Kestra Technologies
Kestra Technologies builds Kestra, an open-source, declarative, event-driven orchestration platform for data pipelines, infrastructure, applications, AI workflows and business processes. Its stated mission is to let developers orchestrate any workflow, in any language, on any infrastructure, with code and UI working together.
At a Glance
- Enterprise data and platform engineering teams
- Infrastructure, DevOps and IT operations teams
- AI/ML and analytics teams
- Financial services and banking
- +4 more
AI Tools by Kestra Technologies
(1)Kestra
Open Source YAML Workflow Orchestrator
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Latest News
Kestra 2.0 launched with a new distributed execution engine, workers anywhere, and flows exposed as AI-agent tools.
Kestra joined the DigitalOcean Partner Program and released a dedicated DigitalOcean plugin and blueprints.
Kestra announced a $25 million Series A led by RTP Global, bringing total funding to $36 million, and outlined Kestra 2.0 and Kestra Cloud investment.
Kestra and Conapi announced a partnership connecting Kestra orchestration with Gravitee API management and JMS integration.
Products & Services
Apache 2.0-licensed, self-hosted declarative orchestration platform with unlimited flows and executions, code and no-code editors, event-driven scheduling, Git integration, multi-cloud/air-gapped deployment and 2,200+ plugins.
Commercial edition for mission-critical, multi-team deployments, adding SSO/OIDC, SCIM, RBAC, multi-tenancy, policies, audit logs, cases, worker groups, task runners, secrets management, high availability, enterprise plugins and SLA-backed support.
Fully managed SaaS offering with hosting, upgrades, monitoring, automatic scaling, built-in security/governance, enterprise plugins and usage-based pricing.
Major release adding declarative orchestration as code and from the UI, AI Copilot, AI Agents, MCP server, AI-powered search, no-code editor improvements, plugin versioning, unit tests, flow SLAs and production deployment enhancements.
Market Position
Kestra positions itself as a universal, language-agnostic orchestration control plane spanning data, infrastructure, applications, business workflows and AI, rather than a Python-only data orchestrator or a narrow infrastructure scheduler. Its main alternatives include Apache Airflow, Dagster, Prefect, Temporal, Argo Workflows, Azure Data Factory and AWS Step Functions; Kestra differentiates through declarative YAML plus UI, broad plugin coverage, event-driven execution, hybrid/air-gapped support and one platform across multiple teams and workload types.
Leadership
Founders
Emmanuel Darras
CEO and co-founder; previously co-founded Ankama.
Ludovic Dehon
CTO and co-founder; software engineer turned entrepreneur and creator of AKHQ, the open-source Kafka GUI.
Executive Team
Emmanuel Darras
CEO and Co-Founder
Serial entrepreneur and former co-founder of Ankama.
Ludovic Dehon
CTO and Co-Founder
Software engineer and entrepreneur; creator of AKHQ.
Founding Story
The underlying project began in 2019 at Leroy Merlin France, where the data team was migrating from Teradata to BigQuery and needed to scale thousands of workflows while existing orchestrators were too fragile, slow or restrictive. Emmanuel Darras and Ludovic Dehon developed Kestra around an engineer-friendly, enterprise-ready and open-source approach: declarative workflows that could span data, infrastructure and applications rather than being locked to one language or team.
Business Model
Revenue Model
Open-source self-hosting is free; Kestra monetizes through annual per-instance Enterprise subscriptions with support and SLAs, plus Kestra Cloud as a fully managed, usage-based SaaS service.
Pricing Tiers
Self-hosted production-ready orchestration with unlimited flows and executions and 2,200+ plugins.
Fully managed hosting, upgrades, monitoring, scaling, security/governance and enterprise plugins; access is requested through Kestra.
Per-instance model with unlimited flows/tasks/executions, enterprise governance/security, customer-success program and SLA-backed support.
Target Markets
- Enterprise data and platform engineering teams
- Infrastructure, DevOps and IT operations teams
- AI/ML and analytics teams
- Financial services and banking
- Retail and e-commerce
- Manufacturing and industrial companies
- Data pipelines and ETL/ELT
- Data ingestion and integration
- Machine-learning model deployment and AI/RAG workflows
- Event-driven automation and real-time processing/change-data capture
- Infrastructure provisioning and orchestration
- CI/CD and Terraform automation
- Apple
- Toyota
- JPMorgan Chase
- BHP