Migrating to Windmill for internal automation

Windmill uses a Rust core for scheduling and queue management. This engine achieves sub-millisecond scheduling latency. It differs from n8n, which runs on Node.js and TypeScript. Developers move to Windmill to access polyglot workers in Python, Go, and Bash. These workers run in isolated processes with configurable resource limits. n8n uses a visual canvas to connect nodes. Windmill uses a web IDE. You likely realize that managing complex logic in a visual diagram becomes difficult once workflows exceed twenty steps. Windmill generates UI forms from typed parameters. This capability lets non-engineers run scripts safely. Teams moving from n8n often encounter friction because n8n requires manual intervention for complex branching, whereas Windmill provides a web IDE with full language server protocol support for autocompletion and type checking. The Windmill flow builder hits complexity walls when handling complex data engineering tasks like dynamic task generation. n8n released version 2.0 in December 2025, which requires every workflow to have a trigger node. Its AI Agent node, released in January 2026, provides improved token management. n8n has over 400 nodes, but Windmill provides flexibility by allowing users to import any library from PyPI or NPM.

Performance and Resource Isolation

Temporal uses the virtual actor pattern for durable execution. Windmill uses a job queue in PostgreSQL. Temporal requires deterministic code to prevent errors during replays. Windmill runs scripts in isolated sandboxes using nsjail and PID namespace isolation. The added latency from a job being pulled from the queue and started is approximately 50ms. A typical lightweight Deno job takes around 100ms total. n8n uses a Node.js event loop with Bull Queue and Redis. n8n memory consumption grows linearly with workflow complexity. In contrast, Windmill maintains a constant orchestrator memory of 150MB. n8n has over 400 built-in nodes. Windmill uses SDKs for integrations like Stripe.

Temporal handles mission-critical processes with high concurrency. Windmill handles script-based automation and internal tools. Windmill provides SSH execution and MQTT triggers for self-hosted users. Windmill automates retries from the last checkpoint. n8n counts over 3,000 enterprise customers as of March 2025. Windmill has over 12,000 GitHub stars. Developers can run scripts locally by passing environment variables for the wemllclient library. Windmill handles workflows as directed acyclic graphs.

Setting Up Self-Hosted Windmill

Self-hosting Windmill requires Docker Compose. The default setup spins up six to eight containers. This includes the server, multiple worker containers, Postgres, and an LSP container. A 4GB RAM minimum supports this deployment. Deployment on Kubernetes uses Helm charts. Windmill provides integrated secret management with a built-in variable store. This system stores encrypted values in the database and injects them at runtime. Python users use uv for dependency management. TypeScript users use Bun or Deno. The platform uses Svelte 5 for its frontend. Windmill allows Git sync for up to two users in the free tier. Deployment on Fargate or Docker is also possible. Windmill handles workflows via a job queue. Users can deploy from GitHub. Windmill also handles file uploads by streaming to S3-compatible storage via vclone. Users can configure worker groups to manage resource isolation. The default credentials for a local setup are admin@windmill.dev/changeme. Will the resource overhead of eight containers prevent small teams from adopting this platform? Windmill wins for DevOps runbooks and internal automation.