docs(architect): weekly KB update — 52 files refreshed (2026-04)

Key content changes:
- MLOps: MLflow 3 scorers expanded (RetrievalRelevance, Fluency, multi-turn judges)
- MLflow 3 A/B eval: mirror_traffic GA confirmed, new scorer catalog
- CI/CD: OIDC auth replaces deprecated --sdk-auth (Azure ML GitHub Actions)
- Agent framework A2A: updated SDK patterns (A2ACardResolver, BearerAuth)
- AG-UI backend tool rendering: accurate TOOL_CALL_* event shapes
- Computer Use agents: US region requirement, credentials patterns
- Purview governance: bulk term edit, expire/delete workflows
- CAF AI Secure: 3-phase structure confirmed current
- Copilot Studio: Claude Sonnet 4.5/4.6 GA, new orchestration controls
- M365 manifest: v1.26 GA (April 2026), copilotAgents node
- Power Platform: agent flow capacity enforcement corrected
- Azure Monitor: Simple Log Alerts GA, AMBA for policy-based alerting
- Security Copilot: SCU capacity model (400 SCU/1000 users)
- EU Data Boundary: all EU + EFTA countries confirmed
- gateway-multi-backend: added 4th topology, subscription-level quota note

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md

@@ -1,7 +1,7 @@
 # Inferencing Optimization and Caching
 
 **Kategori:** MLOps & GenAIOps
-**Dato:** 2026-02-04
+**Dato:** 2026-04
 **Forfattet av:** Cosmo Skyberg, Senior Microsoft AI Solution Architect
 
 **Verified:** MCP 2026-04
@@ -1015,7 +1015,7 @@ Diagnostikk:
 **Confidence nivå: HIGH** — Denne referansen er basert på 12 MCP-kall til offisiell Microsoft-dokumentasjon og kodeeksempler.
 
 
-### ONNX Inferencing Optimization for Computer Vision (Azure ML AutoML 2026)
+### ONNX Inferencing Optimization for Computer Vision (Azure ML AutoML 2026) — Verified (MCP 2026-04)
 
 ONNX (Open Neural Network Exchange) enables cross-framework interoperability and inference optimization: