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	false	Allows PerfectScale to consider the resource changes in the original spec and changes of current resources.
perfectscale.io/workload-grouping-honor-image	false	Allows PerfectScale to consider the image name in the calculated hash.

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.