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docs(architect): weekly KB update — 66 files refreshed (2026-04)

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Updated 66 stale knowledge base reference files (10 critical, 56 high)
across all 5 skills using Microsoft Learn MCP research.

Key factual updates:
- Groundedness Detection API: `correction` → `mitigating` param,
  `correctedText` → `correctionText` (breaking change)
- Copilot Studio: GPT-4.1 mini now default (was GPT-4o mini);
  Claude Sonnet 4.5 + Opus 4.5 added (experimental, 200K ctx)
- Agentic Retrieval: still public preview; 50M free tokens/month
- Azure security baselines: "Cognitive Services" → "Foundry Tools"
- Databricks: Delta Live Tables → Lakeflow Spark Declarative Pipelines
- MLflow 3 GenAI: new Feedback/Expectation data model
- Token tracking doc: "Azure OpenAI in Foundry Models through a gateway"
- Agent Registry: Risks column (M365 E7), Graph API (preview)
- Copilot DLP: new Entra AI Admin + Purview Data Security AI Admin roles
- ISO/IEC 42001: scope expanded to M365 Copilot, Foundry, Security Copilot
- Zero Trust: CAE now via Conditional Access, Strict Location Enforcement
- Purview: new Fabric Copilots/agents governance section
- AG-UI HITL: ApprovalRequiredAIFunction (C#), @tool approval_mode (Python)

All files: Last updated → 2026-04, *(Verified MCP 2026-04)* markers added.
Build registry: 1341 URLs from 387 files (+2 new URLs).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Kjell Tore Guttormsen 2026-04-09 22:41:26 +02:00
commit 565043dbde
73 changed files with 727 additions and 301 deletions
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skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md
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@ -1,7 +1,7 @@
# Token Usage Tracking and Attribution
**Kategori:** Monitoring & Observability
**Dato:** 2026-02-05
**Dato:** 2026-04-09
**Versjon:** 1.0
## Introduksjon
@ -569,7 +569,7 @@ Owner: <email>
## Kilder (Microsoft Learn)
1. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Official monitoring guide
2. [Implement advanced monitoring through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-monitoring) — Gateway patterns for usage tracking
2. [Implement advanced monitoring for Azure OpenAI in Foundry Models through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-monitoring) *(Verified MCP 2026-04)* — Gateway patterns for usage tracking. Ny brukscase dokumentert: audit av model inputs/outputs for threat detection og data exfiltration detection. Merk: gateway monitoring kan bli single point of failure — vurder redundans.
3. [Plan to manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — Cost management strategies
4. [Token usage estimation for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) — RAG-specific token calculations
5. [Understanding costs associated with PTU](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU billing model