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skills/ms-ai-engineering/references/mlops-genaiops/cost-optimization-mlops-pipelines.md
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# Kostnadsoptimalisering i MLOps-pipelines
**Dato:** 2026-04
**Last updated:** 2026-04
**Category:** MLOps & GenAIOps
**Relevans:** Azure Machine Learning, MLOps-implementering, FinOps for AI
**Type:** reference

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skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md
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# Governance and Audit Trails in MLOps
**Category:** MLOps & GenAIOps
**Dato:** 2026-06-19
**Last updated:** 2026-06-19
**Confidence:** 95% (High — bygger på offisiell Microsoft-dokumentasjon og Azure-referansearkitekturer)
**Type:** reference
**Source:** https://learn.microsoft.com/azure/machine-learning/concept-responsible-ai-dashboard

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skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md
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# Inferencing Optimization and Caching
**Category:** MLOps & GenAIOps
**Dato:** 2026-06-19
**Last updated:** 2026-06-19
**Forfattet av:** Cosmo Skyberg, Senior Microsoft AI Solution Architect
**Type:** reference
**Source:** https://learn.microsoft.com/azure/machine-learning/concept-onnx

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skills/ms-ai-engineering/references/mlops-genaiops/infrastructure-as-code-mlops.md
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# Infrastructure as Code for MLOps
**Dato:** 2026-06-19
**Last updated:** 2026-06-19
**Category:** MLOps & GenAIOps
**Forfatter:** Cosmo Skyberg, Senior Microsoft AI Solution Architect
**Type:** reference

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skills/ms-ai-engineering/references/mlops-genaiops/monitoring-observability-ml-systems.md
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# Monitoring and Observability for ML Systems
**Category:** MLOps & GenAIOps
**Dato:** 2026-04
**Last updated:** 2026-04
**Kilder:** Microsoft Learn (azure-machine-learning, azure-monitor)
**Konfidensgrad:** ⭐⭐⭐⭐⭐ (Verifisert mot offisiell Microsoft-dokumentasjon)
**Type:** reference