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azure-observability

microsoft/azure-skills

Query metrics, logs, and traces across Azure Monitor, Application Insights, and Log Analytics.

What is azure-observability?

Azure Observability Services skill provides access to Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks for monitoring infrastructure, application performance, and security. Use this to query metrics and logs with KQL, set up alerts, create interactive dashboards, and analyze distributed traces.

Query metrics from Azure Monitor using the monitor_metrics_query tool
Execute KQL queries against Log Analytics workspaces via monitor_logs_query
List and manage Application Insights resources for APM and distributed tracing
Create and manage Workbooks for interactive monitoring reports
Configure alerts and notifications for Azure resources
Analyze application exceptions, request performance, and resource usage

How to install azure-observability

npx skills add https://github.com/microsoft/azure-skills --skill azure-observability

Prerequisites

Azure subscription with Azure Monitor, Application Insights, or Log Analytics resources deployed
Azure CLI installed and authenticated, or Azure MCP enabled in your agent
Log Analytics workspace ID or Application Insights resource ID for queries

Claude Code

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How to use azure-observability

1.Enable Azure MCP via `/mcp` or run `/azure:setup` if not already configured
2.List available Log Analytics workspaces with `az monitor log-analytics workspace list`
3.Execute KQL queries using the `kusto_query` tool or `az monitor log-analytics query` CLI command
4.Query metrics from Azure Monitor using `monitor_metrics_query` with resource ID and metric name
5.Create alerts using `az monitor alert` CLI or configure Workbooks for interactive reports

Use cases

Good for

Query application error rates and stack traces from the past hour to diagnose failures
Summarize average response times and request counts by endpoint to identify performance bottlenecks
Monitor CPU and memory usage across infrastructure resources to detect capacity issues
Create interactive dashboards combining metrics, logs, and traces for incident response
Set up alerts on failed requests or high latency to notify teams automatically

Who it's for

DevOps engineers managing Azure infrastructure monitoring
Application developers analyzing APM data and distributed traces
SREs investigating incidents and creating observability dashboards
Cloud architects designing monitoring strategies for Azure workloads

azure-observability FAQ

What's the difference between this skill and appinsights-instrumentation?

This skill queries and analyzes existing monitoring data. Use appinsights-instrumentation to instrument your application code with the App Insights SDK.

Can I query Kusto/ADX clusters with this skill?

No, use the azure-kusto skill for querying dedicated Kusto clusters. This skill queries Log Analytics workspaces only.

How do I write KQL queries for common scenarios?

The skill includes example KQL queries for errors, request performance, and resource usage. See the Common KQL Queries section in the documentation.

Do I need to enable Azure MCP to use this skill?

MCP is preferred for full functionality. If not enabled, you can use Azure CLI commands instead via `az monitor` and `az monitor log-analytics` commands.

Can this skill help with cost analysis?

No, use the azure-cost-optimization skill for cost analysis and budget alerts. This skill focuses on performance, errors, and infrastructure monitoring.

Full instructions (SKILL.md)

Source of truth, from microsoft/azure-skills.

name: azure-observability description: "Azure Observability Services including Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks. Provides metrics, APM, distributed tracing, KQL queries, and interactive reports. USE FOR: Azure Monitor, Application Insights, Log Analytics, Alerts, Workbooks, metrics, APM, distributed tracing, KQL queries, interactive reports, observability, monitoring dashboards. DO NOT USE FOR: instrumenting apps with App Insights SDK (use appinsights-instrumentation), querying Kusto/ADX clusters (use azure-kusto), cost analysis (use azure-cost-optimization)." license: MIT metadata: author: Microsoft version: "1.0.0"

Azure Observability Services

Services

Service	Use When	MCP Tools	CLI
Azure Monitor	Metrics, alerts, dashboards	`azure__monitor`	`az monitor`
Application Insights	APM, distributed tracing	`azure__applicationinsights`	`az monitor app-insights`
Log Analytics	Log queries, KQL	`azure__kusto`	`az monitor log-analytics`
Alerts	Notifications, actions	-	`az monitor alert`
Workbooks	Interactive reports	`azure__workbooks`	-

MCP Server (Preferred)

When Azure MCP is enabled:

Monitor

azure__monitor with command monitor_metrics_query - Query metrics
azure__monitor with command monitor_logs_query - Query logs with KQL

Application Insights

azure__applicationinsights with command applicationinsights_component_list - List App Insights resources

Log Analytics

azure__kusto with command kusto_cluster_list - List clusters
azure__kusto with command kusto_query - Execute KQL queries

If Azure MCP is not enabled: Run /azure:setup or enable via /mcp.

CLI Reference

# List Log Analytics workspaces
az monitor log-analytics workspace list --output table

# Query logs with KQL
az monitor log-analytics query \
  --workspace WORKSPACE_ID \
  --analytics-query "AzureActivity | take 10"

# List Application Insights
az monitor app-insights component list --output table

# List alerts
az monitor alert list --output table

# Query metrics
az monitor metrics list \
  --resource RESOURCE_ID \
  --metric "Percentage CPU"

Common KQL Queries

// Recent errors
AppExceptions
| where TimeGenerated > ago(1h)
| project TimeGenerated, Message, StackTrace
| order by TimeGenerated desc

// Request performance
AppRequests
| where TimeGenerated > ago(1h)
| summarize avg(DurationMs), count() by Name
| order by avg_DurationMs desc

// Resource usage
AzureMetrics
| where TimeGenerated > ago(1h)
| where MetricName == "Percentage CPU"
| summarize avg(Average) by Resource

Monitoring Strategy

What to Monitor	Service	Metric/Log
Application errors	App Insights	Exceptions, failed requests
Performance	App Insights	Response time, dependencies
Infrastructure	Azure Monitor	CPU, memory, disk
Security	Log Analytics	Sign-ins, audit logs
Costs	Cost Management	Budget alerts

SDK Quick References

For programmatic access to monitoring services, see the condensed SDK guides:

OpenTelemetry: Python | TypeScript | Python Exporter
Monitor Query: Python | Java
Log Ingestion: Python | Java
App Insights Mgmt: .NET

Service Details

For deep documentation on specific services:

Application Insights setup -> appinsights-instrumentation skill
KQL query patterns -> Log Analytics KQL documentation
Alert configuration -> Azure Monitor alerts documentation

Azure Storage skill: Blob, File Shares, Queue, Table, and Data Lake with access tier guidance and lifecycle management

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