Informational Fresh jira_story: GOV-323

Lesson 4 of 4 — Observability backend

Scale & Intelligence · Source: Jira Story GOV-323 (5 pts) · Authority: Informational (the Jira story is authoritative).

Purpose

Add an observability backend for the platform.

Why it matters

You can't operate at scale what you can't observe.

Where this lives

Runs in the Customer AI Governance platform (components: platform). Requests emit metrics exported to Prometheus/OpenTelemetry. Learn teaches this read-only.

Workflow

Given platform requests
When they are served
Then metrics are exported to Prometheus and OpenTelemetry

Worked example

The platform is slow in production but there are no metrics. What does this story add?

An observability backend exporting metrics to Prometheus/OTel so operations are visible.

Acceptance criteria (authoritative — GOV-323)

Given platform requests, when they are served, then metrics are exported to Prometheus and OpenTelemetry.

Common pitfalls

Shipping features with no metrics or telemetry.

Knowledge check

Scenario: The platform is slow in production but there are no metrics. What does this story add?
Look for: An observability backend exporting metrics to Prometheus/OTel so operations are visible.

Key concepts

observability
Prometheus/OTel
metrics export

For the AI Tutor

Summary: Add an observability backend for the platform.
When to use: teaching or answering questions about "observability backend".
When NOT to use: governance posture computation (that is GOV-135).
Key concepts: observability, Prometheus/OTel, metrics export.

Completion criteria

Learner passes the scenario knowledge check and can point to the system state that satisfies GOV-323's acceptance criterion.

Module: LEARN-MOD-011 (Scale & Intelligence)
Provenance: LEARN-MAP-001 · Generation standard: LEARN-STD-002
Next: (module complete)