azure-resource-health-diagnose

by github40k

Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems.

Install

The skill file stays in the publisher's repository.

Paste the copied command in a terminal. It installs this SKILL.md into that agent.

npx skills add github/awesome-copilot --skill azure-resource-health-diagnose -a cursor -y

Download skill skills/azure-resource-health-diagnose/SKILL.md on GitHub

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acquire-codebase-knowledgeUse this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this rep

Questions

How do I install azure-resource-health-diagnose?: Download skills/azure-resource-health-diagnose/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does azure-resource-health-diagnose live?: The publisher keeps it at https://github.com/github/awesome-copilot.
Which agents can use azure-resource-health-diagnose?: Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.

name: azure-resource-health-diagnose description: 'Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems.'

Azure Resource Health & Issue Diagnosis

This workflow analyzes a specific Azure resource to assess its health status, diagnose potential issues using logs and telemetry data, and develop a comprehensive remediation plan for any problems discovered.

Prerequisites

Azure MCP server configured and authenticated
Target Azure resource identified (name and optionally resource group/subscription)
Resource must be deployed and running to generate logs/telemetry

🏥 Azure Resource Health Assessment 📊 Resource Overview: • Resource: [Name] ([Type]) • Status: [Healthy/Warning/Critical] • Location: [Region] • Last Analyzed: [Timestamp] 🚨 Issues Identified: • Critical: X issues requiring immediate attention • High: Y issues affecting performance/reliability • Medium: Z issues for optimization • Low: N informational items 🔍 Top Issues: 1. [Issue Type]: [Description] - Impact: [High/Medium/Low] 2. [Issue Type]: [Description] - Impact: [High/Medium/Low] 3. [Issue Type]: [Description] - Impact: [High/Medium/Low] 🛠️ Remediation Plan: • Immediate Actions: X items • Short-term Fixes: Y items • Long-term Improvements: Z items • Estimated Resolution Time: [Timeline] ❓ Proceed with detailed remediation plan? (y/n)

# Azure Resource Health Report: [Resource Name] **Generated**: [Timestamp] **Resource**: [Full Resource ID] **Overall Health**: [Status with color indicator] ## 🔍 Executive Summary [Brief overview of health status and key findings] ## 📊 Health Metrics - **Availability**: X% over last 24h - **Performance**: [Average response time/throughput] - **Error Rate**: X% over last 24h - **Resource Utilization**: [CPU/Memory/Storage percentages] ## 🚨 Issues Identified ### Critical Issues - **[Issue 1]**: [Description] - **Root Cause**: [Analysis] - **Impact**: [Business impact] - **Immediate Action**: [Required steps] ### High Priority Issues - **[Issue 2]**: [Description] - **Root Cause**: [Analysis] - **Impact**: [Performance/reliability impact] - **Recommended Fix**: [Solution steps] ## 🛠️ Remediation Plan ### Phase 1: Immediate Actions (0-2 hours) ```bash # Critical fixes to restore service [Azure CLI commands with explanations]

azure-resource-health-diagnose

Install

Related skills

Questions

name: azure-resource-health-diagnose description: 'Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems.'

Azure Resource Health & Issue Diagnosis

Prerequisites

Workflow Steps

Step 1: Get Azure Best Practices

Step 2: Resource Discovery & Identification

Step 3: Health Status Assessment

Step 4: Log & Telemetry Analysis

Step 5: Issue Classification & Root Cause Analysis

Step 6: Generate Remediation Plan

Step 7: User Confirmation & Report Generation

Phase 2: Short-term Fixes (2-24 hours)

Phase 3: Long-term Improvements (1-4 weeks)

📈 Monitoring Recommendations

✅ Validation Steps

📝 Prevention Measures

Error Handling

Success Criteria