Kaytu's AI platform boosts the efficiency of your cloud-hosted workload and Kubernetes Clusters by analyzing historical usage and delivering intelligent recommendations—such as optimizing instance sizes—that maintain reliability.

Overview

• Ease of use: One-line command. Use without modifying workloads or making configuration changes.
• Optimize: Optimize AWS workloads (EC2 Instances, EBS Storage, RDS, Kubernetes/EKS), Azure Kubernetes, and Google Kubernetes (GKE)
• Base on actual Usage: Analyzes based on actual usage from Monitoring (CloudWatch & Prometheus).
• Customize: Optimize for region, CPU, memory, network performance, storage, licenses, and more to match your specific requirements.
• Secure - no credentials to share; extracts required metrics from the client side
• Open philosophy Use without fear of lock-in. The CLI is open-sourced, and the Server side will be open-sourced soon.
• Coming Soon: GPU Optimization, Amazon EFS

To optimize Kubernetes Clusters click here for a walk through

Quick Start - Optimize AWS EC2, RBS, and RDS Workload

1. Install Kaytu CLI

MacOS

brew tap kaytu-io/cli-tap && brew install kaytu

Linux

curl -fsSL https://raw.githubusercontent.com/kaytu-io/kaytu/main/scripts/install.sh | sh

Windows (and all Binaries) Download Windows (Linux, and MacOS) binary from releases

2. Login to AWS CLI

Kaytu works with your existing AWS CLI profile (read-only access required) to gather metrics.

To confirm your AWS CLI login is working correctly:

aws sts get-caller-identity

Click here to see how to log in to AWS CLI.

We respect your privacy. Our open-source code guarantees that we never collect sensitive information such as AWS resource identifiers, credentials, IPs, tags, etc.

3. Run Kaytu CLI

Login to your free account:

kaytu login

To see how you can optimize EC2 Instances, run this command:

kaytu optimize ec2-instance

For RDS:

kaytu optimize rds-instance