Automatically Analyze Your EKS Storage Usage

Automatically Analyze Your EKS Storage Usage

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Automated EKS Storage Usage Analysis with GitHub's ebs-volume-usage-exporter

The ebs-volume-usage-exporter is a tool that helps Amazon EKS (Elastic Container Service for Kubernetes) users optimize their storage usage. It automatically analyzes the storage usage of persistent volumes in an EKS cluster and provides insights on opportunities for cost optimization.

Key Features:

  1. Automatic Analysis: The tool exports CSV files containing detailed information about storage usage, including provisioned capacity, IOPS, throughput, and more.
  2. EBS Volume Usage Calculator: Users can upload the exported CSV file to the Simplyblock EBS Volume Usage Calculator for automatic analysis and calculation of overprovisioning.
  3. Local Execution: The calculator runs completely local in the browser, without uploading data to any servers.
  4. Ready-to-Use Helm Chart: A pre-configured Helm chart is available, making it easy to deploy and manage the tool.

Benefits:

  1. Improved Cost Optimization: By analyzing storage usage patterns, users can identify opportunities to reduce costs and optimize their EKS cluster resources.
  2. Enhanced Insights: The tool provides detailed information about storage usage, helping users make informed decisions about their cloud infrastructure.
  3. Easy Deployment: The Helm chart makes it easy to deploy the tool in an existing EKS environment.

Collector Usage:

To use the ebs-volume-usage-exporter, follow these steps:

  1. Create a secret with your AWS access key ID and secret access key.
  2. Create a service account and cluster role (get and list PVs, PVCs, and snapshots).
  3. Install the Helm chart using the provided command.

CSV File Content:

The exported CSV file contains columns such as aws_region, pv_name, pv_size, ebs_volume_id, ebs_volume_type, and more, providing detailed information about storage usage.

By utilizing the ebs-volume-usage-exporter, users can gain valuable insights into their EKS cluster's storage usage and optimize their resources for cost savings.