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Managed Kubernetes

Kubernetes Cost Optimization: Cut Infrastructure Spend Without Sacrificing Performance

Kubernetes is powerful, but unoptimized, also expensive. We have helped customers reduce their cloud spend by 40-60% without shutting down a single service.

Analyze cost potential Request optimization assessment
40-60%
Cost Reduction
Average cloud spend reduction after optimization
Kubecost
Transparency
Real-time cost visibility per namespace, service and team
Spot
Instances
60-80% cheaper compute capacity for eligible workloads
ROI
in 90 days
Optimization costs typically amortize in under 3 months

Most Kubernetes environments CCsolutions assesses share the same finding: oversized nodes, too-high resource requests, no spot instance usage, and workloads running outside business hours as if no one is coming back in the morning.

The most common challenges

1

Resource requests are set too high

Teams set CPU and memory requests conservatively, for good reason, they do not want OOM kills. But systematically high requests block node capacity that is never used.

2

No use of spot or preemptible instances

Spot instances on AWS, Azure and GCP cost 60-80% less than on-demand. Kubernetes workloads are designed for spot, but only when the architecture implements it correctly.

3

Dev and staging environments run 24/7 at full capacity

Development environments do not need full capacity at night and on weekends. Automatic scale-to-zero saves 40-60% of the costs of those clusters.

The CCsolutions approach

CCsolutions conducts a structured cost optimization assessment using Kubernetes-native tools (Kubecost, Goldilocks) to analyze actual resource consumption, not what manifests say, but what workloads actually use.

The assessment produces prioritized actions: right-sizing resource requests, migrating eligible workloads to spot instances, automatic scale-to-zero for non-production environments, and cluster consolidation.

All actions are implemented with measurable targets, no paper optimism. We define the expected savings before implementing and measure afterwards.

Technologies

Kubecost Goldilocks KEDA Cluster Autoscaler Spot Instances VPA HPA

Frequently asked questions

Do spot instances work for production workloads?

For stateless workloads with correct Pod Disruption Budgets and replica strategies: yes. For stateful workloads (databases, etc.): no, those stay on on-demand. The skill is correctly classifying workloads.

Ready to get started?

We analyse your situation for free and show what is possible in your specific case.

Analyze cost potential