "Cause": "Workflow step failed"
    }
  }
}

Business logic lives in Lambda functions; orchestration logic lives in Amazon States Language. Each step is a separate deployed function. When something breaks, debugging means navigating the Step Functions console, CloudWatch Logs, and individual Lambda execution logs in parallel.

One Platform for Your Entire Technology Stack

Orchestrate across data pipelines, infrastructure operations, business processes, and customer workflows. Multi-cloud by default: AWS, Azure, GCP, and on-premises in a single platform.

Purpose-built for AWS service orchestration. Excellent at coordinating Lambda, ECS, SageMaker, and AWS-native services. Not designed for multi-cloud workflows, cross-language scripting without Lambda, or business process automation beyond the AWS ecosystem.

Kestra vs AWS Step Functions at a Glance


Primary use case	Universal workflow orchestration	AWS service orchestration
Workflow definition	Declarative YAML	Amazon States Language (JSON)
Languages supported	Agnostic (Python, SQL, R, Bash, Node.js & more)	Any language via Lambda wrappers
Cloud support	Multi-cloud (AWS, Azure, GCP, on-premises)	AWS only
Deployment options	Self-hosted, Kestra Cloud, or air-gapped	AWS-managed only (no self-hosted option)
Pricing model	Open source (free) or subscription	Per-state-transition (Standard and Express tiers)
Self-service for non-engineers	Kestra Apps	Not designed for this
Infrastructure automation	Native support	AWS infrastructure only (via SDK task integrations)
Business process automation	Native support	Limited to AWS-native scope
Open source	Apache 2.0	Proprietary AWS service

Kestra was the only tool that combined true multi-tenant isolation, metadata-driven orchestration, and easy integration with our existing AWS and Databricks environments. It provided the foundation we needed to scale confidently.

Director of Engineering @ Acxiom

120+Engineers empowered

50+Customers on multi-tenant platform

0Pipeline rewrites required

Kestra Is Built for How Modern Engineering Teams Work

No cloud vendor lock-in

Kestra runs on AWS, Azure, GCP, on-premises, or any combination. Workflows are portable YAML, not tied to a proprietary state machine format or a single cloud's IAM model. Move environments, add clouds, or go multi-cloud without rewriting orchestration logic.

Bring your existing scripts

Run Python, SQL, Bash, and R directly in Kestra without Lambda wrappers or deployment packages. Scripts execute in isolated containers with full dependency control. Your existing code works as-is. No framework wrappers, no IAM execution role per function.

Minutes to first workflow

Two commands and you're running workflows locally. No AWS account, no IAM configuration, no ASL syntax to learn. When you're ready for production, deploy to Kubernetes or Kestra Cloud with the same YAML you developed locally.

The Right Tool for the Right Job

Choose Kestra When

Your workflows span multiple clouds or include on-premises systems. AWS Step Functions cannot orchestrate outside of AWS.
Your team works in Python, SQL, Bash, or R and you don't want to wrap every script in a Lambda function with its own deployment package.
You need workflow orchestration beyond AWS: data pipelines, business processes, infrastructure automation across your whole stack.
Predictable pricing matters. Per-state-transition costs compound quickly for high-frequency or long-running workflows.
Non-engineers need to trigger and monitor workflows without writing ASL or Lambda code.

Choose AWS Step Functions When

Your workflows are entirely within AWS and you want zero infrastructure to manage.
You're already deeply invested in Lambda and need reliable coordination between functions with native AWS retries and error handling.
Native AWS service integrations (SageMaker, Bedrock, ECS, Glue, DynamoDB) are at the center of your use case.
AWS-native audit trails, CloudWatch integration, and IAM-based access control are compliance requirements.

Getting Started with Multi-Cloud Orchestration

See how Kestra can orchestrate workflows across any cloud, any language, and your entire stack.

Book a Demo

Kestra vs. AWS Step Functions: Any Cloud, Any Language, Any Workflow

Two Platforms, Two Architectures

Universal Orchestration: Any Cloud, Any Language

AWS Service Orchestration

AWS Automation Optimizes Infrastructure.Workflow Orchestration Transforms a Business.

Business-critical Workflows

AWS Service Coordination

Time to First Workflow

~5

Minutes

~45

Minutes

Workflows Your Whole Team Can Read

Kestra: Readable by Your Whole Team

AWS Step Functions: State Machine JSON with Lambda Wrappers

One Platform for Your Entire Technology Stack

Kestra vs AWS Step Functions at a Glance

Kestra Is Built for How Modern Engineering Teams Work

No cloud vendor lock-in

Bring your existing scripts

Minutes to first workflow

The Right Tool for the Right Job

Choose Kestra When

Choose AWS Step Functions When

Frequently asked questions

How do I migrate from AWS Step Functions to Kestra?

Does Kestra work with AWS services?

Can Kestra replace Lambda functions, or do I still need them?

How does Kestra's pricing compare to AWS Step Functions?

Can I run Kestra on AWS?

What about AWS Step Functions' visual workflow editor?

Getting Started with Multi-Cloud Orchestration

AWS Automation Optimizes Infrastructure.
Workflow Orchestration Transforms a Business.