Cost Optimization AWS Kubernetes Clusters

Executive Summary: Standard cloud optimization tools rely on CPU metrics, leading to false positives and the dreaded "Scream Test". AIPrunr provides forensic-level proof of idleness by analyzing network traffic directly, allowing enterprise IT leaders to safely automate the decommissioning of AWS Kubernetes Clusters.

The Problem with CPU Metrics for AWS Kubernetes Clusters

When enterprise IT and Finance teams attempt cost optimization Kubernetes Clusters, they typically rely on tools like CloudHealth or native cloud advisor metrics. These tools look at CPU utilization. However, background agents (like antivirus or log rotation) cause CPU spikes even on completely abandoned infrastructure.

This inaccuracy forces engineering teams to manually verify each server or rely on the "Scream Test" (shutting it down and waiting to see who complains)—a risk unacceptable to enterprise CTOs.

The AIPrunr Solution: Flow Log Forensics

Instead of looking at the server itself, AIPrunr looks at the network. By performing 100% agentless, zero-egress analysis on your AWS VPC/NSG Flow Logs, AIPrunr delivers 99% precision and 24-Hour ROI. (Patent Pending: Method for determining infrastructure asset idleness via Stateless Flow Log Analysis, #63/964,385).

Is anyone talking to this server?
Is it serving external business logic?
Does it have active upstream dependencies?

Because there are no heavy agents to deploy, AIPrunr connects in minutes and immediately proves an asset is truly a zombie. This empowers senior leadership to confidently cut bloated cloud spend without the risk of taking down production.

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