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Kestra

Data, AI, and infrastructure workflows, orchestrated from declarative YAML: Kestra is an open-source, event-driven orchestration platform. Flows are declared in YAML - no DSL rewrites or Python decorators - and the definition stays the single source of truth even when edited through the UI, API, CI/CD, or Terraform, which makes pull-request review, versioning, and rollback natural. Tasks run in any language: Python, Node.js, Go, Rust, R, SQL, or Bash scripts executed in containers, and a plugin ecosystem of 1,000+ integrations covers ingestion, dbt, Airbyte, Spark, cloud storage, databases, and messaging systems. Scheduling supports cron triggers, event triggers, backfills, and conditional branching, with retries, timeouts, error handling, and typed inputs and outputs that surface artifacts in the UI. Namespaces, labels, and subflows organize workflows at scale, and the embedded code editor includes Git integration. Common uses span ETL/ELT pipelines, dbt runs, microservice coordination, infrastructure provisioning, and human-in-the-loop approvals. Java-based, Apache 2.0 licensed, deployed via Docker or Kubernetes.

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AutoGen Studio

Prototype multi-agent AI systems without writing orchestration code: AutoGen Studio is Microsoft's low-code interface over the AutoGen AgentChat framework. You compose teams of LLM-powered agents in a visual Team Builder, either by drag-and-drop from a component library or by editing the declarative JSON specification directly. Each agent gets a model, a prompt, tools (Python functions), and the team gets termination conditions and an orchestration pattern, sequential or LLM-driven. The Playground runs teams interactively with live message streaming between agents, a visual control-transition graph, tool-call and code-execution tracking, and pause/stop controls, which makes it a practical debugger for agent behavior. Finished teams export as JSON for use in any Python application via the TeamManager class, or serve as an API endpoint. Any OpenAI-compatible model endpoint works, including local servers like Ollama or vLLM. Microsoft labels it a research prototype: use it for prototyping and evaluation, and build production systems on the underlying AutoGen framework.

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