Free online client-side Kubernetes resource calculator and cluster capacity sizing tool. Calculate pod CPU and memory requests and limits, prevent OOMKilled crashes and CPU throttling, estimate minimum worker node hardware requirements, determine Pod Quality of Service (QoS) classes, and auto-generate Kubernetes ResourceQuota, LimitRange, and Helm values.yaml manifests.
Reserved for Kubelet & OS system pods.
Maximum safe target before auto-scaling.
apps/v1 & v1
Choose a pre-configured template (REST API, AI/ML Worker, Redis Cache, JVM Spring, or Static Web) or input custom CPU/Memory requests and limits.
Include optional sidecar proxy containers (Envoy, Service Mesh, Logging) and specify your target Horizontal Pod Autoscaler (HPA) replica counts.
Choose worker node hardware specs (vCPU and RAM) and adjust system overhead buffers (Kubelet/OS) and maximum target node utilization sliders.
Examine total cluster CPU/Memory demands, minimum required node count, bottleneck classification (CPU-bound vs Memory-bound), and Pod Quality of Service (QoS) class.
Copy or download the generated Pod `resources:` spec, namespace `ResourceQuota` YAML, `LimitRange` default limits, or Helm `values.yaml` snippet.
Calculate precise memory limits based on actual process heap baselines, preventing Linux kernel OOM killer terminations and Kubernetes Node pressure evictions.
Accurately size worker node instances (AWS EKS, GCP GKE, Azure AKS) based on aggregated pod CPU/Memory requests, avoiding over-provisioned idle cloud nodes.
Generate production-grade Kubernetes `ResourceQuota` and `LimitRange` manifests to prevent rogue workloads from consuming shared cluster hardware resources.
Ensure critical database or caching pods obtain `Guaranteed` QoS priority (equal requests & limits) while non-critical background jobs run under `Burstable` limits.
Efficiently managing compute resources in a Kubernetes cluster is essential for maintaining application stability, eliminating latency spikes, and controlling cloud infrastructure costs. In Kubernetes, container compute resources are defined using Requests and Limits for CPU and Memory.
Our Kubernetes Resource & Capacity Sizing Calculator performs real-time capacity modeling to help SREs and Cloud Architects establish optimal container resource allocations.
OOMKilled (Out Of Memory) process termination by the Linux kernel.m) or vCPU cores. 1000m equals 1 vCPU / Hyperthread core. A request of 250m represents 25% of a single vCPU.Mi for Mebibytes, Gi for Gibibytes). 1Gi equals 1024Mi (1,073,741,824 bytes).Kubernetes automatically assigns a QoS class to every pod based on its resource requests and limits configuration:
Every container in the pod has CPU and Memory requests set exactly equal to their limits. These pods are never evicted under node memory pressure unless system components crash.
Pod containers have requests specified, but limits are higher than requests (or limits are omitted for CPU). Burstable pods can burst up to their limit when node capacity is available.
Containers have no CPU or Memory requests or limits configured. BestEffort pods are the first to be killed when a worker node runs out of memory.
To calculate the minimum number of worker nodes required for a workload:
Create production Kubernetes Deployment, Service, Ingress, ConfigMap, and Secret manifests.
Visually build and validate production-ready Kubernetes NetworkPolicy manifests to enforce Zero-Trust microservice isolation, pod ingress/egress filtering, and CIDR ipBlock rules.