devops-troubleshooter

Diagnose production outages through log analysis, tracing, and Kubernetes debugging.

4|20|Updated Sep 27, 2025

Search Tags:#devops #debugging #troubleshooting #kubernetes #observability #incident response

Ready to run

npx skills add https://github.com/tan-yong-sheng/cloudflare-image-mcp --skill devops-troubleshooter-tan-yong-sheng

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: devops-troubleshooter
Source: https://github.com/tan-yong-sheng/cloudflare-image-mcp/tree/main/.claude/skills/devops-troubleshooter
Command: npx skills add https://github.com/tan-yong-sheng/cloudflare-image-mcp --skill devops-troubleshooter-tan-yong-sheng

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides expert assistance for rapid incident response, advanced debugging, and modern observability, helping to resolve production outages and improve system reliability.

Core Features & Use Cases

Incident Response: Guides through immediate actions during production outages.
Log & Trace Analysis: Helps analyze logs, metrics, and traces to pinpoint root causes.
Kubernetes Debugging: Assists in troubleshooting containerized applications and Kubernetes environments.
Use Case: When a critical service experiences intermittent failures, this Skill can help analyze system logs and network traffic to identify the root cause and suggest remediation steps.

Quick Start

Use the devops troubleshooter skill to debug high memory usage in Kubernetes pods causing frequent OOMKills and restarts.

Frequently Asked Questions about devops-troubleshooter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I troubleshoot Kubernetes pods with high memory usage and OOMKills?▼

To troubleshoot Kubernetes OOMKills, analyze pod resource limits, inspect memory metrics, and review container logs to identify memory leaks or misconfigured limits, then apply remediation steps like adjusting resource requests.

What is the best way to perform root cause analysis for production outages?▼

Root cause analysis for production outages involves guided incident response, examining distributed traces, analyzing system logs, and correlating metrics to pinpoint the exact failure point and resolve system reliability issues.

How does distributed tracing help with incident response?▼

Distributed tracing helps incident response by visualizing request paths across microservices, pinpointing latency bottlenecks, and identifying exact failure points within complex infrastructure during advanced debugging.

Can I use this for debugging containerized applications in Kubernetes environments?▼

Yes, you can use this to debug containerized applications within Kubernetes environments by examining container orchestration states, analyzing network traffic, and resolving complex infrastructure issues.

How do I analyze logs and metrics to resolve intermittent service failures?▼

Analyze logs and metrics to resolve intermittent failures by querying observability platforms, correlating anomalous metric spikes with specific error logs, and utilizing SRE principles to diagnose the root cause.