Optimization Dashboard (K8s)

This dashboard provides an overall picture of cluster efficiency, allocations (requested resources), and optimization opportunities by identifying the gap between requested vs actually used CPU/memory.

Steps

  1. In the Pulse UI, go to Cluster Efficiency on the left pane.
  2. Select Step Interval (how often the dashboard update) and Time Period.
  3. In Cost Settings:
    1. Cloud Provider: Select the cloud service provider.
    2. Instance Type: Select the instance type.
    3. Click Save Settings.

You can see the dashboard details are updated based on the selection.

Efficiency and Savings Potential

CPU Efficiency

  • Shows how much CPU is actually used compared to the cluster’s total CPU capacity over the selected time range.
  • Lower efficiency typically indicates the CPU is over-requested or underutilized across workloads.

Memory Efficiency

  • Shows how much memory is actually used compared to the cluster’s total memory capacity.
  • Helps identify memory over-allocation at a cluster level.

CPU Savings Potential

  • Shows the difference between how much all the pods combined are requesting and how much the actual utilization is on the cluster level.

Memory Savings Potential

  • Estimates reclaimable memory (GB) using the same request-vs-usage gap for memory.
  • Helps quantify how much memory could potentially be freed up.

Cluster-Level CPU Resource Breakdown

Breaks down CPU into:

  • Used (actual consumption)
  • Requested (what pods asked for)
  • Capacity (total available in the cluster)

This gives us the overall picture of the cluster resources' state.

Cluster-Level Memory Resource Breakdown

Same breakdown for memory:

  • Used, Requested, and Capacity
  • Shows whether memory inefficiency is due to over-requesting.

Namespace Allocations

  • Time-series view of how much resource is requested (allocated) per namespace.

  • You can switch between node and namespace-level allocations.

    • In node and namespace, you can switch between Cost, Cores, and Memory, and filter nodes and namespaces to understand which nodes and namespaces are driving allocations.
  • In this context, “Allocated” refers to what workloads were requested, not necessarily what they used.

Click on a namespace to view pod details.

POD Allocation:

  • Pod Count
  • CPU Requests
  • Memory Requests
  • CPU Limits
  • Memory Limits

POD Details:

  • CPU Usage, CPU Request, CPU Waste, CPU Efficiency
  • Memory Usage, Memory Request, Memory Waste, Memory Efficiency

Namespace Waste or Node Waste

  • Shows waste per namespace and node based on the difference between requested and used resources.
  • Clicking a namespace provides pod-level details (requests, usage-related efficiency/waste, and cost impact).

Click on a namespace to view pod details.

POD Allocation:

  • Pod Count
  • CPU Requests
  • Memory Requests
  • CPU Limits
  • Memory Limits

POD Details:

  • CPU Usage, CPU Request, CPU Waste, CPU Efficiency
  • Memory Usage, Memory Request, Memory Waste, Memory Efficiency

CPU vs Memory Efficiency by Namespace

This helps in comparing namespace efficiency:

  • One axis = CPU efficiency
  • Other axis = memory efficiency

Namespaces closer to the “balanced” zone (100 percent) indicate healthier request-to-usage alignment; extremes indicate under- or over-request patterns.

  • If the efficiency is more than 100 percent, it means that the request value is a lot different than the actual usage.
  • If the efficiency is less than 100 percent, it means that the usage is less than the requested value.

Cluster-Level Idle Cost Breakdown

Splits idle cost into:

  • Workload idle (idle due to workload over-requesting)
  • Infrastructure idle (idle due to cluster/node-level capacity not being utilized)

Idle Cost by Namespace (Top 8)

  • Ranks namespaces that contribute the most to idle cost (CPU + memory).
  • Useful to prioritize optimization efforts.

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Other Details

  • Node Free Memory

    • Shows available (free) memory per node.
    • Useful for capacity planning and spotting nodes with headroom.
  • Node Memory Utilization

    • Shows memory utilization % per node.
    • Helps detect hotspots or imbalances across nodes.
  • Per Node CPU Metrics

    • Compares CPU Usage vs CPU Allocation at the node level.
    • Helps identify nodes with consistent over-allocation or underutilization.
  • Per Node Memory Metrics

    • Compares Memory Usage vs Memory Allocation at the node level.
    • Highlights nodes where memory is frequently over-requested.
  • Cluster-Wide CPU Utilization

    • Time-series trend of overall CPU utilization across the cluster (all nodes combined).
    • Helps correlate workload activity and cluster scaling behavior.
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