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Introduction

Welcome to Stackbooster.io documentation! We're excited to help you optimize your Kubernetes infrastructure using our AI-powered cost management platform.

About Stackbooster.io

Stackbooster.io is designed to help businesses of all sizes get the most out of their Kubernetes investments by automating cost optimization tasks with artificial intelligence. Our platform analyzes your cluster usage patterns, makes intelligent scaling decisions, and implements strategies to minimize waste while ensuring application performance.

Key Benefits

  • Reduce Cloud Costs: Typical customers see 30-70% reduction in Kubernetes infrastructure costs
  • Automate Operations: Eliminate manual intervention for scaling and resource management
  • Optimize Resources: Ensure every node and pod is operating at optimal efficiency
  • Maintain Performance: Cost savings never come at the expense of application performance
  • Gain Visibility: Clear dashboards show exactly where your resources are being used

How It Works

Stackbooster.io connects to your existing Kubernetes clusters through secure API integrations and deploys lightweight monitoring components. Our AI algorithms analyze usage patterns and make intelligent decisions about:

  1. When to scale up resources to meet increasing demand
  2. How to consolidate workloads to minimize waste
  3. Which instance types offer the best price/performance ratio for your workloads
  4. When to hibernate clusters to avoid unnecessary costs

Who Should Use Stackbooster.io

Our platform is ideal for:

  • DevOps teams managing multiple Kubernetes clusters
  • Cloud architects looking to optimize infrastructure costs
  • Finance teams seeking to control cloud spending
  • Businesses of all sizes running containerized workloads on AWS

Next Steps

Ready to get started? Follow these steps:

  1. Quick Setup Guide
  2. Account Setup Instructions
  3. AWS Integration Guide
  4. Creating Your First Cluster

If you have any questions along the way, check out our FAQ or contact our support team.

Released under the MIT License. Contact us at [email protected]