Stop Overpaying for Kubernetes

Our AI agents analyze your resource allocation, utilization, and cloud spend — every recommendation comes with a dollar amount and a specific before/after YAML diff. Works with EKS, GKE, AKS, and self-managed clusters.

Duration: 5-10 days Team: 1 Senior K8s Consultant + AI Cost Agents
The Challenge

You might be experiencing...

EKS/GKE/AKS bills growing 40% QoQ with no visibility into which teams or services are driving the cost
Resource requests set once and never adjusted — most pods are 2-5x over-provisioned
No visibility into which teams, namespaces, or services are driving costs
Non-prod environments running 24/7 at production scale
Our Approach

Engagement Phases

Days 1-2

Data Collection

Deploy cost visibility tooling. Export 30-day Prometheus metrics and cloud billing data (AWS Cost Explorer, GCP Billing, Azure Cost Management). Map namespaces to teams.

Days 3-4

AI-Powered Analysis

AI agents analyze right-sizing opportunities, idle resources, spot/preemptible eligibility, and reserved capacity gaps. Cross-reference with FinOps Foundation FOCUS spec.

Day 5

Report & Roadmap

Deliver cost optimization report with per-namespace breakdown and week-by-week implementation plan.

What You Get

Deliverables

Cost optimization report with current spend vs. target
Per-namespace cost breakdown with waste percentage
Right-sizing recommendations per pod (before/after YAML)
Spot/preemptible instance strategy for AWS, GCP, and Azure
Idle resource cleanup list with $ savings
Week-by-week implementation roadmap
FinOps tooling recommendations (Kubecost, VPA, Karpenter)
Reserved instance / committed use discount analysis
Expected Outcomes

Before & After

MetricBeforeAfter
Monthly K8s Spend$48K/month$28K/month (42% savings)
CPU Utilization25-35%60-75%
Cost VisibilityNo namespace attribution100% cost attribution
Resource Request Accuracy20-30%80%+
Technology

Tools We Use

Kubecost OpenCost Prometheus VPA Karpenter Claude Code Agents
Common Questions

Frequently Asked Questions

How much can we realistically save on Kubernetes costs?

Most organizations find 30-50% cost waste in their Kubernetes environments. Common savings come from right-sizing over-provisioned pods, eliminating idle resources, implementing spot instance strategies on AWS, GCP, or Azure, and scheduling non-production environments. We provide exact dollar amounts per namespace.

How long does the cost optimization engagement take?

The engagement runs 5-10 days. Days 1-2 cover data collection and cost visibility tooling deployment, days 3-4 use AI agents to analyze right-sizing opportunities and spot eligibility, and day 5 delivers the cost optimization report with a week-by-week implementation plan.

Do you implement the changes or just provide recommendations?

We deliver actionable before/after YAML diffs for every right-sizing recommendation, plus a week-by-week implementation roadmap. We can also implement the changes directly if you prefer hands-on execution support.

Will cost optimization affect application performance?

No. Our AI agents analyze 30 days of Prometheus metrics to understand actual resource utilization patterns before recommending changes. Right-sizing recommendations maintain appropriate headroom for traffic spikes and include VPA configurations for ongoing auto-adjustment.

What ongoing cost management tools do you recommend?

We recommend Kubecost or OpenCost for cost visibility and attribution, VPA (Vertical Pod Autoscaler) for automated right-sizing, and Karpenter for intelligent node provisioning. We also recommend integrating with AWS Cost Explorer, GCP Billing, or Azure Cost Management for cloud-level visibility aligned with the FinOps Foundation FOCUS spec.

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