Orion
The declarative services runtime for the AI era
Orion is a declarative services runtime written in Rust. Instead of writing, deploying, and operating a microservice for every piece of business logic, you declare what the service should do, and Orion runs it. Architectural governance — observability, rate limiting, circuit breakers, versioning, input validation, and more — is built in.
AI generates workflows, Orion provides the governance. Every service gets health checks, metrics, retries, and error handling, regardless of how the workflow was created.
Replace a sprawl of single-purpose microservices with one runtime: each channel and workflow is independently versioned, testable, and deployable, but they share a single binary and a single set of built-in production features. This site is the deep reference and how-to guide — new here? Install Orion and ship your first service in a couple of minutes.
From zero to a live, governed service — business logic as JSON, deployed over plain HTTP. ▶ Click to play.Three Primitives
You build services in Orion with three things:
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Channel │──────▶│ Workflow │──────▶│ Connector │
│ (endpoint) │ │ (logic) │ │ (external) │
└─────────────┘ └──────────────┘ └─────────────┘
| Primitive | What it is | Example |
|---|---|---|
| Channel | A service endpoint: sync (REST, HTTP) or async (Kafka) | POST /orders, GET /users/{id}, Kafka topic order.placed |
| Workflow | A pipeline of tasks that defines what the service does | Parse → validate → enrich → transform → respond |
| Connector | A named connection to an external system, with auth and retries | Stripe API, PostgreSQL, Redis, Kafka cluster |
Design-time: define channels, build workflows, configure connectors, test with dry-run, manage versions — all through the admin API. Runtime: Orion routes traffic to channels, executes workflows, calls connectors, and handles observability automatically.
Start here
- CLI Setup — install Orion and ship your first service in a couple of minutes.
- MCP Server Setup — give an AI assistant full Orion context so it generates valid workflows.
- Use Cases & Patterns — complete, tested examples for classification, transformation, routing, and CI/CD.
Build workflows
- Workflow Reference — the workflow & task JSON schema, conditions, error handling, lifecycle, and rollout.
- Function Reference — every built-in task function and its exact
inputschema. - Admin API & Data API — the full REST surface for managing and calling services.
- Configuration — config file, environment variables, database backends, and deployment.
How it works
- Architecture Overview — channels, workflows, the engine, hot-reload, and the request-processing flow.
- Production features, all built in and configurable per channel: Observability, Resilience, Security, Scalability, Deployability, Extensibility, Availability, and Maintainability.