remediation-advisor

Diagnose GCSFuse performance regressions and compile advisory remediation plans.

9|6|Updated Jan 11, 2025

Search Tags:#performance #benchmarking #remediation #diagnostics #sla #gcsfuse

Ready to run

npx skills add https://github.com/GoogleCloudPlatform/gcsfuse-tools --skill remediation-advisor-googlecloudplatform

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: remediation-advisor
Source: https://github.com/GoogleCloudPlatform/gcsfuse-tools/tree/main/npi/.agents/skills/remediation-advisor
Command: npx skills add https://github.com/GoogleCloudPlatform/gcsfuse-tools --skill remediation-advisor-googlecloudplatform

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses complex performance regressions and SLA failures in GCSFuse deployments by providing a structured diagnostic path for identifying bottlenecks in network, kernel, and FUSE configurations.

Core Features & Use Cases

Diagnostic Decision Trees: Systematic troubleshooting for throughput regressions, conformance failures, and resource exhaustion.
Remediation Planning: Compiles a comprehensive, advisory-only remediation plan covering FUSE parameters, kernel offloads, and network tuning.
Use Case: When a benchmark run fails to meet the 20 GB/s SLA gate, use this Skill to analyze validation reports and generate a prioritized list of configuration adjustments to restore performance.

Quick Start

Use the remediation-advisor skill to analyze the provided npi_validation_report.md and generate a remediation plan for the identified performance bottlenecks.

Frequently Asked Questions about remediation-advisor

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

FAQPage Schema

How do I diagnose GCSFuse performance regressions and SLA gate failures?▼

To diagnose GCSFuse performance regressions and SLA gate failures, analyze benchmark metrics and conformance test results using structured decision trees to systematically identify bottlenecks in network, kernel, and FUSE configurations.

What system configurations are evaluated during GCSFuse benchmarking troubleshooting?▼

GCSFuse benchmarking troubleshooting evaluates system-level configurations including FUSE queue depths, gRPC connection pools, and network offload settings to pinpoint the exact causes of resource exhaustion and throughput drops.

Can I use this approach to automatically apply fixes when a benchmark run fails to meet the 20 GB/s SLA?▼

No, you cannot use this approach to automatically apply fixes because it compiles an advisory-only remediation plan of configuration adjustments to resolve identified bottlenecks without executing unauthorized system modifications.

What is the best way to generate a remediation plan for GCSFuse bottlenecks?▼

The best way to generate a remediation plan for GCSFuse bottlenecks is to analyze an npi_validation_report containing benchmark metrics, which produces a prioritized list of FUSE, kernel, and network configuration adjustments.

What limitations exist when resolving conformance failures and resource exhaustion in GCSFuse?▼

A key limitation when resolving conformance failures and resource exhaustion is that the diagnostic process is strictly advisory, meaning it identifies bottlenecks and suggests fixes but does not execute any direct system modifications.