Ephemeral Pods Grouping

Leverage advanced PerfectScale grouping to streamline your optimization process even for highly dynamic environments

The PerfectScale grouping configuration is a powerful tool that enables the aggregation of redundant workloads exhibiting similar patterns. By preventing overload through batches of identical information, it enables you to focus on what matters, thereby streamlining analysis processes.

Custom grouping is a rule that aggregates multiple workloads into a single entity (for example, all GitLab runners are aggregated into a single entity—the GitLab workload), merging their data (resource usage, limits, requests, etc.).

This feature is especially convenient when using Spark, GitLab, Airflow or any other operators that produce short-lived, small workloads that often reflect just a single pod in the cluster, or when automating the ungrouped workloads.

Grouping by labels

To group the workloads, two predefined labels should be added to this workload:

Key	Value	Description
perfectscale.io/workload-grouping-workload-name	custom-workload-name	Specifies a target workload name
perfectscale.io/workload-grouping-workload-type	custom-workload-type	Specifies a target workload type

This grouping approach is specifically helpful for automating dynamic, short-lived workloads.

Labels perfectscale.io/workload-grouping-workload-name and perfectscale.io/workload-grouping-workload-type are required to configure automation for ephemeral workloads. After applying the labels, a new workload will appear in PerfectScale. However, automation will only reduce resources after sufficient data has been collected.

To ensure PerfectScale considers all revisions, including those not made by Automation, and to drive better results, you can optionally specify the following labels:

Key	Value	Description
perfectscale.io/workload-grouping-honor-spec	true false (default)	Allows PerfectScale to consider the resource changes in the original spec and changes to current resources. When to use? Set to true if: You are manually changing spec resources (set by the customer in the parent object) and want PerfectScale to respect those changes. ❗Note: To ensure predictable automation behavior, use this label with the value true only when all workloads in the group have equal resources. You want every manual resource change revision to appear in the Revisions Timeline.
perfectscale.io/workload-grouping-honor-image	true false (default)	Allows PerfectScale to consider the image name in the calculated hash. When to use? Set to true if: If you want to see the deployment history in the timeline when the application version (image) changes. ❗Note: Each update will create a new revision in the Revisions Timeline, which may result in a large number of entries.

If you enable automation for a custom workload type, the WorkloadLabelsSelector in a cluster or namespace configuration will not be applied. All workloads of that custom type will be automated despite the label's configuration.