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IldarMinaev
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qubership-postgresql-troubleshooting

Map PostgreSQL symptoms to structured investigation paths for pgskipper-managed clusters.

1|3|Updated Mar 23, 2026
Search Tags:#troubleshooting#postgresql#kubernetes#ai-agent#patroni#pgskipper#dbaas
One-click install
npx skills add https://github.com/IldarMinaev/troubleshooting-skill --skill qubership-postgresql-troubleshooting
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qubership-postgresql-troubleshooting
Source: https://github.com/IldarMinaev/troubleshooting-skill/tree/main
Command: npx skills add https://github.com/IldarMinaev/troubleshooting-skill --skill qubership-postgresql-troubleshooting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a structured troubleshooting framework to guide AI agents in diagnosing PostgreSQL issues in Kubernetes environments.

Core Features & Use Cases

  • A modular, rule-based prompt suite that orchestrates health checks, performance analysis, storage and backups, connections, logs, DBAAS, and monitoring investigations.
  • Enables routing of vague symptoms to targeted skills, forming a clear investigation plan and actionable remediation steps.
  • Maintains an auditable trail of evidence and decisions to support reproducible incident analysis.

Quick Start

Use this skill to bootstrap AI-driven troubleshooting workflows across Patroni clusters, including health checks, performance assessments, and DBAAS status inquiries.

Frequently Asked Questions about qubership-postgresql-troubleshooting

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

FAQPage Schema
How do I troubleshoot PostgreSQL cluster issues in Kubernetes using an AI agent?▼

To troubleshoot PostgreSQL clusters in Kubernetes, this Skill maps symptoms to a structured investigation path across health, performance, storage, and DBAAS domains, enabling rapid root-cause analysis and remediation planning.

What is the best way to diagnose Patroni cluster health and performance problems?▼

Diagnosing Patroni cluster issues involves routing vague symptoms to targeted checks that analyze health, performance, connections, and logs, forming a clear investigation plan with actionable remediation steps.

Does this PostgreSQL troubleshooting approach work with pgskipper-managed DBAAS deployments?▼

Yes, this troubleshooting workflow specifically applies to pgskipper-managed deployments, covering DBAAS status inquiries, storage, backups, and monitoring investigations within Kubernetes environments.

Can I use an AI-driven workflow to maintain an auditable trail of PostgreSQL incident analysis?▼

Yes, the AI-driven troubleshooting workflow maintains an auditable trail of evidence and decisions, enforcing safety checks and credential handling rules to support reproducible PostgreSQL incident analysis.

How do I start an investigation when my PostgreSQL cluster has vague or unclear symptoms?▼

Starting an investigation requires mapping vague symptoms to a structured, rule-based prompt suite that orchestrates targeted checks across health, performance, storage, backups, connections, logs, DBAAS, and monitoring domains.

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