performance-degradation-rca

Merge metrics, drift, deployment history, and data provenance to document root causes of production performance degradations.

5|Updated Nov 18, 2025
One-click install
npx skills add https://github.com/DuqueOM/ML-MLOps-Portfolio --skill performance-degradation-rca
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: performance-degradation-rca
Source: https://github.com/DuqueOM/ML-MLOps-Portfolio/tree/main/.devin/skills/performance-degradation-rca
Command: npx skills add https://github.com/DuqueOM/ML-MLOps-Portfolio --skill performance-degradation-rca

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill synthesizes multi-stream evidence to identify a root cause for performance degradations in production services, enabling rapid diagnosis and durable fixes.

Core Features & Use Cases

  • Correlates performance metrics, drift history, deployment events, and data provenance to propose a root cause.
  • Generates an evidence-backed RCA document template for sharing with on-call and engineering teams.
  • Supports post-incident reviews and continuous improvement of monitoring and deployment practices.

Quick Start

Provide input incident-id and service name to generate a complete RCA draft with supporting evidence.

Frequently Asked Questions about performance-degradation-rca

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

FAQPage Schema
How do I perform a root-cause analysis for production performance degradation?

To perform a root-cause analysis for production performance degradation, you merge performance metrics, drift history, deployment events, and data provenance to identify the cause and generate an evidence-backed RCA document.

What is the best way to document an incident response with cited evidence?

The best way to document an incident response is to generate a blameless RCA template that includes cited files, timestamps, PR numbers, and actionable corrective actions based on merged data streams.

How do I correlate metrics drift and deployment history to find a root cause?

You correlate metrics drift and deployment history by synthesizing multi-stream evidence during a post-incident review, which proposes a root cause and supports durable fixes for production services.

Do I need an incident-id and service name to generate a post-incident RCA?

Yes, you need to provide an incident-id and service name as input to quickly generate a complete RCA draft with supporting evidence for your on-call and engineering teams.

Can I use this approach for blameless post-incident reviews in production?

Yes, you can use this approach for blameless post-incident reviews because it synthesizes multi-stream evidence to enable rapid diagnosis and continuous improvement of monitoring practices.

What should be included in a reproducible RCA for performance degradations?

A reproducible RCA for performance degradations should include cited files, timestamps, PR numbers, actionable corrective actions, and evidence-backed findings derived from data provenance and deployment history.