Continuous, Data-Driven Optimization

Peak Kubernetes performance at the lowest possible cost — without engineering overhead.

One-line Helm chart, insights on day one

Continuous, context-aware right-sizing with safety guardrails

Proactive resilience and performance risks detection and remediation

Comprehensive node-level visibility and actionable insights

Policy-driven autonomous optimization

Impact-aware alerting and anomaly detection

Homegrown DYI Stack

An Open-Source Tools Stack

VPA + Goldilocks dashboard + Robusta KRR for one-off audits + Prometheus + custom scripts.

Months of engineering effort before initial capability

Recommendations are periodic, requires manual adjustments, in many cases reactive.

No resilience awareness, performance risks discovered through production incidents

Implemented node-autoscaling based on guesstimated configurations

Each tool is maintained independently, requiring constant oversight

What the DIY Stack Actually Looks Like

Building in-house Kubernetes right-sizing means combining open-source tools with custom automation scripts. Here’s what that stack usually looks like

VPA

VPA can help with basic right-sizing by generating CPU and memory recommendations for containers.

It lacks impact and context awareness, so it requires manual review to reduce production risk. It also doesn’t work well with HPA. And because it relies heavily on recent usage data, it is a poor fit for highly dynamic or short-lived workloads, especially AI/ML applications where usage patterns change fast.

Goldilocks

Labels namespaces, creates VPA objects automatically, and shows recommendations in a dashboard.

It makes VPA easier to use at scale, but the visibility stays limited. You can see what VPA recommends, but not the context behind it: workload behavior over time, revision-awareness, business or performance impact, or whether applying it actually makes sense.

KRR

Analyzes Prometheus data and recommends CPU and memory requests for workloads.

It helps reduce right-sizing guesswork, but it still depends on metrics history and gives limited context around workload changes, production risk, requiring manual reviews.

Prometheus + Grafana + Custom Scripts

Prometheus provides the metrics layer for the DIY stack, while Grafana dashboards and custom scripts turn those metrics into actions.

Relying on Prometheus metrics adds extra effort and increases the cluster footprint, with ongoing maintenance around storage, retention, query performance, scripts, PR automation, and breakages when Prometheus or Kubernetes changes.

Feature Comparison

Understand the differences between PerfectScale and a typical DIY optimization stack.

Homegrown

Setup & Operations

Time to insight

Minutes

Weeks

Installation

One-line Helm

Integrate VPA + Goldilocks + Prometheus + scripts

TCO

Low (Fully managed, auto-updates)

High (Prometheus ops, script fixes, versions)

Prometheus dependency

Independent (own lightweight agent)

Heavy dependency

Cost Visibility & Reporting

Cloud billing integration (AWS/GCP/Azure)

Manual integration effort

Workload-level cost allocation

Partial

Ephemeral workload visibility (Spark, Jobs, ML)

Wasted cost forecast

Rollout awareness

Code revision impact visibility

Node group support and idle space visibility

Cost & Performance Optimization

CPU and Memory request recommendations

CPU and Memory limit recommendations

Adaptive resiliency-aware policies

Node-level optimization recommendations

If node autoscaler is implemented and properly configured

Resilience & Risk Management

Automated resilience risk detection

Impact-driven risk prioritization

Suspected memory leak indication

Autonomous resilience risk remediation

Automation & Integration

Production-ready autonomous optimization

Basic

Code revision-aware automation

HPA-aware optimization

GitOps / IaC integration

Custom effort

Configurable maintenance windows

Operations & Compliance

Prometheus-independent operation

Dedicated optimization specialist support

Maintenance Overhead

Low

Requires deep expertise, continuous development and maintenance

The True Cost of “Free” Open-Source

Homegrown tools are not free, as they’re paid for in engineering time, the most expensive resource you have.

6-12 mo

Initial Build

To integrate VPA + Goldilocks + KRR + Prometheus + custom scripts into a solution that produces actionable, automated results across the entire K8s stack.

1-2 FTEs

Ongoing Maintenance

Each release or version can break VPA CRDs, Prometheus exporters, and your custom scripts. Someone must keep an eye on it.

30-60%

Savings Left on the Table

PerfectScale customers consistently find additional savings on top of what their existing tooling captured, plus cost of mitigated resilience incidents.

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