Azure-Samples / Azure-Samples/simple-foundry-hosted-agent-python-aigateway

Update AI Gateway monitoring to use the current OpenTelemetry configuration

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Description

### Problem

The sample currently configures `telemetryExporters` with `kind: applicationInsights` and an Application Insights connection string. The current AI Gateway monitoring experience expects the native OTLP/OpenTelemetry configuration, so the portal does not reliably recognize this legacy exporter as monitoring-enabled.

### Missing configuration

- Register the `Microsoft.Monitor` resource provider.
- Set `AzureMonitorWorkspaceIngestionMode: Enabled` on the workspace-based Application Insights resource.
- Wait for Application Insights to generate its managed DCR/DCE and OTLP endpoints.
- Configure the exporter with `kind: OpenTelemetry`, the Application Insights resource ID, metrics/logs/traces OTLP endpoints, and managed-identity audience `https://monitor.azure.com`.
- Assign the AI Gateway system-assigned identity the **Monitoring Metrics Publisher** role (`3913510d-42f4-4e42-8a64-420c390055eb`) at the generated DCR scope.
- Account for the deny assignment on the generated managed resource group: a nested ARM/Bicep role assignment is blocked, while a direct role-assignment PUT from an `azd` post-provision hook works.
- Document that exporter `kind` is immutable, requiring delete/recreate when migrating an existing legacy exporter.

### Current preview behavior

The service currently persists metrics and logs endpoints but may omit a supplied `tracesEndpoint` from exporter GET responses. Metrics and logs are sufficient for the portal dashboard eligibility check.

Contributor guide

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Research direction

Start by locating the sample's AI Gateway exporter and Azure provisioning configuration, then trace how the workspace-based Application Insights resource and azd post-provision hook are defined. Done means the current OpenTelemetry endpoints, provider and workspace settings, managed-identity role assignment, migration behavior, and preview response caveat are represented and documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
azure
Domain
cloud, infrastructure, observability-sre
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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