APIM Policy Patterns for AI Governance: Part 1 – Rate Limits, Token Quotas & Observability
How I would use Azure API Management to control AI request rates and token consumption, attribute usage, emit useful telemetry and handle backend throttling.
Azure API Management
From Azure Policy to APIM: Implementing Azure AI Guardrails
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
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.
AI Engineering Needs Platform Controls
AI-assisted engineering is moving beyond “can the agent do the task?” and into the same practical concerns platform teams already deal with: cost visibility, ownership, observability, governance, repeatable workflows, and sensible defaults.
This post looks at why AI engineering needs boring platform controls, from APIM policies and token visibility through to Agent Skills, MCP, Terraform modules, OpenTelemetry, and evaluation loops.
Cross-Tenant Azure API Management Authentication with Federated Credentials: A Complete Guide
Working with Azure API Management across multiple tenants? Tired of managing service principal secrets and certificates? In this blog post, I’m going to show you how to set up passwordless cross-tenant authentication using User-Assigned Managed Identities and Federated Credentials. This approach eliminates the need for client secrets while enabling secure service-to-service authentication between API Management … Read more