Technology & Engineering¶

This domain models the organization's technology capabilities, engineering activities, technical investments, and technology related decision making.

Purpose¶

The domain provides the technical context required to understand how the organization builds, operates, and invests in its software, infrastructure, and AI capabilities, and how that activity connects to delivery, cost, and business outcomes.

Scope¶

The Technology & Engineering domain covers:

Software engineering
Architecture
Infrastructure
Technical delivery
Technical capacity
Technical debt
Technology investment
Engineering quality
AI engineering
AI services
System reliability
Observability
Technical telemetry

Observability¶

Observability is a capability within Technology & Engineering rather than a separate organizational domain. It models the telemetry generated by applications and supporting infrastructure, including metrics, logs, traces, events, and other operational signals.

Observability's own ontology, canonical mappings, OpenTelemetry field reference, metrics catalogue, and field matrix are documented under observability/, starting with the Observability overview.

That sub-area retains its own internal reference material because it is substantially more detailed than the organizational metrics and KPIs derived from it. The canonical, organization-level metrics that are sourced from observability telemetry (HTTP, database, Redis, process, and related measurements) are published as part of this domain's metrics catalogue, using this domain's technology.* identifiers rather than the observability.* identifiers used internally within the observability sub-area's own field matrix and canonical mappings.

Systems and Data Sources¶

Work tracking system
Source control and CI/CD tooling
Cloud provider billing
AI project tracking tooling and model/agent registries
OpenTelemetry instrumentation, Prometheus, Loki, and Jaeger (see Observability)

Key Concepts¶

Established through the organizational ontology and, for telemetry specifically, the Minimum Observability Ontology.

Metrics and KPIs¶

Canonical metrics and KPIs for this domain are maintained in the Data Dictionary and published at:

Data Assets¶

Processes¶

To be documented through engineering and platform process discovery.

Technology & Engineering connects technical activity and system behaviour with Projects, Products, People, Finance, and organizational outcomes.