AI Gateway

APIM Policy Patterns for AI Governance: Part 2 – Content Safety & Model Control

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Part 1 covered the consumption side of an AI gateway: rate limits, token quotas, usage attribution and the telemetry needed to understand them. The next runtime decision is whether a request should be allowed through at all, followed by whether that consumer is entitled to use the model it asked for. Those are separate controls, … Read more

APIM Policy Patterns for AI Governance: Part 1 – Rate Limits, Token Quotas & Observability

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How I would use Azure API Management to control AI request rates and token consumption, attribute usage, emit useful telemetry and handle backend throttling.

From Azure Policy to APIM: Implementing Azure AI Guardrails

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Azure Policy and API Management solve different parts of AI governance in Azure. This post goes into the actual policies and APIM XML behind that two-layer model, covering network controls, approved models, token quotas, content safety and observability.

Building an Azure AI Landing Zone Without Slowing Teams Down

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An Azure AI Landing Zone should make the governed route the easiest route for delivery teams. This post covers how Azure API Management, Azure Policy, identity, networking, quotas, telemetry and clear ownership boundaries work together to control AI consumption without turning the platform team into an approval bottleneck.