Node group view
Gain insights and identify the most impactful optimization opportunities within the node groups
Last updated
Gain insights and identify the most impactful optimization opportunities within the node groups
Last updated
This view provides a comprehensive and granular breakdown of all node groups within a cluster. It facilitates immediate identification of resource inefficiencies, enables quick prioritization of optimization tasks for optimal results, and unlocks further deep investigation.
Node Group
This displays the Node Group Name. To sort or filter data, click on a column title or use a drop-down list.
Architecture
This displays the Node Architecture (ARM, x86). You can sort or filter data by clicking on a column title or using a drop-down list.
Nodes (avg & max)
This displays the average and maximum number of nodes in a specific node group. Click on a column title to sort the data.
Reservation
Display the reservation type of nodes in the group. To sort or filter data, click on a column title or use a drop-down list.
Avg Cost/h
Displays the average node group cost per hour. Click on a column title to sort data.
Total Cost
Displays the total node group cost. Click on a column title to sort data.
Idle Cost
Displays the cost of the space in a node group that has never been used. Click on a column title to sort the data.
Potential savings
Last Seen
Displays the last time PerfectScale observed the Node Group.
Utilization
Shows the total cost and idle of the nodes.
By clicking on the node group, you will be navigated to the Node Group Details screen. Here, you can get a detailed view of the running workloads within this group or review the distribution of node types along with relevant data for further analysis.
Once you are in the Node Group, you can easily explore the data with various levels of granularity based on your needs:
Node Recommendations is a powerful feature that provides actionable, data-driven insights to help you choose the optimal node type for your workloads and streamline the overall optimization process. Also, this view delivers the estimated savings you can achieve by applying the recommendations, enabling better forecasting and budget planning.
Node recommendations are optimized for steady-state workloads (e.g., Deployments, StatefulSets). Bursty workloads like Jobs or CI pipelines may yield less accurate results due to their ephemeral nature.
Click the Show button to expand the view and access the full recommendation, including the best-fit node type, its configuration spec, and how much $ you can cut by applying it.
The projected impact on costs after implementing the recommendations and the percentage difference between the current and recommended costs.
Recommended node type.
Constraints, including architecture type, instance type, GPU allocation, etc.
Node details, including the available CPU and memory per node, recommended node count, and average cost per hour.
The price comparison between the original and recommended nodes is performed on a like-for-like basis: on-demand to on-demand and spot to spot. PerfectScale does not factor in any discounts the customer currently has on their existing nodes, as we cannot predict what discounts will apply to the recommended nodes if the change is made.
PerfectScale highly values your feedback on node recommendations — don’t forget to click the "Is this helpful?" button to let us know!
Node Group indicates the name of the node group associated with the displayed data.
Timeframe allows you to check the data for a specific time period: click on the drop-down list in the upper right corner and select one of the existing options.
Seamlessly Export and effortlessly share your data by exporting it into a .csv file for further analysis.
Node Group Resources Utilization
To view data at a specific percentile, use the Utilization filter. The filter will impact both the charts and the table.
Cost per Node Type displays the cost trend of the Node Types over the selected timeframe.
CPU displays the allocated, requested, and used amount of CPU (cores) with the selected usage percentile in the group over time.
Memory displays the allocated, requested, and used amount of Memory (GB) with the selected usage percentile in the group over time.
Node Type
Instance Type Name. Click on a column title or use a drop-down list to sort or filter data.
Architecture
Node Architecture. Click on a column title or use a drop-down list to sort or filter data.
Reservation
Node reservation type. Click on a column title or use a drop-down list to sort or filter data.
CPU/Mem (node)
Node size. Click on a column title to sort data.
Nodes avg/max
Average and maximum number of nodes with a specific type. Click on a column title to sort data.
Avg Pods per Node
Current average number of pods per the node in the node group.
Max Pods per Node
The maximum possible pods that can be scheduled on the node.
Running Hours
Total instance running hours.
Avg Cost/h
Average cost per hour of the instance with the specific type. Click on a column title to sort data.
Total Cost
Total cost of nodes with the specific type. Click on a column title to sort data.
Idle Cost
Cost of the space in nodes with the specific types that has never been used. Click on a column title to sort the data.
Last Seen
Last time PerfectScale observed node with a specific type.
Utilization
Diving into the workloads running on a specific node enables you to seamlessly identify which workloads contribute the most to resource waste due to over-provisioning and adjust resource allocations with data-driven recommendations, creating new opportunities to optimize your underlying Kubernetes infrastructure.
Workload
Indicates the name of the workload.
Automation
Displays the automation status of a particular workload. You can easily sort the data by automation status to focus on the most relevant information for further investigation.
Type
Indicates the type of the workload.
Namespace
Indicates the workloads' namespace.
Running Hours
The workload running hours.
Total Cost
The total cost of allocated resources of the workload.
Pod Waste
The total cost of reducible workload resources.
Increase Needed
An estimated cost increase associated with implementing the recommendation to resolve resiliency risks caused by underprovisioned resources.
Potential Savings
An estimated dollar savings by applying workload sizing recommendations.
Container
Indicates the container of the workload.
Labels and Policies view
Optimization Policy
Displays the Optimization policy associated with the workload:
MaxSavings - maximum cost savings, the best for non-production environments
Balanced (default) - optimally balances cost and resiliency
ExtraHeadroom - the best fit for latency-sensitive environments
MaxHeadroom - keeps the environment above the highest spikes
Labels
Displays the label associated with the workload. You can select up to two labels to display.
The Workload labels have higher precedence than Namespace labels. If the Workload label and Namespace label have the same name, only the Workload label will display.
HPA view
The HPA view provides a clear overview of workloads utilizing Horizontal Pod Autoscaler (HPA). This feature enables users to quickly identify the workloads where HPA has been introduced and adjust HPA thresholds with provided informative tooltips that offer tailored recommendations. These recommendations are particularly helpful in optimizing scaling decisions, minimizing resource waste, and ensuring efficient operation of workloads.
HPA
Indicates whether HPA has been introduced for the workload. You can easily sort the column by clicking the header or apply specific filters.
CPU (%)
Displays the trigger for HPA by CPU. For insights on threshold recommendations, simply hover over the warning tooltip. You can easily sort the column by its values by clicking the header.
There are two types of indicators to be aware of:
A red indication signifies that the threshold is below 60%, indicating potential significant CPU waste.
A yellow indication suggests that the threshold falls between 60% and 80%, pointing to potential moderate CPU waste.
Memory (%)
Displays the trigger for HPA by Memory. For insights on threshold recommendations, simply hover over the warning tooltip. You can easily sort the column by its values by clicking on the header.
There are two types of indicators to be aware of:
A red indication signifies that the threshold is below 60%, indicating potential significant Memory waste.
A yellow indication suggests that the threshold falls between 60% and 80%, pointing to potential moderate Memory waste.
Custom metric
Indicates whether a Custom metric has been detected. You can easily sort the column by clicking the header or apply specific filters.
The workloads trend chart helps you identify waste and cost trends within the Node Group, directing your focus to the most critical and valuable aspects.
Select whether you want to display the workload data by waste or cost using this selector.
Filter the data by the workload type.
Select the interval for data display based on your desired data granularity.
Use the workloads legend to include or exclude the particular workloads from the chart.
Choose a limit from the dropdown (from 1 to 15) to exhibit only the top N entities
Node group <none> contains nodes whose labels were not identified (for example, custom labels). In that case, we recommend you group such nodes manually by configuring the .
Displays the estimated dollar savings by applying .
A visual representation of CPU and Memory Utilization (allocation, request, and usage) based on the Use a drop-down list to filter data with the needed value.
Optimization Policy indicates the cluster policy that specifies how your resources should be allocated to support the individual needs of your workloads. Learn more about policies .
CPU and Memory Utilization (allocation, request, and usage) based on the . Use a drop-down list to filter data with the needed value.
Clicking on a specific node type will navigate you to the workloads table, displaying the workloads associated with that node type. This view is particularly helpful for identifying the most wasteful workload running on the node with the selected type and providing data-driven recommendations on how to eliminate it in a few clicks. To explore the workload details at a deeper level, click on the specific workload to open a window that provides an in-depth view.
