GKE Cost Optimization

MCP Tools:

get_k8s_resource

,

describe_k8s_resource

,

apply_k8s_manifest

,

patch_k8s_resource

,

get_cluster

Golden Path Cost Features

autoscalingProfile

OPTIMIZE_UTILIZATION

verticalPodAutoscaling

enabled

Workflows & Optimization Strategies

1. Prerequisite: Cost Allocation & Monitoring

--enable-cost-allocation

kubectl top

bq

gke-cost-analysis

2. Configure Resource Quotas

kubectl apply -f - <<EOF
apiVersion: v1
kind: ResourceQuota
metadata:
  name: compute-quota
  namespace: {namespace}
spec:
  hard:
    requests.cpu: "4"
    requests.memory: 16Gi
    limits.cpu: "8"
    limits.memory: 32Gi
EOF

3. Pod Rightsizing (VPA & MPA)

• Use VPA in Recommendation Mode:

# 1. Deploy VPA in recommendation mode
kubectl apply -f - <<EOF
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: {deployment_name}-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: {deployment_name}
  updatePolicy:
    updateMode: "Off"
EOF

# 2. Wait 24+ hours for data collection

# 3. Read recommendations
kubectl get vpa {deployment_name}-vpa -o jsonpath='{.status.recommendation}'

• Optimization Rules:

P95 * 1.2

P95 * 1.2

P95 * 1.2

• Use MPA: Reconcile HPA and VPA recommendations when scaling both horizontally and vertically to avoid conflicting scale events.
• Review Cost Recommendations: Check Google Cloud Console (

  Cost Management

  >

  GKE Cost Optimization

  ) for built-in rightsizing suggestions.

4. Spot VMs via ComputeClasses & NodeSelector

4.1 ComputeClass Configuration

apiVersion: cloud.google.com/v1
kind: ComputeClass
metadata:
  name: spot-with-fallback
spec:
  activeMigration:
    optimizeRulePriority: true
  priorities:
  - machineFamily: n4
    spot: true
  - machineFamily: n4
    spot: false

4.2 Direct Workload Spot Selection (

nodeSelector

)

nodeSelector

[!WARNING] Preemption Warning: Spot VMs are interruptible and can be preempted at any time with a 30-second notice. Workloads must be fault-tolerant and run with at least 2 replicas for high availability. Always explicitly warn users about this preemption risk when recommending Spot VMs.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: stateless-spot-app
spec:
  replicas: 2
  template:
    spec:
      nodeSelector:
        cloud.google.com/gke-provisioning: Spot
      terminationGracePeriodSeconds: 25  # Must be < 30s for Spot preemption handling
      containers:
      - name: app
        image: {image_name}
        lifecycle:
          preStop:
            exec:
              command: ["/bin/sh", "-c", "sleep 5"]

5. Machine Type Selection

6. Committed Use Discounts (CUDs)

• 1-year: ~20-30% discount
• 3-year: ~50-55% discount
• Applied automatically to matching usage across the region.
• Purchase via Google Cloud Console > Billing > Committed use discounts.

7. Cluster Management & Multi-Tenancy

• Stop/start dev clusters: Idle dev clusters cost money even with no workloads due to control plane fees.
• Right-size node pools (Standard): Use Cluster Autoscaler with appropriate min/max limits.
• Multi-tenant consolidation: Share a single cluster across multiple engineering teams instead of maintaining per-team clusters, using Namespaces and ResourceQuotas to isolate workloads.

Cost & Utilization Monitoring

kubectl top nodes/pods

gcloud billing budgets list

bq query

gke-cost-analysis

Dev/Test Cost Savings

SYSTEM_COMPONENTS

Best Practices Summary

1. Enable Cost Allocation: Always enable GKE cost allocation (

   --enable-cost-allocation

   ) to gain billing transparency across namespaces and labels.
2. Enforce Resource Quotas: Restrict namespace CPU/memory limits in multi-tenant environments to prevent runaway costs or noisy neighbors.
3. Rightsize Continuously: Run VPA in recommendation mode (

   updateMode: Off

   ) and adjust requests to match

   P95 * 1.2

   .
4. Leverage Spot VMs: Use Spot VMs with

   nodeSelector

   or

   ComputeClass

   for stateless, fault-tolerant workloads to save 60-90%.
5. Optimize Autoscaling Profile: Use

   OPTIMIZE_UTILIZATION

   for aggressive node scale-down on idle compute.
6. Consolidate & Clean Up: Stop idle development clusters and consolidate multi-team workloads into shared multi-tenant clusters.