Automatic Workload Rightsizing

Overview

Komodor’s Automated Rightsizing capability helps you continuously optimize your Kubernetes workloads by adjusting CPU and memory requests based on real usage patterns.

This feature moves beyond manual recommendations by:

Mutating pod specs automatically on creation/update
Enforcing safe, policy-driven resource limits
Providing full auditability and control

With Autopilot Rightsizing, you can reduce overprovisioning, cut cloud costs, and improve application reliability - all with minimal manual intervention.

What Is Rightsizing?

Rightsizing is the process of adjusting a container’s CPU and memory requests to match actual usage. Overprovisioned workloads waste money; underprovisioned workloads risk OOMKills, throttling, or instability.

Without Komodor:

You monitor usage manually
Apply changes via YAML or GitOps
Hope developers follow best practices

With Komodor:

Daily evaluations per workload
Automated enforcement with guardrails
Real-time observability and impact analysis

How Komodor Automates Rightsizing

Komodor uses a Kubernetes Admission Controller to:

Intercept pod creation/update events
Evaluate whether a pod is eligible for mutation
Apply optimized CPU/memory requests automatically
Label the pod for easy tracking of changes
Only pods are changed, therefore Komodor is GitOps friendly as it does not mutate the deployment, and therefore not leading to drifts.

Eligibility Criteria

Workloads must meet the following:

At least 7 days of historical usage data
Not managed by HPA (currently excluded)
Included in a rightsizing policy (manual or dynamic)
Not explicitly excluded by the user

Rightsizing Policies

Policies define when, where, and how Komodor can apply resource changes. Each policy can define the optimization strategy (the base percentile fed into the rightsizing recommendation algorithm), limits on the change magnitude (only apply if delta ≥ X%), Request buffers, configuration to allow upscaling/downscaling (independently toggleable), and more.

These guardrails ensure safe, stable behavior, even in sensitive environments.

Optimization Strategy

Specify the base percentile value (between 70 and 99) to be used in the rightsizing recommendation algorithm.

Komodor calculates this percentile over a 30-day sliding window and uses it as the baseline for the recommended resource values. The final recommendation also considers additional guardrails defined in your cost optimization policy.

Scope Types

Type	Description
Dynamic Scope	Based on rules (namespace, workload type, etc.)
Manually Added	Workloads enabled directly from the Rightsizing UI
Manually Excluded	Workloads opted-out by users despite being included as part of a dynamic scope (think of it as a “deny list”)

Each policy can currently target a single cluster and include wildcard-based definitions for flexibility.

Access to policy management requires the manage_cost_policies action as part of the user role.

Managing Automation from the Rightsizing Dashboard

The Rightsizing dashboard has two main tables:

Potential Savings Table

Lists workloads that could benefit from rightsizing
Includes:
- Current vs recommended requests
- Monthly savings estimate
- Under provisioned containers that may require rightsizing up
- Option to enable automation directly per workload

Active Savings Table

Lists workloads already managed by Komodor
Includes:
- Applied request values
- Number of affected pods out of the total number of replicas
- Estimated monthly savings
- Option to configure the rightsizing policy

Enabling or disabling automation updates the policy scope dynamically (manual vs excluded).

Top Summary Metrics

Visible at the top of the Rightsizing page:

Metric	Description
Monthly Potential Savings	How much you could save if all recommendations were applied
Under-provisioned Workloads	How many workloads were detected as under-provisioned and require rightsizing up
Monthly Active Savings	Current savings from automated workloads
Automated Workload %	% of eligible workloads currently under Komodor autopilot

Identify Automatic Rightsized Workloads

All rightsizing actions are auditable and can be tracked through the pod view itself.

Komodor can also issue full reports on all workload changes upon request (this will be added to the platform down the road).

You can also keep track easily using the labels Komodor creates on the pod.

Manual Rightsizing is Still Available

Komodor still provides the ability to manually change the requests of workloads based on its recommendations (calculated based on the last 30 days).

All functionality remains the same:

For non-automated workloads, an option to drill down to the usage and recommendation will exist.
In that modal, you can easily modify the requests of each container based on what you see fit (and potentially based on Komodor’s recommendation)