Show HN: Orloj – agent infrastructure as code (YAML and GitOps)

Summary

Named after the Prague Orloj, an astronomical clock that has coordinated complex mechanisms for over 600 years. An orchestration runtime for multi-agent AI systems. Declare your agents, tools, and policies as YAML. Orloj schedules, executes, routes, and governs them so you can run multi-agent systems in production with the same operational rigor you expect from infrastructure. Status: Orloj is under active development. APIs and resource schemas may change between minor versions before 1.0. Running AI agents in production today looks a lot like running containers before container orchestration: ad-hoc scripts, no governance, no observability, and no standard way to manage an agent fleet. Orloj provides: Agents-as-Code -- declare agents, their models, tools, and constraints in version-controlled YAML manifests. DAG-based orchestration -- pipeline, hierarchical, and swarm-loop topologies with fan-out/fan-in support. Model routing -- bind agents to OpenAI, Anthropic, Azure OpenAI, Ollama, and other endpoints. Switch providers without changing agent definitions. Tool isolation -- execute tools in containers, WASM sandboxes, or process isolation with configurable timeout and retry. Governance built in -- policies, roles, and tool permissions enforced at the execution layer. Unauthorized tool calls fail closed. Production reliability -- lease-based task ownership, idempotent replay, capped exponential retry with jitter, and dead-letter handling. Web console -- built-in UI with topology views, task inspection, and live event streaming. Download orlojd (server) and orlojctl (CLI) for your platform from GitHub Releases, extract them, and run: # Start the server with an embedded worker ./orlojd --storage-backend=memory --task-execution-mode=sequential --embedded-worker Open http://127.0.0.1:8080/ to explore the web console, then apply a starter blueprint. The example manifests live in this repo -- clone it or browse them on GitHub: # Apply a starter blueprint (pipeline: planne...