Semantic Mapping Registry

The Semantic Mapping Registry is a centralized directory designed to align naming conventions across diverse observability backends, eliminating semantic fragmentation at the edge.

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1. Naming Fragmentation & Migration Complexities

Observability platforms have historically developed proprietary attribute naming conventions. When organizations deploy multi-vendor strategies, correlation breaks because different dashboards and alert queries search for different keys representing the same metric or attribute:

Concept	OpenTelemetry standard	Datadog	Splunk	Elastic
Service Name	service.name	service	service_name	service.name
Host Name	host.name	host	host	host.name
Log Message	body	message	_raw	message
Environment	deployment.environment	env	environment	service.environment

This fragmentation complicates tool migrations, telemetry multi-routing, and incident correlation. It forces developers to write duplicate query logic for different platforms.

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2. Dynamic Translation Rules & Registry Configurations

The registry manages translation schemas. Once defined, CollectorCtrl uses these rules to compile OTel transform or attributes processor configurations, executing field translation at the edge before data ingestion.

OTel-Native Platforms (e.g. Coralogix)

Many modern platforms are OpenTelemetry-native.

• Native Integration: Coralogix is designed to ingest and parse standard OTel semantic conventions directly.
• Simplifying Mappings: When adding Coralogix as a target in the registry, you do not need to configure complex attribute renames. You can align Coralogix fields directly to standard OTel keys (e.g. keeping service.name and host.name as-is). This ensures zero-translation overhead and maintains high data compatibility.

Import & Bulk Updates

Managing thousands of legacy attributes is made easy via spreadsheet tools:

• CSV Bulk Uploads: Import schema dictionaries using the CSV uploader.
• Bulk Export: Export active mappings to a CSV spreadsheet, edit attributes in bulk, and re-upload to refresh translation processors across the fleet.

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3. AI-Driven Dashboard & Alert Migrations

Having an active, machine-readable mapping registry enables automated migration workflows. When you migrate dashboards and alerts (e.g. from Datadog to Coralogix), you can use translation mappings as a reference dictionary for AI tools:

[Datadog JSON Dashboard] 
       |
       v (AI Parser queries Semantic Registry lookup table)
   Replaces "host" with "host.name"
   Replaces "service" with "service.name"
       |
       v
[OTel-Native JSON Dashboard]

Translation Example

An AI parser uses the registry's mapping definitions to translate a Datadog monitor query into an OTel-native Prometheus alert query:

• Source Datadog query:
  avg(last_5m):sum:system.cpu.user{host:my-server} > 80
• Target OTel-native query:
  avg_over_time(system_cpu_user{host_name="my-server"}[5m]) > 80

The translation maps metrics and attribute dimensions automatically, allowing you to migrate thousands of alerts without manual rewriting.