Python Micrometer Gcp Cloud Monitoring
Helps with Python, Google Cloud, monitoring 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-gcp-cloud-monitoring npx -- -y @trustedskills/python-micrometer-gcp-cloud-monitoring
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"python-micrometer-gcp-cloud-monitoring": {
"command": "npx",
"args": [
"-y",
"@trustedskills/python-micrometer-gcp-cloud-monitoring"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill enables Python applications to instrument metrics and export them directly to Google Cloud Monitoring using Micrometer. It provides a standardized way to collect application performance data, allowing for centralized monitoring and alerting within the GCP ecosystem. This facilitates deeper insights into application behavior and resource utilization.
When to use it
- Monitoring Application Performance: Track key metrics like request latency, error rates, and CPU usage in Python applications deployed on Google Cloud Platform.
- Troubleshooting Production Issues: Quickly identify performance bottlenecks or errors by correlating application metrics with Cloud Monitoring dashboards.
- Capacity Planning: Analyze resource utilization trends to optimize infrastructure costs and ensure adequate capacity for future growth.
- Observability Integration: Integrate custom Python applications into existing GCP observability pipelines.
Key capabilities
- Micrometer instrumentation for Python applications.
- Automatic metric export to Google Cloud Monitoring.
- Standardized metric naming and tagging.
- Support for various Micrometer registries.
Example prompts
- "Instrument the
process_orderfunction in my application to track its execution time." - "Configure this skill to send metrics every 5 seconds to Cloud Monitoring."
- “Show me how to add custom tags to my request latency metric.”
Tips & gotchas
- Requires a Google Cloud project with appropriate permissions to write metrics to Cloud Monitoring.
- Ensure Micrometer is properly configured within your Python application before using this skill.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.