Core Concepts
What is Conductor?
Applies to both editions
This page describes the Conductor engine that powers both open-source Conductor and Orkes Conductor. Operational defaults mentioned here, such as Redis or Elasticsearch, are specifics of the open-source distribution; Orkes Conductor deployments run the Orkes platform stack.
Conductor is an open source orchestration engine that runs workflows durably. A workflow is a series of tasks that can branch, loop, and run in parallel. Conductor decides which task runs next, records the result of every step, and retries or resumes when a step fails. A crash or restart never loses progress.
Responsibilities are split between the Conductor server and your own code:
- The server orchestrates. It runs as its own service, self-hosted or managed in the cloud. It schedules tasks, enforces retries and timeouts, and persists state after every step. Orchestration logic stays out of your application code.
- Your workers execute. They run in your own infrastructure, inside the services, containers, or functions you already deploy. Business logic is a plain function written in any language with a Conductor SDK. Workers poll the server for tasks and report results, so they need no inbound ports.
- System tasks are built in. They run inside the server itself. Common steps such as HTTP calls, events, and LLM calls need no worker code.
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flowchart LR
def["Workflow definition<br/>(JSON or code)"] --> engine
subgraph server["Conductor server"]
engine["Schedules tasks, persists every state transition,<br/>handles retries, timeouts, and flow control"]
end
engine -- "queues tasks" --> queue[["Task queues"]]
workers["Your workers<br/>(any language)"] -- "poll for work" --> queue
workers -- "report results" --> engineWorkflow definitions are JSON. Version them in source control, generate them from code, or let an LLM create and modify them at runtime.
AI work runs the same way. LLM calls, tool use, and agents are workflow tasks, with the same retries, persistence, and observability as every other step.
What can Conductor do?
Core building blocks
- Workflows — The blueprint of a process flow. A workflow is a JSON document that describes a directed graph of tasks, their dependencies, input/output mappings, and failure handling policies.
- Tasks — The basic building blocks of a Conductor workflow. Tasks can be system tasks (executed by the engine) or worker tasks (executed by external workers polling for work).
- Workers — The code that executes tasks in a Conductor workflow. Workers are language-agnostic processes that poll the Conductor server, execute business logic, and report results back.
- Agents (
AGENTtask) — Invoke a deployed Conductor Agent or a remote A2A agent as a durable step inside a workflow.
Supported platforms and integrations
A quick reference for what Conductor supports out of the box:
| Area | Supported |
|---|---|
| Worker SDKs | Java, Python, Go, JavaScript, C#, Clojure, Ruby, Rust |
| LLM providers | 14+, including OpenAI, Anthropic, Gemini, Bedrock, Mistral, and Azure OpenAI |
| Tool calling | MCP (Model Context Protocol) |
| Vector databases | Pinecone, pgvector, MongoDB Atlas |
| Event brokers | Kafka, NATS JetStream, SQS, AMQP, Azure Service Bus |
| Persistence backends | PostgreSQL, MySQL, Redis, Cassandra, SQLite |
Deep dives
- Architecture — system design and components
- Durable Execution — failure semantics and state persistence
- Agents & AI — LLM orchestration patterns and agentic workflows