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monitoring-analytics

Monitor Proxmox infrastructure health and performance. Track node statistics, analyze resource utilization, and identify optimization opportunities across your cluster.

231 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/monitoring-analytics/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/dataknifeai/monitoring-analytics/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/monitoring-analytics/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How monitoring-analytics Compares

Feature / Agentmonitoring-analyticsStandard Approach
Platform SupportmultiLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Monitor Proxmox infrastructure health and performance. Track node statistics, analyze resource utilization, and identify optimization opportunities across your cluster.

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Monitoring & Analytics Skill

Monitor and analyze your Proxmox infrastructure health and performance.

## What this skill does

This skill enables you to:
- Get node statistics and performance metrics
- Monitor CPU, memory, and disk utilization
- Track network performance
- Analyze VM/container performance
- Monitor resource allocation efficiency
- Identify performance bottlenecks
- Generate performance reports
- Track usage trends over time
- Plan capacity based on metrics
- Establish baselines and thresholds

## When to use this skill

Use this skill when you need to:
- Check cluster health and performance
- Monitor node resource usage
- Analyze VM/container performance
- Identify performance bottlenecks
- Troubleshoot performance issues
- Plan capacity expansion
- Generate performance reports
- Establish monitoring baselines
- Forecast resource needs
- Optimize resource allocation

## Available Tools

- `get_node_status` - Get node statistics and performance
- `get_vm_status` - Get VM performance metrics
- `get_container_status` - Get container performance metrics
- `get_cluster_resources` - Get overall cluster metrics

## Typical Workflows

### Infrastructure Health Check
1. Use `get_cluster_resources` for overall health
2. Use `get_node_status` for each node
3. Use `get_vm_status` and `get_container_status` for workload analysis
4. Generate comprehensive health report

### Performance Analysis
1. Use `get_node_status` to analyze node performance
2. Use `get_vm_status` to check VM performance
3. Identify high-utilization resources
4. Analyze performance trends
5. Recommend optimizations

### Capacity Planning
1. Use `get_cluster_resources` for current utilization
2. Use `get_node_status` for detailed metrics
3. Analyze growth trends
4. Project future capacity needs
5. Plan scaling or upgrades

### Bottleneck Identification
1. Use `get_node_status` to find high CPU/memory nodes
2. Use `get_vm_status` for resource-hungry VMs
3. Use `get_storage` for disk bottlenecks
4. Analyze performance impact
5. Recommend solutions

## Example Questions

- "What's the current cluster health and performance?"
- "Which nodes are running at high utilization?"
- "Show me the performance metrics for all VMs"
- "Are there any performance bottlenecks?"
- "Get a complete performance analysis report"
- "Which containers are consuming the most resources?"
- "What are the resource trends over time?"

## Response Format

When using this skill, I provide:
- Node statistics with CPU, memory, disk metrics
- VM/container performance data
- Utilization trends and analysis
- Bottleneck identification
- Capacity planning recommendations
- Optimization suggestions

## Best Practices

- Monitor metrics continuously
- Establish performance baselines
- Set appropriate alert thresholds
- Track metrics over time for trends
- Identify and optimize peak usage periods
- Balance load across nodes
- Monitor both physical and virtual resources
- Analyze before and after optimization
- Keep historical data for trend analysis
- Use metrics to justify capacity investments
- Monitor network performance
- Consider both current and future growth