Build durable workflows on Catalyst

This section is for developers who orchestrate long-running processes with Catalyst Workflows. A workflow on Catalyst picks up where it left off after a crash, a deploy, or a restart, and it can run for hours or days. Catalyst can also sign each step of a workflow's history, so you can prove how a run went.

You write workflows in .NET, Go, Java, JavaScript, or Python.

Start with your AI coding agent

Let Claude Code, Codex or the Copilot CLI run a durable workflow in your language for you.

Quickstart: build a workflow (AI Plugin)

Your agent runs a sample workflow, crashes it, and shows you it resume.

Local installation

Install the Catalyst AI plugin for your coding agent.

Pick your language

Each language has a page with its quickstart, SDK guide, and tutorials.

• Python

  • Quickstart

• .NET

  • Quickstart
  • Why Dapr, Aspire and Catalyst
  • All resources

• JavaScript

  • Quickstart

• Java

  • Quickstart
  • Spring Boot
  • Quarkus

• Go

  • SDK guide

For every language

Patterns

Task chaining, fan-out/fan-in, human-in-the-loop, sagas, and more.

Versioning

Change a workflow without breaking the runs already in flight.

Dapr Skills

Scaffold and review workflows with Claude Code.

Tutorial: verifiable execution

Tamper with a signed workflow and catch it.

Where to go next

Concepts

Workflow applications, durable execution, and verifiable execution.

Run & operate

Manage workflow runs, verify their history, and set access policies.

Reference

The App API, including the workflow endpoints.

Learn hands-on

🎓Durable Execution & Dapr University · Learn this hands-onDapr Workflow: Use durable execution to build reliable distributed applicationsBuild reliable distributed applications with durable execution: task chaining, fan-out/fan-in, and error handling.Intermediate50 min.NET · Java · PythonStart the track →