Vector¶

Field	Value
Purpose	Vector-specific configuration — high-performance observability data pipeline
Repo	AmadlaOrg/Entities/Application/LogShipping/Vector
Entity URI	`amadla.org/entity/application/log-shipping/vector@v1.0.0`
Parent type	Application/LogShipping

Schema¶

Property	Type	Description
`sources`	object	Named source configurations (each key is a source ID)
`sources.<id>.type`	string	Source type (`file`, `journald`, `syslog`)
`transforms`	object	Named transform configurations (each key is a transform ID)
`transforms.<id>.type`	string	Transform type (`remap`, `filter`, `aggregate`)
`transforms.<id>.inputs`	array of strings	Input source or transform IDs
`sinks`	object	Named sink configurations (each key is a sink ID)
`sinks.<id>.type`	string	Sink type (`elasticsearch`, `loki`, `kafka`, `console`)
`sinks.<id>.inputs`	array of strings	Input source or transform IDs

Example¶

_type: amadla.org/entity/application/log-shipping/vector@v1.0.0
_extends: amadla.org/entity/application/log-shipping@v1.0.0
_body:
  sources:
    nginx_logs:
      type: file
      include:
        - /var/log/nginx/*.log
    journal:
      type: journald
      units:
        - myapp.service
  transforms:
    parse_nginx:
      type: remap
      inputs:
        - nginx_logs
      source: ". = parse_nginx_log!(.message)"
    add_metadata:
      type: remap
      inputs:
        - journal
      source: '.environment = "production"'
  sinks:
    loki:
      type: loki
      inputs:
        - parse_nginx
        - add_metadata
      endpoint: http://loki.example.com:3100
      labels:
        job: vector
    console:
      type: console
      inputs:
        - parse_nginx
      encoding:
        codec: json

Consumers¶

Tool	How It Uses Application/LogShipping/Vector
lay	Installs the `vector` package
weaver	Generates `/etc/vector/vector.toml`
enjoin-service	Enables/starts `vector` service