azure-resource-health-diagnose skill

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
• Prefer Azure MCP tools (azmcp-*) over direct Azure CLI when available

Workflow Steps

Step 1: Get Azure Best Practices

Action: Retrieve diagnostic and troubleshooting best practices Tools: Azure MCP best practices tool Process:

1. Load Best Practices:

• Execute Azure best practices tool to get diagnostic guidelines
• Focus on health monitoring, log analysis, and issue resolution patterns
• Use these practices to inform diagnostic approach and remediation recommendations

Step 2: Resource Discovery & Identification

Action: Locate and identify the target Azure resource Tools: Azure MCP tools + Azure CLI fallback Process:

1. Resource Lookup:

• If only resource name provided: Search across subscriptions using azmcp-subscription-list
• Use az resource list --name to find matching resources
• If multiple matches found, prompt user to specify subscription/resource group
• Gather detailed resource information:
• Resource type and current status
• Location, tags, and configuration
• Associated services and dependencies

1. Resource Type Detection:

• Identify resource type to determine appropriate diagnostic approach:
• Web Apps/Function Apps: Application logs, performance metrics, dependency tracking
• Virtual Machines: System logs, performance counters, boot diagnostics
• Cosmos DB: Request metrics, throttling, partition statistics
• Storage Accounts: Access logs, performance metrics, availability
• SQL Database: Query performance, connection logs, resource utilization
• Application Insights: Application telemetry, exceptions, dependencies
• Key Vault: Access logs, certificate status, secret usage
• Service Bus: Message metrics, dead letter queues, throughput

Step 3: Health Status Assessment

Action: Evaluate current resource health and availability Tools: Azure MCP monitoring tools + Azure CLI Process:

1. Basic Health Check:

• Check resource provisioning state and operational status
• Verify service availability and responsiveness
• Review recent deployment or configuration changes
• Assess current resource utilization (CPU, memory, storage, etc.)

1. Service-Specific Health Indicators:

• Web Apps: HTTP response codes, response times, uptime
• Databases: Connection success rate, query performance, deadlocks
• Storage: Availability percentage, request success rate, latency
• VMs: Boot diagnostics, guest OS metrics, network connectivity
• Functions: Execution success rate, duration, error frequency

Step 4: Log & Telemetry Analysis

Action: Analyze logs and telemetry to identify issues and patterns Tools: Azure MCP monitoring tools for Log Analytics queries Process:

1. Find Monitoring Sources:

• Use azmcp-monitor-workspace-list to identify Log Analytics workspaces
• Locate Application Insights instances associated with the resource
• Identify relevant log tables using azmcp-monitor-table-list

Use azmcp-monitor-log-query with targeted KQL queries based on resource type:

1. Execute Diagnostic Queries:

General Error Analysis:

// Recent errors and exceptions
   union isfuzzy=true 
       AzureDiagnostics,
       AppServiceHTTPLogs,
       AppServiceAppLogs,
       AzureActivity
   | where TimeGenerated > ago(24h)
   | where Level == "Error" or ResultType != "Success"
   | summarize ErrorCount=count() by Resource, ResultType, bin(TimeGenerated, 1h)
   | order by TimeGenerated desc

Performance Analysis:

// Performance degradation patterns
   Perf
   | where TimeGenerated > ago(7d)
   | where ObjectName == "Processor" and CounterName == "% Processor Time"
   | summarize avg(CounterValue) by Computer, bin(TimeGenerated, 1h)
   | where avg_CounterValue > 80

Application-Specific Queries:

// Application Insights - Failed requests
   requests
   | where timestamp > ago(24h)
   | where success == false
   | summarize FailureCount=count() by resultCode, bin(timestamp, 1h)
   | order by timestamp desc
   
   // Database - Connection failures
   AzureDiagnostics
   | where ResourceProvider == "MICROSOFT.SQL"
   | where Category == "SQLSecurityAuditEvents"
   | where action_name_s == "CONNECTION_FAILED"
   | summarize ConnectionFailures=count() by bin(TimeGenerated, 1h)

1. Pattern Recognition:

• Identify recurring error patterns or anomalies
• Correlate errors with deployment times or configuration changes
• Analyze performance trends and degradation patterns
• Look for dependency failures or external service issues

Step 5: Issue Classification & Root Cause Analysis

Action: Categorize identified issues and determine root causes Process:

1. Issue Classification:

• Critical: Service unavailable, data loss, security breaches
• High: Performance degradation, intermittent failures, high error rates
• Medium: Warnings, suboptimal configuration, minor performance issues
• Low: Informational alerts, optimization opportunities

1. Root Cause Analysis:

• Configuration Issues: Incorrect settings, missing dependencies
• Resource Constraints: CPU/memory/disk limitations, throttling
• Network Issues: Connectivity problems, DNS resolution, firewall rules
• Application Issues: Code bugs, memory leaks, inefficient queries
• External Dependencies: Third-party service failures, API limits
• Security Issues: Authentication failures, certificate expiration

1. Impact Assessment:

• Determine business impact and affected users/systems
• Evaluate data integrity and security implications
• Assess recovery time objectives and priorities

Step 6: Generate Remediation Plan

Action: Create a comprehensive plan to address identified issues Process:

1. Immediate Actions (Critical issues):

• Emergency fixes to restore service availability
• Temporary workarounds to mitigate impact
• Escalation procedures for complex issues

1. Short-term Fixes (High/Medium issues):

• Configuration adjustments and resource scaling
• Application updates and patches
• Monitoring and alerting improvements

1. Long-term Improvements (All issues):

• Architectural changes for better resilience
• Preventive measures and monitoring enhancements
• Documentation and process improvements

1. Implementation Steps:

• Prioritized action items with specific Azure CLI commands
• Testing and validation procedures
• Rollback plans for each change
• Monitoring to verify issue resolution

Step 7: User Confirmation & Report Generation

Action: Present findings and get approval for remediation actions Process:

1. Display Health Assessment Summary:

🏥 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)

1. Generate Detailed Report:

# 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)

# Critical fixes to restore service [Azure CLI commands with explanations]