Do I need specific permissions to use this skill?

Yes, you must have an authenticated Azure MCP server configured and the necessary RBAC roles to read logs, metrics, and resource configurations.

Does this skill automatically fix Azure issues?

No, it generates a comprehensive remediation plan and provides the specific Azure CLI commands required. You review and execute these commands manually to maintain control.

How does it analyze Azure logs?

It identifies the relevant Log Analytics or Application Insights workspace and executes targeted Kusto Query Language (KQL) queries to find error patterns and anomalies.

Which Azure resources are supported for health diagnosis?

The skill supports a wide range of resources including Web Apps, Function Apps, Virtual Machines, Cosmos DB, SQL Databases, Storage Accounts, and Key Vault.

Can it help with performance tuning?

Yes, the skill analyzes performance metrics and resource utilization to identify bottlenecks and provides optimization recommendations as part of the remediation plan.

Azure Resource Health & Diagnostics

Name: Azure Resource Health & Diagnostics
Author: MoonAxis

byMoonAxis

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Infraestructura en la Nube

Analyzes Azure resource health, diagnoses performance issues using telemetry, and generates actionable remediation plans.

This skill automates the complex process of troubleshooting Azure infrastructure by integrating with Azure MCP tools and Log Analytics. It identifies resource health states across various services including Web Apps, SQL databases, and Virtual Machines, executing targeted KQL queries to uncover root causes. By streamlining the path from discovery to resolution, it provides a structured remediation report complete with Azure CLI commands, helping developers maintain high availability and resolve incidents faster.

Características Principales

01Automated root cause identification and issue classification

02Automated health assessment for diverse Azure resource types

03Integration with Azure MCP best practices for standardized troubleshooting

04Comprehensive remediation reports with prioritized action items

05Deep-dive log analysis using pre-configured KQL queries

062 GitHub stars

Casos de Uso

01Investigating production downtime or performance degradation in Azure App Services

02Analyzing system logs and boot diagnostics for troubleshooting Virtual Machine failures

03Diagnosing failed database connections and query timeouts in SQL or Cosmos DB

Características Principales

01Automated root cause identification and issue classification

02Automated health assessment for diverse Azure resource types

03Integration with Azure MCP best practices for standardized troubleshooting

04Comprehensive remediation reports with prioritized action items

05Deep-dive log analysis using pre-configured KQL queries

062 GitHub stars

Casos de Uso

01Investigating production downtime or performance degradation in Azure App Services

02Analyzing system logs and boot diagnostics for troubleshooting Virtual Machine failures

03Diagnosing failed database connections and query timeouts in SQL or Cosmos DB