---
title: "Pod rightsizing"
slug: "pod-rightsizing"
updated: 2026-07-14T14:11:35Z
published: 2026-07-15T11:56:55Z
canonical: "docs.zesty.co/pod-rightsizing"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zesty.co/llms.txt
> Use this file to discover all available pages before exploring further.

# Pod rightsizing

This section describes the Kompass Pod rightsizing optimization solution.

Kubernetes scaling typically focuses on horizontal adjustments—adding or removing pods—but that alone doesn’t address inefficiencies from misconfigured resource requests **within pods**. The Kompass **Pod rightsizing solution** complements horizontal scaling with automated vertical adjustments, ensuring each container has the right CPU (vCPU) and memory allocation (GiB) based on real usage. **Benefits of Pod rightsizing include**:

- Reduce resource waste caused by inaccurate CPU and memory requests.
- Improve workload stability by identifying workloads at risk of underprovisioning and aligning them with actual demand.
- Eliminate manual resource tuning.
- Continuously optimize workloads through policy-driven automation. Pod rightsizing works frictionlessly with horizontal autoscalers (like HPA, KEDA) that optimize cluster-wide capacity, by fine-tuning resources at the Pod level to reduce waste and improve workload stability.

Pod rightsizing identifies these types of nonoptimized workloads:

- **Under-provisioned workload**: memory or CPU exceed recommended utilization Kompass recommends to increase vCPU or Gi requests
- **Over-provisioned workload**: memory or CPU are far from recommended utilization Kompass recommends to decrease vCPU or Gi requests

The Pod rightsizing solution provides detailed recommendations for rightsizing CPU and memory requests, but its core strength is **automated correction**: When you apply Pod rightsizing to a workload, Kompass adjusts workload resources in real time to keep workloads optimized without manual effort. Built-in rollback mechanisms protect workload stability by reverting changes if CPU throttling or out-of-memory (OOM) events occur.

Pod rightsizing behavior is managed through **Policies**. Policies allow you to apply opinionated, goal-driven configurations that adapt rightsizing behavior per workload type and usage pattern. When a workload is matched by a policy, rightsizing is applied to that workload. To ensure consistent optimization, each workload is managed by no more than one policy at any given time.

The solution integrates with GitOps tools like ArgoCD, ensuring changes align with CI/CD workflows and are not overridden.

For teams running Kubernetes at scale, it reduces manual overhead, enforces consistency, and helps maintain efficient, stable resource usage across clusters.

Pod rightsizing relies on these components in the cluster:

- The **Insights agent** is installed. This agent provides visibility into the workloads running in the cluster. It can take up to 24 hours after installing the agent for Kompass to deliver recommendations.
- The **Pod rightsizing solution** is enabled. When the solution is enabled, you can apply it to workloads. It can take up to 1 hour after enabling the solution before you can apply it to workloads.

For more information, see [Deploy Kubernetes resource optimization solutions](/v1/docs/deploy-kubernetes-resource-optimization-solutions).

####