Cost Efficiency with AI Guide

Learn how GIIP AI analyzes infrastructure usage patterns to reduce unnecessary costs and maximize resource efficiency.

📋 Overview

A significant portion of corporate infrastructure costs stems from allocated but unused resources or over-configured specifications. GIIP AI suggests optimal resource sizes based on real-time metric data and captures cost-saving opportunities.

🔍 Key Analysis & Optimization Features

1. Rightsizing Recommendations

Analysis: Analyzes CPU, memory, and disk I/O patterns for over 7 days.
Recommendation: Suggests changing low-load servers to smaller instance types or scaling resources only during peak hours.

2. Zombie Asset Detection

Identifies and lists disks (EBS/Disk) without connected instances, unassigned public IPs, and neglected snapshots, and recommends their deletion.

3. Reserved Instances (RI) & Spot Instance Proposals

If workload patterns are consistent, it recommends purchasing Reserved Instances. for temporary, interruptible tasks, it suggests using Spot Instances to help save up to 70% or more.

🛠️ How to Apply Optimizations

Check the [AI Recommendations] section in the GIIP [Cost Management] dashboard.
Review the estimated savings for each item proposed in the analysis report.
Click the [Apply via Agent] button, and the
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agent will automatically change instance types or clean up resources after backing them up.

📊 Expected Benefits

Average 20-40% Cost Savings: Significant cloud/on-premise costs can be reduced just through regular AI analysis and actions.
Enhanced Visibility: Intuitively understand which services are consuming excessive costs.

Version: 1.0 Last Updated: 2026-03-19 Source:

giipv3/public/help/cost-optimization.en.md