GCP Cost Optimization: Reduce Your Google Cloud Bill

# Purchase a Compute Engine CUD (1-year)
gcloud compute commitments create \
  --region us-central1 \
  --name cud-1yr-8vcpu \
  --resources vcpu=8,memory=32768 \
  --plan 12-month \
  --type general-purpose

# Purchase a CUD for GPUs (3-year)
gcloud compute commitments create \
  --region us-central1 \
  --name cud-3yr-t4 \
  --resources vcpu=16,memory=65536,gpu=2 \
  --plan 36-month \
  --type accelerators

# List existing commitments
gcloud compute commitments list --region us-central1

[
    {
        "name": "cud-1yr-8vcpu",
        "plan": "12-month",
        "resources": {"vcpu": "8", "memory": "32768MB"},
        "status": "NOT_YET_ACTIVE",
        "startTimestamp": "2026-06-21T00:00:00Z]
    }
]

# sustained_use_calculator.py
def calculate_sustained_use_discount(hours_run: int, monthly_hours: int = 730) -> float:
    """Calculate automatic sustained use discount for a single VM."""
    usage_percentage = (hours_run / monthly_hours) * 100
    
    if usage_percentage <= 25:
        discount = 0.0
    elif usage_percentage <= 50:
        discount = 10.0
    elif usage_percentage <= 75:
        discount = 20.0
    else:
        discount = 30.0
    
    return discount

def monthly_cost(instance_type: str, hours: int, base_rate: float) -> dict:
    discount = calculate_sustained_use_discount(hours)
    discounted_rate = base_rate * (1 - discount / 100)
    total_cost = discounted_rate * hours
    
    return {
        "instance": instance_type,
        "hours": hours,
        "usage_pct": round((hours / 730) * 100, 1),
        "discount_pct": discount,
        "effective_rate": round(discounted_rate, 4),
        "total_cost": round(total_cost, 2)
    }

vms = [
    ("n2-standard-4", 730, 0.095), "# Full month
    ("n2-standard-4"", 400, 0.095), "# Half month
    ("n2-standard-4"", 100, 0.095),   # Short burst
]

for vm in vms:
    result = monthly_cost(*vm)
    print(f"{result['instance']:15} {result['hours']:4}h ({result['usage_pct']:5.1f}%) "
          f"-> {result['discount_pct']:2.0f}% off -> ${result['total_cost']:>7.2f}")

# Create a preemptible VM
gcloud compute instances create batch-worker-01 \
  --zone us-central1-a \
  --machine-type n2-standard-8 \
  --preemptible \
  --max-run-duration 14400s

# Create a Spot VM with proactive termination handling
gcloud compute instances create spot-worker-01 \
  --zone us-central1-a \
  --machine-type n2-standard-8 \
  --provisioning-model SPOT \
  --instance-termination-action STOP

# Create a preemptible instance template for managed instance groups
gcloud compute instance-templates create preemptible-template \
  --machine-type n2-standard-4 \
  --preemptible \
  --image-family ubuntu-2204-lts \
  --image-project ubuntu-os-cloud

#!/bin/bash
# preemptible-shutdown.sh — runs when GCP signals preemption
# Set up with: gcloud compute instances add-metadata \
#   --metadata shutdown-script="$(cat preemptible-shutdown.sh)"

echo "Preemption notice received. Saving checkpoint..."
JOB_DIR="/var/checkpoints"

# Save job state to persistent storage
if [ -f "$JOB_DIR/current_job.state" ]; then
    gsutil cp "$JOB_DIR/current_job.state" "gs://dodatech-checkpoints/$(hostname)-$(date +%s).state"
    echo "Checkpoint saved."
fi

# Drain connections
echo "Draining active connections..."
sleep 5

# Signal completion
curl -X POST -H "Content-Type: application/json" \
  -d '{"instance": "'$(hostname)'", "status": "shutdown", "checkpoint": true}' \
  https://monitor.dodatech.com/events

echo "Shutdown complete."

# List rightsizing recommendations
gcloud recommender recommendations list \
  --project=my-project \
  --location=us-central1-a \
  --recommender=google.compute.instance.MachineTypeRecommender \
  --format="json"

# Apply a recommendation (resize instance)
gcloud compute instances set-machine-type my-instance \
  --machine-type e2-standard-4 \
  --zone us-central1-a

# List idle IP address recommendations
gcloud recommender recommendations list \
  --project=my-project \
  --location=global \
  --recommender=google.compute.address.IdleResourceRecommender

{
    "recommendation": "Change machine type from n2-standard-8 to n2-standard-4",
    "costProjection": {
        "monthlySavings": {"currency": "USD", "value": 98.56}
    },
    "primaryImpact": {
        "category": "COST",
        "costProjectionBefore": 197.12,
        "costProjectionAfter": 98.56
    }
}

# Create a lifecycle policy to tier data
gcloud storage buckets update gs://dodatech-logs \
  --lifecycle-file=- <<EOF
{
  "lifecycle": {
    "rule": [
      {
        "action": {"type": "SetStorageClass", "storageClass": "NEARLINE"},
        "condition": {"age": 30, "matchesStorageClass": ["STANDARD"]}
      },
      {
        "action": {"type": "SetStorageClass", "storageClass": "COLDLINE"},
        "condition": {"age": 90, "matchesStorageClass": ["NEARLINE"]}
      },
      {
        "action": {"type": "SetStorageClass", "storageClass": "ARCHIVE"},
        "condition": {"age": 365, "matchesStorageClass": ["COLDLINE"]}
      },
      {
        "action": {"type": "Delete"},
        "condition": {"age": 730}
      }
    ]
  }
}
EOF

# Check current storage class breakdown
gsutil du -s -c gs://dodatech-logs/**