Editor setup (autocomplete & validation)

faucet ships a JSON Schema for the whole config document, so a YAML-aware editor can give you autocomplete, inline documentation, and validation as you type while authoring a faucet.yaml.

Get the schema

Generate it from your own binary (so it reflects exactly the connectors and blocks you compiled in):

faucet schema config > faucet.schema.json

A prebuilt, comprehensive copy (generated under --all-features) is also committed to the repository at schemas/faucet.schema.json.

VS Code (YAML extension)

Install the Red Hat YAML extension, then either add a modeline to the top of each config:

# yaml-language-server: $schema=./faucet.schema.json
version: 1
name: my-pipeline
pipeline:
  source:
    type: rest      # ← autocompletes; picking a type narrows `config:`
    config: { ... }

or map it globally in .vscode/settings.json:

{
  "yaml.schemas": {
    "./faucet.schema.json": ["faucet.yaml", "faucet.yml", "**/pipelines/*.yaml"]
  }
}

JetBrains IDEs

Settings → Languages & Frameworks → Schemas and DTDs → JSON Schema Mappings. Add a mapping from faucet.schema.json to your config file(s) or a glob.

What you get

• Top-level grammar — every block (pipeline, matrix, execution, schedule, lineage, quality, dlq, resilience, …) with its fields and descriptions; unknown top-level keys are flagged.
• Connector discrimination — the source: / sink: type: field autocompletes to the connector kinds your binary knows, and picking one narrows the config: block to that connector’s fields.
• Interpolation-tolerant — a ${env:…} / ${vars:…} / ${now.*} placeholder is accepted anywhere a typed value is expected, so an interpolated config never shows spurious type errors.

The schema is regenerated and diff-checked in CI, so it never drifts from the connectors and config blocks the code actually accepts.