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Cost ManagementAnalytics

Analysis

Overview

The ScaleOps Resource and Cost Analysis pages provide comprehensive insights into your Kubernetes cluster’s resource utilization and cost optimization. These pages serve as your central dashboard for understanding how your infrastructure is performing, where resources are being used, and how ScaleOps is helping you optimize costs and performance.

The Resource and Cost Analysis pages have the following features:

  • Analysis Groups: Separate views for resource analysis and cost analysis
  • Filtering: Filter by time range, namespaces, labels, and annotations
  • Real-time Metrics: Live data refresh for current cluster status
  • Multi-cluster Support: View metrics across multiple clusters simultaneously

Resource Analysis

The Resource Analysis group focuses on understanding how your cluster resources (CPU, memory) are being utilized, how automation is progressing with ScaleOps.

Metrics Displayed

Top-Level Metrics
  • Average Allocatable CPU: Total CPU cores available across your cluster
  • Average Allocatable Memory: Total memory available across your cluster
  • Automation Progress: Percentage of workloads and pods that are automated
Resources Over Time
  • Purpose: Track CPU and memory usage patterns over time
  • What it shows:
    • Current usage vs requests
    • Original requests vs optimized requests
    • Resource allocation trends
  • Use case: Identify resource consumption patterns and optimization opportunities
Automation Progress
  • Automated Rightsizing Pods: Shows the percentage of pods that have been automatically rightsized
  • Automated Unevictable Pods: Tracks optimization of pods that cannot be evicted
  • Automated HPA Pods: Monitors Horizontal Pod Autoscaler optimization (when enabled)
Automated Resources Progress
  • Automated Rightsizing CPU Requests: Tracks CPU request optimization over time
  • Automated Rightsizing Memory Requests: Tracks memory request optimization over time
  • Blocked Resources: Shows CPU and memory blocked by unevictable pods
HPA Optimization (when enabled)
  • Automated HPA CPU Requests: Tracks CPU request optimization for HPA workloads
  • Automated HPA Memory Requests: Tracks memory request optimization for HPA workloads

Cost Analysis

The Cost Analysis group focuses on understanding your cluster costs, identifying savings opportunities, and tracking the financial impact of ScaleOps optimizations.

Metrics Displayed

Top-Level Metrics
  • Average Monthly Cost: Total cost of your cluster infrastructure
  • Average Active Savings: Current savings from implemented optimizations
  • Average Nodes: Number of nodes in your cluster
  • Automation Progress: Percentage of workloads that are cost-optimized
Cost and Infrastructure
  • Cost (Daily): Daily cost breakdown showing spending patterns over time
  • Nodes: Number of nodes in your cluster, helping correlate cost with infrastructure size
Savings Analysis
  • Active Savings (Daily): Current savings from implemented ScaleOps optimizations
  • Savings Available (Daily): Potential savings from additional optimizations that could be implemented
Workload Metrics
  • Number of Pods: Total pods vs automated pods over time
  • Number of Workloads: Total workloads vs automated workloads over time
  • Workloads with HPA: HPA-enabled workloads and their automation status (when HPA optimization is enabled)

Support

  • Data Retention: Analytics data is retained based on your ScaleOps configuration (30 days by default)
  • Multi-cluster Support: Efficiently view metrics across multiple clusters

If you encounter issues with the Analytics pages or need help interpreting the data, please contact your ScaleOps support team. The Analytics pages are designed to provide comprehensive insights into your cluster performance and help you make informed decisions about optimization and resource management.

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