Exploring Automation KPIs
Automation performance evaluation offers insights into automation-driven actions, highlighting their impact on resource optimization and overall efficiency
Last updated
Automation performance evaluation offers insights into automation-driven actions, highlighting their impact on resource optimization and overall efficiency
Last updated
The Automation screen offers a detailed overview of all actions PerfectScale Automation performs across your environment, highlighting their impact on resource optimization. This view provides clear insights into automation-driven optimization results and helps seamlessly evaluate its efficiency.
With the provided level of information granularity, you can effortlessly review a detailed breakdown of the actions taken by Automation. This includes insights into the specific tasks executed, the containers affected, and the precise timestamps indicating when each action occurred. Such comprehensive visibility ensures thorough oversight and facilitates further analysis.
PerfectScale provides a detailed and transparent view of automation performance, enabling you to evaluate the progress of automation-driven optimization effectively. This comprehensive insight enables you to monitor key metrics and understand how automation improves resource allocation, enhancing the stability and cost-effectiveness of your environment.
This widget highlights the resiliency risks that PerfectScale's automation has addressed within the selected time frame. In the top right corner, you can see the total count of risks addressed during this period.
To view the specific number of risks resolved on any given date, hover over the corresponding bar in the chart.
This view allows you to seamlessly evaluate the optimization actions performed by automation to enhance the stability and resiliency of your Kubernetes clusters.
The CPU optimization widget displays changes in CPU requests over time, giving you a detailed view of how Automation has optimized CPU allocation for workloads and their replicas. It provides a detailed visual comparison of the adjustments made against the original configurations, offering transparent insight into the efficiency improvements achieved during the selected period.
To check the details of CPU optimization performed by Automation on a specific date, hover over the corresponding bar in the chart.
Original Requests
The original requests reflect the sum of CPU requests from the initial configurations of all workloads and their replicas at the selected time.
Optimized Requests
The optimized requests represent the sum of CPU requests allocated by Automation for all workloads and their replicas at the selected time.
Impact
Impact quantifies the difference between the CPU requests from the original configuration and those allocated by Automation, providing clear visibility into how effectively Automation optimizes CPU allocation for your clusters.
The Memory optimization widget displays changes in Memory requests over time, giving you a detailed view of how Automation has optimized Memory allocation for workloads and their replicas. It provides a detailed visual comparison of the adjustments made against the original configurations, offering transparent insight into the efficiency improvements achieved during the selected period.
To check the details of Memory optimization performed by Automation on a specific date, hover over the corresponding bar in the chart.
Original Requests
The original requests reflect the sum of Memory requests from the initial configurations of all workloads and their replicas at the selected time.
Optimized Requests
The optimized requests represent the sum of Memory requests allocated by Automation for all workloads and their replicas at the selected time.
Impact
Impact quantifies the difference between the Memory requests from the original configuration and those allocated by Automation, providing clear visibility into how effectively Automation optimizes Memory allocation for your clusters.
Started at
The timestamp indicates when the automated action was initiated.
Cluster
Indicates which cluster the automated action was taken in.
Namespace
Indicates which namespace the automated action was taken in.
Workload
Indicates which workload the automated action was taken in.
Type
Container
Indicates which container the automated action was taken in.
CPU Request
Displays the CPU request change if any action was taken.
CPU Limit
Displays the CPU limit change if any action was taken.
Memory Request
Displays the Memory request change if any action was taken.
Memory Limit
Displays the Memory limit change from its previous value to the new one if any action was taken.
PerfectScale empowers you to customize your Automation Audit Log view, enabling you to focus on what matters to you.
📌 To filter the data by a specific value, use a drop-down list at the top of the columns.
Available filters:
Cluster
Namespace
Workload
Type
Container
📐 Choose your preferred format for displaying changes to resources with the advanced filters
Detailed - to display the changes made to resources (shows both the previous and new values).
Total Changes in Units - to display changes made to resources as an absolute number, factoring in replica count.
Single Instance Changes in Units - to display changes made to resources as an absolute number.
Single Instance Change in % - to display changes made to resources in a percentage format.
The export feature gives you the ability to export your data into a .csv file for seamless analysis and effortless sharing. Click the Export button, and the data will be exported in a second.
Indicates the type of workload in which the automated action was taken. Automation is currently available for workloads of the following types: Deployment, DaemonSet, StatefulSet, CronJob, and Job.
To sort the data in the desired order, simply click on the title of the column.
Hover over the results to get more details on the resource changes
