Python Micrometer Metrics Setup
Helps with Python, setup and configuration as part of developing backend services and APIs workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add python-micrometer-metrics-setup npx -- -y @trustedskills/python-micrometer-metrics-setup
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"python-micrometer-metrics-setup": {
"command": "npx",
"args": [
"-y",
"@trustedskills/python-micrometer-metrics-setup"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill automates the setup of Micrometer metrics collection in Python applications. It configures a Prometheus client, registers a meter and counter, and ensures proper metric reporting. This allows for easy monitoring and performance analysis of your application's behavior.
When to use it
- Monitoring API Performance: Track response times and error rates for critical API endpoints.
- Tracking Background Jobs: Measure the duration and frequency of asynchronous tasks.
- Resource Usage Analysis: Monitor CPU usage, memory consumption, or other resource metrics within your application.
- Debugging Slow Operations: Identify bottlenecks by tracking specific operations' execution times.
Key capabilities
- Prometheus client configuration
- Meter registration for measuring cumulative values
- Counter registration for tracking event occurrences
- Metric reporting
Example prompts
- "Set up Micrometer metrics to track the duration of my API endpoint
/users." - "Configure a counter to measure the number of successful database connections."
- "Initialize Micrometer and register a meter named 'queue_size'."
Tips & gotchas
This skill requires a Prometheus server to be accessible for metric reporting. Ensure your application has network access to the Prometheus endpoint during setup.
Tags
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