Apim Kql

APIM KQL Skill

Guide for creating Kusto Query Language (KQL) queries for Azure API Management monitoring data in Azure Monitor.

Quick Start

Basic Gateway Logs Query

ApiManagementGatewayLogs
| where TimeGenerated > ago(1h)
| project TimeGenerated, Method, Url, ResponseCode, TotalTime, BackendTime, CallerIpAddress
| order by TimeGenerated desc
| take 100

LLM Token Usage Query

ApiManagementGatewayLlmLog
| where TimeGenerated > ago(24h)
| summarize 
    TotalPromptTokens = sum(PromptTokens),
    TotalCompletionTokens = sum(CompletionTokens),
    TotalTokens = sum(TotalTokens)
by DeploymentName, ModelName

Tables Overview

For complete table schemas, see references/table-schemas.md.

Essential Query Patterns

Joining LLM Logs with Gateway Logs

let llmLogs = ApiManagementGatewayLlmLog 
| where DeploymentName != '';

let logsWithSubscription = llmLogs 
| join kind=leftouter ApiManagementGatewayLogs on CorrelationId 
| project 
    SubscriptionId = ApimSubscriptionId, 
    DeploymentName, 
    ModelName,
    PromptTokens, 
    CompletionTokens, 
    TotalTokens;

logsWithSubscription 
| summarize 
    SumPromptTokens = sum(PromptTokens), 
    SumCompletionTokens = sum(CompletionTokens), 
    SumTotalTokens = sum(TotalTokens) 
by SubscriptionId, DeploymentName

Error Analysis

ApiManagementGatewayLogs
| where TimeGenerated > ago(24h)
| where ResponseCode >= 400
| summarize ErrorCount = count() by ResponseCode, ApiId, LastErrorReason
| order by ErrorCount desc

Request Latency Analysis

ApiManagementGatewayLogs
| where TimeGenerated > ago(1h)
| summarize 
    AvgTotalTime = avg(TotalTime),
    AvgBackendTime = avg(BackendTime),
    P95TotalTime = percentile(TotalTime, 95),
    RequestCount = count()
by bin(TimeGenerated, 5m), ApiId
| order by TimeGenerated desc

Backend Performance

ApiManagementGatewayLogs
| where TimeGenerated > ago(1h)
| where BackendId != ""
| summarize 
    AvgBackendTime = avg(BackendTime),
    MaxBackendTime = max(BackendTime),
    ErrorCount = countif(BackendResponseCode >= 400),
    TotalRequests = count()
by BackendId
| order by AvgBackendTime desc

Token Usage by Time

ApiManagementGatewayLlmLog
| where TimeGenerated > ago(7d)
| summarize 
    TotalTokens = sum(TotalTokens),
    PromptTokens = sum(PromptTokens),
    CompletionTokens = sum(CompletionTokens)
by bin(TimeGenerated, 1h), DeploymentName
| order by TimeGenerated desc

MCP Tool Usage

ApiManagementGatewayMCPLog
| where TimeGenerated > ago(24h)
| summarize 
    CallCount = count(),
    UniqueClients = dcount(ClientName)
by ToolName, ServerName, Method
| order by CallCount desc

WebSocket Connection Events

ApiManagementWebSocketConnectionLogs
| where TimeGenerated > ago(1h)
| summarize 
    EventCount = count()
by EventName, Source, Destination
| order by EventCount desc

KQL Operators Reference

Filtering

| where TimeGenerated > ago(1h)
| where ResponseCode == 200
| where ApiId contains "openai"
| where isnotempty(BackendId)

Aggregation

| summarize count() by ApiId
| summarize avg(TotalTime), percentile(TotalTime, 95) by ApiId
| summarize sum(TotalTokens) by DeploymentName
| summarize dcount(CallerIpAddress) by bin(TimeGenerated, 1h)

Time Functions

| where TimeGenerated > ago(1h)
| where TimeGenerated between (datetime(2024-01-01) .. datetime(2024-01-31))
| where TimeGenerated >= startofmonth(now()) and TimeGenerated <= endofmonth(now())
| summarize ... by bin(TimeGenerated, 5m)

Joins

| join kind=leftouter OtherTable on CorrelationId
| join kind=inner OtherTable on $left.Field1 == $right.Field2

Projections

| project TimeGenerated, Method, Url, ResponseCode
| project-away _BilledSize, _IsBillable
| extend Duration = TotalTime - BackendTime
| extend IsError = ResponseCode >= 400

Ordering and Limiting

| order by TimeGenerated desc
| take 100
| top 10 by TotalTime desc

Common Scenarios

Daily Request Summary

ApiManagementGatewayLogs
| where TimeGenerated > ago(7d)
| summarize 
    TotalRequests = count(),
    SuccessfulRequests = countif(ResponseCode < 400),
    FailedRequests = countif(ResponseCode >= 400),
    AvgLatency = avg(TotalTime)
by bin(TimeGenerated, 1d), ApiId
| extend SuccessRate = round(100.0 * SuccessfulRequests / TotalRequests, 2)
| order by TimeGenerated desc

Top Consumers by Token Usage

let llmLogs = ApiManagementGatewayLlmLog 
| where TimeGenerated > ago(30d);

llmLogs 
| join kind=leftouter ApiManagementGatewayLogs on CorrelationId 
| summarize 
    TotalTokens = sum(TotalTokens),
    RequestCount = count()
by ApimSubscriptionId
| top 10 by TotalTokens desc

Error Rate Over Time

ApiManagementGatewayLogs
| where TimeGenerated > ago(24h)
| summarize 
    Total = count(),
    Errors = countif(ResponseCode >= 400)
by bin(TimeGenerated, 1h)
| extend ErrorRate = round(100.0 * Errors / Total, 2)
| project TimeGenerated, Total, Errors, ErrorRate
| order by TimeGenerated desc

Cache Hit Analysis

ApiManagementGatewayLogs
| where TimeGenerated > ago(24h)
| where Cache != ""
| summarize 
    HitCount = countif(Cache == "hit"),
    MissCount = countif(Cache == "miss")
by ApiId
| extend HitRate = round(100.0 * HitCount / (HitCount + MissCount), 2)

Streaming vs Non-Streaming LLM Requests

ApiManagementGatewayLlmLog
| where TimeGenerated > ago(24h)
| summarize 
    StreamingRequests = countif(IsStreamCompletion == true),
    NonStreamingRequests = countif(IsStreamCompletion == false),
    AvgTokens = avg(TotalTokens)
by DeploymentName

Running KQL Queries

Azure CLI

az monitor log-analytics query \
  -w <workspace-id> \
  --analytics-query "ApiManagementGatewayLogs | take 10"

Python

query = """
ApiManagementGatewayLogs
| where TimeGenerated > ago(1h)
| take 100
"""
result = utils.run(f'az monitor log-analytics query -w {workspace_id} --analytics-query "{query}"')

Best Practices

1. Always filter by time - Use where TimeGenerated > ago(...) to limit data scanned
2. Use summarize early - Aggregate data before joins when possible
3. Project only needed columns - Reduce data transfer with explicit projections
4. Use let statements - Break complex queries into readable parts
5. Join on CorrelationId - Link APIM tables together using this common key
6. Use bin() for time series - Group time data into meaningful intervals

References

• references/table-schemas.md - Complete table column definitions
• references/query-examples.md - Additional query examples from this repository