This topic describes optimizing a workload with Pod rightsizing.
A workload is optimized after the following steps:
You apply a Pod rightsizing policy to a workload.
Pod rightsizing changes the allocated resources according to the selected optimization strategy.
This process completes within an hour of applying the solution.
Resource optimization policies
You can apply the following built-in resource optimization policies:
Balanced: A balanced setup with moderate buffers and stable recommendations for general workloads.
Stability-focused: Prioritizes availability and resiliency by using longer lookback periods and larger buffers. Suitable for mission-critical or long-lived services.
Cost-focused: Aggressively minimizes overprovisioning to reduce cost with minimal buffers and fast reaction to utilization drops. Suitable for non-critical or stateless services.
For more information about the fixed parameter settings for the built-in policies, see Built-in policy fixed parameter values.
You can also create and use custom policies.
The following table demonstrates the Balanced optimization policy recommendations:
Over-provisioned | Under-provisioned | |
|---|---|---|
Current | 2.0 cores | 1.8 cores |
Actual (last 24 hours) | 0.6 cores | 1.0 cores |
Policy buffer calculation (20%) | 0.6 x 0.2 = 0.12 cores | 1.8 x 0.2 = 0.36 cores |
Recommendation | 0.6 + 0.12 = .72 cores | 1.8 + 0.36 = 2.16 cores |
Result | Reduce from 2.0 to 0.72 cores, saving 64% with safety buffer for spikes | Increase from 1.0 to 2.16 cores, preventing throttling and performance issues |
A workload could have both over-provisioned and under-provisioned recommendations, one for RAM and the other for CPU, or vice-versa.
After the initial resource reduction, Kompass continues to analyze and adjust the resources to ensure that managed workloads are being optimized according to the selected policy. Changes may be made every hour or when an optimization policy is changed.
You can apply Pod rightsizing to a workload using the user interface or using YAML.
After Pod rightsizing is active on a workload, you can see the impact on the workload in terms of CPU, RAM, cost, and other metrics. You can also change the selected optimization policy or remove the solution entirely. For more info, see Apply and manage Pod rightsizing.
Changes made by the solution are logged in the Audit log.
For information about supported environments and limitations, see Compute solutions supported environments and limitations.
See also: