azure-resource-health-diagnose（Azure resource health diagnose 问题管理）

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 <resource-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

1. Execute Diagnostic Queries: Use azmcp-monitor-log-query with targeted KQL queries based on resource type: 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)
2. 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)
2. 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) `bash # Critical fixes to restore service [Azure CLI commands with explanations] `` Phase 2: Short-term Fixes (2-24 hours) # Performance and reliability improvements [Azure CLI commands with explanations] Phase 3: Long-term Improvements (1-4 weeks) # Architectural and preventive measures [Azure CLI commands and configuration changes] 📈 Monitoring Recommendations ✅ Validation Steps 📝 Prevention Measures `

- Alerts to Configure: [List of recommended alerts] - Dashboards to Create: [Monitoring dashboard suggestions] - Regular Health Checks: [Recommended frequency and scope] - Verify issue resolution through logs - Confirm performance improvements - Test application functionality - Update monitoring and alerting - Document lessons learned - [Recommendations to prevent similar issues] - [Process improvements] - [Monitoring enhancements]

Error Handling

• Resource Not Found: Provide guidance on resource name/location specification
• Authentication Issues: Guide user through Azure authentication setup
• Insufficient Permissions: List required RBAC roles for resource access
• No Logs Available: Suggest enabling diagnostic settings and waiting for data
• Query Timeouts: Break down analysis into smaller time windows
• Service-Specific Issues: Provide generic health assessment with limitations noted

Success Criteria

• ✅ Resource health status accurately assessed
• ✅ All significant issues identified and categorized
• ✅ Root cause analysis completed for major problems
• ✅ Actionable remediation plan with specific steps provided
• ✅ Monitoring and prevention recommendations included
• ✅ Clear prioritization of issues by business impact
• ✅ Implementation steps include validation and rollback procedures