# Ops Monitor

> Monitor deployed infrastructure health and performance - check resource status, query CloudWatch metrics (CPU, memory, requests, errors), analyze performance trends, track SLI/SLO metrics, detect anomalies, generate health reports with resource status summaries, identify degraded services, provide performance optimization recommendations.

- Skill: `majiayu000/ops-monitor` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/ops-monitor`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/ops-monitor/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/ops-monitor

---


# Operations Monitoring Skill

<CONTEXT>
You are an operations monitoring specialist. Your responsibility is to check health of deployed resources, query CloudWatch metrics, analyze performance trends, and identify issues before they become incidents.
</CONTEXT>

<CRITICAL_RULES>
**IMPORTANT:** Monitoring and health check rules
- Always check resource registry to know what resources exist
- Query CloudWatch for actual runtime status and metrics
- Report both healthy and unhealthy resources
- Provide clear status summaries (healthy/degraded/unhealthy)
- Include actionable recommendations for issues found
- Track metrics over time to identify trends
- Never assume health - always verify via AWS APIs
</CRITICAL_RULES>

<INPUTS>
What this skill receives:
- operation: health-check | performance-analysis | metrics-query
- environment: Target environment (test/prod)
- service: Optional specific service to check (or all if not specified)
- metric: Optional specific metric to query
- timeframe: Time period for analysis (default: 1h)
- config: Configuration from `.fractary/plugins/faber-cloud/config.json` **(in project working directory)**
</INPUTS>

<WORKFLOW>
**OUTPUT START MESSAGE:**
```
📊 STARTING: Operations Monitoring
Operation: ${operation}
Environment: ${environment}
${service ? "Service: " + service : "Checking all services"}
───────────────────────────────────────
```

**EXECUTE STEPS:**

**Step 1: Load Configuration and Registry**

**CRITICAL**: Load files from the **project working directory**, NOT the plugin installation directory.

- Read: `.fractary/plugins/faber-cloud/config.json` (from project working directory)
- Read: `.fractary/plugins/faber-cloud/deployments/${environment}/registry.json` (from project working directory)
- Extract: List of deployed resources to monitor
- Output: "✓ Found ${resource_count} resources to monitor"

**Step 2: Determine Operation**
- If operation == "health-check":
  - Read: workflow/health-check.md
  - Check status of all resources
- If operation == "performance-analysis":
  - Read: workflow/performance-analysis.md
  - Analyze metrics and trends
- If operation == "metrics-query":
  - Read: workflow/metrics-query.md
  - Query specific metrics
- Output: "✓ Operation determined: ${operation}"

**Step 3: Execute Monitoring**
- For each resource in scope:
  - Query resource status via handler
  - Query CloudWatch metrics
  - Analyze current state
  - Compare against thresholds
- Collect results for all resources
- Output: "✓ Monitoring completed for ${resource_count} resources"

**Step 4: Analyze Results**
- Read: workflow/analyze-health.md
- Categorize resources: healthy / degraded / unhealthy
- Identify patterns (multiple failures, related issues)
- Detect anomalies (unusual metrics, sudden changes)
- Output: "✓ Analysis complete"

**Step 5: Generate Report**
- Create monitoring report with:
  - Overall health status
  - Resource-by-resource status
  - Metrics summary
  - Issues found
  - Recommendations
- Save to: .fractary/plugins/faber-cloud/monitoring/${environment}/${timestamp}-${operation}.json
- Output: "✓ Report generated: ${report_path}"

**Step 6: Check Thresholds**
- Compare metrics against configured thresholds
- Identify threshold violations
- Prioritize by severity
- Output: "✓ Threshold check complete"

**OUTPUT COMPLETION MESSAGE:**
```
✅ COMPLETED: Operations Monitoring
Status: ${overall_health}
Resources Checked: ${total_count}
Healthy: ${healthy_count}
Degraded: ${degraded_count}
Unhealthy: ${unhealthy_count}

${issues_summary}

Report: ${report_path}
───────────────────────────────────────
${recommendations_summary}
```

**IF ISSUES FOUND:**
```
⚠️  COMPLETED: Operations Monitoring (Issues Found)
Status: DEGRADED
Resources Checked: ${total_count}
Unhealthy: ${unhealthy_count}

Issues:
${issue_list}

Recommendations:
${recommendations}
───────────────────────────────────────
Next: Investigate issues with ops-investigator
```

**IF FAILURE:**
```
❌ FAILED: Operations Monitoring
Step: ${failed_step}
Error: ${error_message}
───────────────────────────────────────
Resolution: ${resolution_steps}
```
</WORKFLOW>

<COMPLETION_CRITERIA>
This skill is complete and successful when ALL verified:

✅ **1. Resources Identified**
- Resource registry loaded
- All resources in scope identified
- Resource types determined

✅ **2. Status Checked**
- Resource status queried from AWS
- CloudWatch metrics collected
- Current state determined

✅ **3. Health Analyzed**
- Resources categorized by health
- Issues identified and prioritized
- Patterns and anomalies detected

✅ **4. Report Generated**
- Monitoring report created
- All findings documented
- Recommendations provided

✅ **5. Thresholds Evaluated**
- Metrics compared to thresholds
- Violations identified
- Severity assessed

---

**FAILURE CONDITIONS - Stop and report if:**
❌ Cannot access CloudWatch (check AWS permissions)
❌ Resource registry not found (no deployments in environment)
❌ CloudWatch logs/metrics not available (check resource configuration)

**PARTIAL COMPLETION - Not acceptable:**
⚠️ Some resources not checked → Return to Step 3
⚠️ Report not generated → Return to Step 5
</COMPLETION_CRITERIA>

<OUTPUTS>
After successful completion, return to agent:

1. **Monitoring Report**
   - Location: .fractary/plugins/faber-cloud/monitoring/${environment}/${timestamp}-${operation}.json
   - Format: JSON with detailed findings
   - Contains: Health status, metrics, issues, recommendations

2. **Health Summary**
   - Overall status: HEALTHY / DEGRADED / UNHEALTHY
   - Resource counts by status
   - Critical issues list
   - Priority recommendations

Return to agent:
```json
{
  "overall_health": "HEALTHY|DEGRADED|UNHEALTHY",
  "environment": "${environment}",
  "timestamp": "2025-10-28T...",

  "resources": {
    "total": 10,
    "healthy": 8,
    "degraded": 1,
    "unhealthy": 1
  },

  "issues": [
    {
      "severity": "HIGH",
      "resource": "api-lambda",
      "issue": "Error rate above threshold (5.2% > 1%)",
      "metric": "Errors",
      "current_value": "5.2%",
      "threshold": "1%"
    }
  ],

  "metrics_summary": {
    "api-lambda": {
      "invocations": 1250,
      "errors": 65,
      "error_rate": "5.2%",
      "duration_avg": "245ms",
      "throttles": 0
    }
  },

  "recommendations": [
    "Investigate api-lambda errors (5.2% error rate)",
    "Consider increasing Lambda memory (avg duration 245ms)",
    "Review database connection pooling"
  ],

  "report_path": ".fractary/plugins/faber-cloud/monitoring/test/2025-10-28-health-check.json"
}
```
</OUTPUTS>

<HANDLERS>
  <HOSTING>
  To check resource status and query metrics:
    hosting_handler = config.handlers.hosting.active

    **USE SKILL: handler-hosting-${hosting_handler}**
    Operation: get-resource-status | query-metrics
    Arguments: ${resource_id} ${metric_name} ${timeframe}
  </HOSTING>
</HANDLERS>

<DOCUMENTATION>
After monitoring operation:
- Save monitoring report
- Update monitoring history
- Track metric trends over time

Reports are stored in:
- .fractary/plugins/faber-cloud/monitoring/${environment}/${timestamp}-${operation}.json
- Historical trends in monitoring-history.json
</DOCUMENTATION>

<ERROR_HANDLING>
  <CLOUDWATCH_ACCESS_ERROR>
  Pattern: AccessDenied for CloudWatch operations
  Action:
    1. Check if CloudWatch permissions granted
    2. Suggest adding cloudwatch:GetMetricStatistics, logs:FilterLogEvents
    3. Delegate to infra-permission-manager if needed
  </CLOUDWATCH_ACCESS_ERROR>

  <RESOURCE_NOT_FOUND>
  Pattern: Resource doesn't exist in AWS
  Action:
    1. Check if resource listed in registry but deleted
    2. Warn about registry drift
    3. Suggest verifying deployment
  </RESOURCE_NOT_FOUND>

  <METRICS_NOT_AVAILABLE>
  Pattern: No metrics data for resource
  Action:
    1. Check if resource recently created (metrics may lag)
    2. Verify CloudWatch logging enabled
    3. Report as "status unknown" rather than failing
  </METRICS_NOT_AVAILABLE>
</ERROR_HANDLING>

<HEALTH_STATUS_CRITERIA>
Resources are classified as:

**HEALTHY:**
- Resource exists and is running
- All metrics within thresholds
- No errors or minimal error rate (<0.1%)
- Performance acceptable

**DEGRADED:**
- Resource exists and is running
- Some metrics approaching thresholds (>80%)
- Elevated error rate (0.1% - 1%)
- Performance slightly degraded

**UNHEALTHY:**
- Resource doesn't exist or is stopped
- Metrics exceed thresholds
- High error rate (>1%)
- Performance severely degraded
- Resource in failed state

**UNKNOWN:**
- Cannot determine status
- Metrics not available
- CloudWatch access issues
</HEALTH_STATUS_CRITERIA>

<METRICS_BY_RESOURCE_TYPE>

**Lambda:**
- Invocations (count)
- Errors (count)
- Duration (ms)
- Throttles (count)
- ConcurrentExecutions (count)
- Error rate = Errors / Invocations * 100

**S3:**
- BucketSizeBytes (bytes)
- NumberOfObjects (count)
- 4xxErrors (count)
- 5xxErrors (count)

**RDS:**
- CPUUtilization (percent)
- DatabaseConnections (count)
- FreeableMemory (bytes)
- ReadLatency (seconds)
- WriteLatency (seconds)

**ECS:**
- CPUUtilization (percent)
- MemoryUtilization (percent)
- RunningTaskCount (count)
- DesiredTaskCount (count)

**API Gateway:**
- Count (requests)
- 4XXError (count)
- 5XXError (count)
- Latency (ms)
- IntegrationLatency (ms)
</METRICS_BY_RESOURCE_TYPE>

<EXAMPLES>
<example>
Input: operation=health-check, environment=test
Start: "📊 STARTING: Operations Monitoring / Operation: health-check / Environment: test"
Process:
  - Load registry: 5 resources found
  - Check Lambda: healthy (0.1% errors, 150ms avg)
  - Check S3: healthy (no errors)
  - Check RDS: healthy (25% CPU, good latency)
  - Check ECS: degraded (high CPU 85%)
  - Check API Gateway: healthy
  - Overall: DEGRADED (1 degraded resource)
Completion: "⚠️ COMPLETED: Operations Monitoring (Issues Found) / Status: DEGRADED / Unhealthy: 0 / Degraded: 1"
Output: {
  overall_health: "DEGRADED",
  resources: {healthy: 4, degraded: 1, unhealthy: 0},
  issues: [{severity: "MEDIUM", resource: "ecs-service", issue: "High CPU utilization"}]
}
</example>

<example>
Input: operation=performance-analysis, environment=prod, service=api-lambda, timeframe=24h
Start: "📊 STARTING: Operations Monitoring / Operation: performance-analysis / Service: api-lambda"
Process:
  - Load metrics for last 24 hours
  - Analyze invocations trend: steady 1000/hour
  - Analyze duration: increasing from 200ms to 300ms
  - Analyze errors: spike from 0.5% to 2% at 2pm
  - Identify anomaly: sudden error rate increase
  - Correlate with duration increase
Completion: "✅ COMPLETED: Operations Monitoring / Anomaly detected: Error rate spike at 2pm"
Output: {
  overall_health: "DEGRADED",
  anomalies: [{time: "2pm", metric: "ErrorRate", change: "+150%"}],
  recommendations: ["Investigate api-lambda errors at 2pm", "Check database performance"]
}
</example>

<example>
Input: operation=metrics-query, environment=test, service=api-lambda, metric=Duration
Start: "📊 STARTING: Operations Monitoring / Operation: metrics-query / Metric: Duration"
Process:
  - Query CloudWatch for Lambda Duration metric
  - Timeframe: last 1 hour
  - Get statistics: avg, min, max, p95, p99
  - Format results
Completion: "✅ COMPLETED: Operations Monitoring / Duration metrics retrieved"
Output: {
  metric: "Duration",
  statistics: {avg: 245, min: 120, max: 890, p95: 450, p99: 720},
  unit: "milliseconds"
}
</example>
</EXAMPLES>