Azure Aigateway
MicrosoftOfficialCreated by Microsoft
- Skill
- Tool integration
- Cloud and DevOps
- MIT
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides the configuration patterns and policy references needed to transform Azure API Management (APIM) into a robust AI Gateway. It enables centralized governance for AI models, including Azure OpenAI and AI Foundry, by implementing essential features like semantic caching, token usage tracking, load balancing, and content safety filtering. The skill covers the full lifecycle from backend setup and managed identity authentication to advanced policy application and troubleshooting.
What it does
- Connects AI models as backends within Azure API Management.
- Implements cost control through token limits and semantic caching.
- Enforces security policies like jailbreak detection and content safety.
- Enables load balancing across multiple AI backend instances.
- Provides observability by emitting token usage metrics.
- Facilitates MCP tool protection and rate limiting.
When to use it
- When you need to govern and secure access to AI models in production.
- When you want to implement cost controls for LLM usage.
- When you need to load balance requests across multiple AI regions.
- When you need to protect AI agents with content filtering and jailbreak detection.
- When you want to convert existing APIs into MCP-compatible tools.
Advantages
- Centralized management of AI policies and security.
- Significant cost savings via semantic caching.
- Improved reliability through load balancing and retry logic.
- Enhanced security using managed identities for backend authentication.
- Detailed observability into token consumption and model performance.
Usage examples
- “Add a new Azure OpenAI backend to my existing APIM instance.”
- The agent provides the CLI commands to create the backend and the XML policy snippet to authenticate using managed identity.
- “How do I implement semantic caching to save on AI costs?”
- The agent explains how to apply the azure-openai-semantic-cache-lookup/store policies within the APIM inbound processing block.
- “Set up load balancing for my AI models across two regions.”
- The agent provides a policy pattern that uses a variable to rotate between backend URLs based on request hash.
- “How can I protect my AI gateway from jailbreak attempts?”
- The agent guides you to apply the llm-content-safety policy to filter harmful content and detect malicious inputs.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/azure-aigateway/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip azure-aigateway.zip -d .agents/skills
Documentation by Microsoft
Azure AI Gateway
Configure Azure API Management (APIM) as an AI Gateway for governing AI models, MCP tools, and agents.
To deploy APIM, use the azure-prepare skill. See APIM deployment guide.
When to Use This Skill
| Category | Triggers |
|---|---|
| Model Governance | "semantic caching", "token limits", "load balance AI", "track token usage" |
| Tool Governance | "rate limit MCP", "protect my tools", "configure my tool", "convert API to MCP" |
| Agent Governance | "content safety", "jailbreak detection", "filter harmful content" |
| Configuration | "add Azure OpenAI backend", "configure my model", "add AI Foundry model" |
| Testing | "test AI gateway", "call OpenAI through gateway" |
Quick Reference
| Policy | Purpose | Details |
|---|---|---|
azure-openai-token-limit | Cost control | Model Policies |
azure-openai-semantic-cache-lookup/store | 60-80% cost savings | Model Policies |
azure-openai-emit-token-metric | Observability | Model Policies |
llm-content-safety | Safety & compliance | Agent Policies |
rate-limit-by-key | MCP/tool protection | Tool Policies |
Get Gateway Details
# Get gateway URL
az apim show --name <apim-name> --resource-group <rg> --query "gatewayUrl" -o tsv
# List backends (AI models)
az apim backend list --service-name <apim-name> --resource-group <rg> \
--query "[].{id:name, url:url}" -o table
# Get subscription key
az apim subscription keys list \
--service-name <apim-name> --resource-group <rg> --subscription-id <sub-id>Test AI Endpoint
GATEWAY_URL=$(az apim show --name <apim-name> --resource-group <rg> --query "gatewayUrl" -o tsv)
curl -X POST "${GATEWAY_URL}/openai/deployments/<deployment>/chat/completions?api-version=2024-02-01" \
-H "Content-Type: application/json" \
-H "Ocp-Apim-Subscription-Key: <key>" \
-d '{"messages": [{"role": "user", "content": "Hello"}], "max_tokens": 100}'Common Tasks
Add AI Backend
See references/patterns.md for full steps.
# Discover AI resources
az cognitiveservices account list --query "[?kind=='OpenAI']" -o table
# Create backend
az apim backend create --service-name <apim> --resource-group <rg> \
--backend-id openai-backend --protocol http --url "https://<aoai>.openai.azure.com/openai"
# Grant access (managed identity)
az role assignment create --assignee <apim-principal-id> \
--role "Cognitive Services User" --scope <aoai-resource-id>Apply AI Governance Policy
Recommended policy order in <inbound>:
Authentication - Managed identity to backend
Semantic Cache Lookup - Check cache before calling AI
Token Limits - Cost control
Content Safety - Filter harmful content
Backend Selection - Load balancing
Metrics - Token usage tracking
See references/policies.md for complete example.
Troubleshooting
| Issue | Solution |
|---|---|
| Token limit 429 | Increase tokens-per-minute or add load balancing |
| No cache hits | Lower score-threshold to 0.7 |
| Content false positives | Increase category thresholds (5-6) |
| Backend auth 401 | Grant APIM "Cognitive Services User" role |
See references/troubleshooting.md for details.
References
Detailed Policies - Full policy examples
Configuration Patterns - Step-by-step patterns
Troubleshooting - Common issues
SDK Quick References
Content Safety: Python | TypeScript
Files
- ATTRIBUTION.mdAdded by AutoGineer977 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md4.9 KiB
- references/auth-best-practices.md6.1 KiB
- references/patterns.md6.6 KiB
- references/policies.md9.2 KiB
- references/sdk/azure-ai-contentsafety-py.md1.3 KiB
- references/sdk/azure-ai-contentsafety-ts.md1.4 KiB
- references/sdk/azure-mgmt-apimanagement-dotnet.md1.3 KiB
- references/sdk/azure-mgmt-apimanagement-py.md1.0 KiB
- references/troubleshooting.md7.7 KiB
references/troubleshooting.md
AI Gateway Troubleshooting
Common issues when using Azure API Management as an AI Gateway.
Authentication Issues
401 Unauthorized from Backend
Symptom: APIM returns 401 when calling Azure OpenAI.
Causes & Solutions:
| Cause | Fix |
|---|---|
| Managed identity not enabled on APIM | az apim update --name <apim> --resource-group <rg> --set identity.type=SystemAssigned |
| Missing RBAC role | az role assignment create --assignee <apim-principal-id> --role "Cognitive Services User" --scope <aoai-resource-id> |
| Wrong auth resource | Ensure resource="https://cognitiveservices.azure.com" (not the endpoint URL) |
| RBAC propagation delay | Wait 5-10 minutes after role assignment |
Diagnostic:
# Verify identity is enabled
az apim show --name <apim> --resource-group <rg> --query "identity" -o json
# Check role assignments
AOAI_ID=$(az cognitiveservices account show --name <aoai> --resource-group <rg> --query id -o tsv)
az role assignment list --scope "$AOAI_ID" --query "[?principalType=='ServicePrincipal'].{role:roleDefinitionName, principal:principalId}" -o tableRate Limiting Issues
429 Token Limit Exceeded
Symptom: Requests blocked with 429 Too Many Requests from azure-openai-token-limit policy.
Solutions:
Increase limit: Raise
tokens-per-minutevalueAdd more backends: Load balance across regions for higher aggregate TPM
Enable semantic caching: Reduce actual token consumption by serving cached responses
Switch counter-key: Use per-user instead of global to prevent one user from exhausting the pool
<!-- Per-user instead of global -->
<azure-openai-token-limit
tokens-per-minute="50000"
counter-key="@(context.Request.Headers.GetValueOrDefault("X-User-Id", context.Subscription.Id))"
estimate-prompt-tokens="true" />429 from Azure OpenAI (Not APIM)
Symptom: Backend returns 429 even though APIM token limits are not exceeded.
Cause: Azure OpenAI's own TPM quota is exhausted.
Solutions:
Increase Azure OpenAI deployment TPM quota in the portal
Add load balancing across multiple Azure OpenAI instances
Use retry with backoff:
<retry condition="@(context.Response.StatusCode == 429)" count="3" interval="10">
<forward-request />
</retry>Semantic Caching Issues
No Cache Hits
Symptom: Semantic cache is configured but cache hit rate is 0%.
Causes & Solutions:
| Cause | Fix |
|---|---|
score-threshold too high | Lower from 0.9 to 0.7 (more matches) |
| Embeddings backend misconfigured | Verify backend URL and auth |
| Redis not configured | Deploy Azure Cache for Redis Enterprise with RediSearch |
| Streaming requests | Semantic caching doesn't work with "stream": true |
Verify caching is working:
# Check cache-related headers in response
curl -v -X POST "${GATEWAY_URL}/openai/deployments/<deployment>/chat/completions?api-version=2024-02-01" \
-H "Content-Type: application/json" \
-H "Ocp-Apim-Subscription-Key: <key>" \
-d '{"messages": [{"role": "user", "content": "What is Azure?"}], "max_tokens": 100}'
# Look for: x-cache-status header in responseCache Returns Stale Data
Solution: Reduce duration in azure-openai-semantic-cache-store:
<!-- Shorter TTL for frequently changing knowledge -->
<azure-openai-semantic-cache-store duration="300" /> <!-- 5 minutes -->Content Safety Issues
False Positives (Legitimate Content Blocked)
Symptom: Normal business content is being blocked by content safety policy.
Solutions:
Increase thresholds (less strict):
<llm-content-safety backend-id="contentsafety-backend">
<category name="Hate" threshold="5" /> <!-- Was 4, now less strict -->
<category name="Sexual" threshold="5" />
<category name="SelfHarm" threshold="5" />
<category name="Violence" threshold="5" />
</llm-content-safety>Log blocked content for review:
<on-error>
<choose>
<when condition="@(context.LastError.Source == "llm-content-safety")">
<trace source="content-safety" severity="warning">
@{
return new JObject(
new JProperty("blocked", true),
new JProperty("subscription", context.Subscription.Id),
new JProperty("timestamp", DateTime.UtcNow)
).ToString();
}
</trace>
<return-response>
<set-status code="400" reason="Content Filtered" />
<set-body>{"error": "Content filtered by safety policy"}</set-body>
</return-response>
</when>
</choose>
</on-error>Content Safety Backend Error
Symptom: 500 error from llm-content-safety policy.
Causes:
| Cause | Fix |
|---|---|
| Content Safety resource not deployed | Deploy Azure AI Content Safety resource |
| Backend URL wrong | Check contentsafety-backend URL matches resource endpoint |
| Missing RBAC | Grant APIM "Cognitive Services User" on the Content Safety resource |
| Region mismatch | Content Safety must be in a supported region |
Backend Configuration Issues
Backend Not Found
Symptom: 500 error with "Backend not found" message.
# Verify backend exists
az apim backend list --service-name <apim> --resource-group <rg> \
--query "[].{id:name, url:url}" -o table
# Check backend ID matches policy referenceTimeout on AI Requests
Symptom: Requests timeout, especially for large context windows or complex prompts.
Solution: Increase timeout in <backend>:
<backend>
<!-- Default is 30s, increase for large AI requests -->
<forward-request timeout="120" />
</backend>Diagnostic Tools
APIM Tracing
Enable request tracing for debugging policy flow:
# Get tracing subscription key
az apim subscription list --service-name <apim> --resource-group <rg> \
--query "[?displayName=='Built-in all-access subscription'].primaryKey" -o tsv
# Send request with tracing
curl -X POST "${GATEWAY_URL}/..." \
-H "Ocp-Apim-Trace: true" \
-H "Ocp-Apim-Subscription-Key: <built-in-key>"Application Insights
If APIM is connected to Application Insights:
// Failed AI gateway requests
requests
| where success == false
| where url contains "openai"
| project timestamp, resultCode, duration, url
| order by timestamp desc
| take 20
// Token metrics over time
customMetrics
| where name == "Total Tokens"
| summarize TotalTokens = sum(value) by bin(timestamp, 1h)
| render timechart
// Content safety blocks
traces
| where message contains "content-safety"
| project timestamp, message, customDimensions
| order by timestamp descHealth Check
Quick validation that the AI Gateway is functioning:
# 1. Check APIM is running
az apim show --name <apim> --resource-group <rg> --query "provisioningState" -o tsv
# Expected: Succeeded
# 2. Check backends
az apim backend list --service-name <apim> --resource-group <rg> -o table
# 3. Test endpoint
curl -s -o /dev/null -w "%{http_code}" "${GATEWAY_URL}/openai/deployments/<deployment>/chat/completions?api-version=2024-02-01" \
-H "Ocp-Apim-Subscription-Key: <key>" \
-H "Content-Type: application/json" \
-d '{"messages": [{"role": "user", "content": "ping"}], "max_tokens": 5}'
# Expected: 200References
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs a command-line tool
The author says: Requires Azure CLI (az) for configuration and testing
Security
What our scanner noticed· Low risk
- Instructions that use the network
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills · .github/plugins/azure-skills/skills/azure-aigateway · commit 0696600
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- microsoft/azure-skills
AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-aigateway.zip