kaytu: A Go repository from Kaytu

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

kaytu login

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

kaytu optimize ec2-instance

For RDS:

kaytu optimize rds-instance