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Kubernetes Resource Calculator

Right-size your K8s workloads with optimal resource requests, limits, and HPA configuration. Compare EKS Fargate vs EC2 costs with live AWS pricing data. Generate production-ready YAML manifests. 100% Browser-Based

Workload Presets

Compute Mode

Resource Configuration

m
m
Mi
Mi
%

Avg Replicas

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Total CPU

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requests x avg replicas

Total Memory

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requests x avg replicas

Est. Monthly Cost

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Cost Breakdown

Line Item Qty Unit Price Monthly

Generated YAML Manifests

Kubernetes Resource Fundamentals

Resource Requests vs Limits

Requests are what your container is guaranteed. The scheduler uses them to place pods on nodes. Limits are the maximum your container can use before being throttled (CPU) or killed (memory). Set requests based on steady-state usage and limits based on peak spikes.

Quality of Service Classes

Kubernetes assigns QoS classes based on resource settings. Guaranteed (requests = limits) pods are never evicted first. Burstable pods (requests < limits) can use extra resources when available. BestEffort pods (no resources set) are evicted first under memory pressure.

Horizontal Pod Autoscaling

HPA adjusts replica count based on CPU utilization (or custom metrics). A 70% CPU target is typical for web workloads. Setting it too low wastes resources; too high risks latency spikes during scale-up. HPA requires resource requests to be set on containers.

Right-Sizing Strategy

Start with conservative requests, monitor actual usage with metrics-server or Prometheus, and adjust iteratively. Over-provisioning wastes money; under-provisioning causes OOMKills and throttling. The Vertical Pod Autoscaler (VPA) can recommend values based on observed usage.

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