Resource Usage Tracker
Track CPU, memory, disk I/O, and network utilization in real time to identify bottlenecks, right-size instances, and reduce cloud infrastructure costs.
Overview
This skill provides a comprehensive solution for monitoring and optimizing resource usage within an application. It leverages the resource-usage-tracker plugin to gather real-time metrics, identify performance bottlenecks, and suggest optimization strategies.
How It Works
- Identify Resources: The skill identifies the resources to be tracked based on the user's request and the application's configuration (CPU, memory, disk I/O, network I/O, etc.).
- Collect Metrics: The plugin collects real-time metrics for the identified resources, providing a snapshot of current resource consumption.
- Analyze Data: The skill analyzes the collected data to identify performance bottlenecks, resource imbalances, and potential optimization opportunities.
- Provide Recommendations: Based on the analysis, the skill provides specific recommendations for optimizing resource allocation, right-sizing instances, and reducing costs.
When to Use This Skill
This skill activates when you need to:
- Identify performance bottlenecks in an application.
- Optimize resource allocation to improve efficiency.
- Reduce cloud infrastructure costs by right-sizing instances.
- Monitor resource usage in real-time to detect anomalies.
- Track the impact of code changes on resource consumption.
Examples
Example 1: Identifying Memory Leaks
User request: "Track memory usage and identify potential memory leaks."
The skill will:
- Activate the resource-usage-tracker plugin to monitor memory usage (heap, stack, RSS).
- Analyze the memory usage data over time to detect patterns indicative of memory leaks.
- Provide recommendations for identifying and resolving the memory leaks.
Example 2: Optimizing Database Connection Pool
User request: "Optimize database connection pool utilization."
The skill will:
- Activate the resource-usage-tracker plugin to monitor database connection pool metrics.
- Analyze the connection pool utilization data to identify periods of high contention or underutilization.
- Provide recommendations for adjusting the connection pool size to optimize performance and resource consumption.
Best Practices
- Granularity: Track resource usage at a granular level (e.g., process-level CPU usage) to identify specific bottlenecks.
- Historical Data: Analyze historical resource usage data to identify trends and predict future resource needs.
- Alerting: Configure alerts to notify you when resource usage exceeds predefined thresholds.
Integration
This skill can be integrated with other monitoring and alerting tools to provide a comprehensive view of application performance. It can also be used in conjunction with deployment automation tools to automatically right-size instances based on resource usage patterns.
Prerequisites
- Access to system monitoring tools (top, ps, vmstat, iostat)
- Resource metrics collection infrastructure
- Historical usage data in ${CLAUDE_SKILL_DIR}/metrics/resources/
- Performance baseline definitions
Instructions
- Identify resources to track (CPU, memory, disk, network)
- Collect real-time metrics using system tools
- Analyze data for bottlenecks and patterns
- Compare against historical baselines
- Generate optimization recommendations
- Provide right-sizing and cost reduction strategies
Output
- Resource usage reports with trends
- Bottleneck identification and analysis
- Right-sizing recommendations for instances
- Cost optimization suggestions
- Alert configurations for thresholds
Error Handling
If resource tracking fails:
- Verify system monitoring tool permissions
- Check metrics collection daemon status
- Validate data storage availability
- Ensure network access to monitoring endpoints
- Review baseline data completeness
Resources
- System performance monitoring guides
- Cloud resource optimization best practices
- CPU and memory profiling techniques
- Infrastructure cost optimization strategies
1---2name: tracking-resource-usage3description: Track and optimize resource usage across application stack including CPU, memory, disk, and network I/O. Use when identifying bottlenecks or optimizing costs. Trigger with phrases like "track resource usage", "monitor CPU and memory", or "optimize resource allocation".4license: MIT5---6# Resource Usage Tracker
7
8Track CPU, memory, disk I/O, and network utilization in real time to identify bottlenecks, right-size instances, and reduce cloud infrastructure costs.
9
10## Overview
11
12This skill provides a comprehensive solution for monitoring and optimizing resource usage within an application. It leverages the resource-usage-tracker plugin to gather real-time metrics, identify performance bottlenecks, and suggest optimization strategies.
13
14## How It Works
15
161. **Identify Resources**: The skill identifies the resources to be tracked based on the user's request and the application's configuration (CPU, memory, disk I/O, network I/O, etc.).
172. **Collect Metrics**: The plugin collects real-time metrics for the identified resources, providing a snapshot of current resource consumption.
183. **Analyze Data**: The skill analyzes the collected data to identify performance bottlenecks, resource imbalances, and potential optimization opportunities.
194. **Provide Recommendations**: Based on the analysis, the skill provides specific recommendations for optimizing resource allocation, right-sizing instances, and reducing costs.
20
21## When to Use This Skill
22
23This skill activates when you need to:
24- Identify performance bottlenecks in an application.
25- Optimize resource allocation to improve efficiency.
26- Reduce cloud infrastructure costs by right-sizing instances.
27- Monitor resource usage in real-time to detect anomalies.
28- Track the impact of code changes on resource consumption.
29
30## Examples
31
32### Example 1: Identifying Memory Leaks
33
34User request: "Track memory usage and identify potential memory leaks."
35
36The skill will:
371. Activate the resource-usage-tracker plugin to monitor memory usage (heap, stack, RSS).
382. Analyze the memory usage data over time to detect patterns indicative of memory leaks.
393. Provide recommendations for identifying and resolving the memory leaks.
40
41### Example 2: Optimizing Database Connection Pool
42
43User request: "Optimize database connection pool utilization."
44
45The skill will:
461. Activate the resource-usage-tracker plugin to monitor database connection pool metrics.
472. Analyze the connection pool utilization data to identify periods of high contention or underutilization.
483. Provide recommendations for adjusting the connection pool size to optimize performance and resource consumption.
49
50## Best Practices
51
52- **Granularity**: Track resource usage at a granular level (e.g., process-level CPU usage) to identify specific bottlenecks.
53- **Historical Data**: Analyze historical resource usage data to identify trends and predict future resource needs.
54- **Alerting**: Configure alerts to notify you when resource usage exceeds predefined thresholds.
55
56## Integration
57
58This skill can be integrated with other monitoring and alerting tools to provide a comprehensive view of application performance. It can also be used in conjunction with deployment automation tools to automatically right-size instances based on resource usage patterns.
59
60## Prerequisites
61
62- Access to system monitoring tools (top, ps, vmstat, iostat)
63- Resource metrics collection infrastructure
64- Historical usage data in ${CLAUDE_SKILL_DIR}/metrics/resources/
65- Performance baseline definitions
66
67## Instructions
68
691. Identify resources to track (CPU, memory, disk, network)
702. Collect real-time metrics using system tools
713. Analyze data for bottlenecks and patterns
724. Compare against historical baselines
735. Generate optimization recommendations
746. Provide right-sizing and cost reduction strategies
75
76## Output
77
78- Resource usage reports with trends
79- Bottleneck identification and analysis
80- Right-sizing recommendations for instances
81- Cost optimization suggestions
82- Alert configurations for thresholds
83
84## Error Handling
85
86If resource tracking fails:
87- Verify system monitoring tool permissions
88- Check metrics collection daemon status
89- Validate data storage availability
90- Ensure network access to monitoring endpoints
91- Review baseline data completeness
92
93## Resources
94
95- System performance monitoring guides
96- Cloud resource optimization best practices
97- CPU and memory profiling techniques
98- Infrastructure cost optimization strategies
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