The Six Most Common GCP Cost Leaks
1. Over-Provisioned Compute Instances
The most common cause of waste. Most teams provision n2-standard-8 instances for workloads that only need n2-standard-2.
Fix: Enable Google Cloud's recommender and apply right-sizing recommendations:
gcloud recommender recommendations list \
--project=YOUR_PROJECT \
--recommender=google.compute.instance.MachineTypeRecommender
Typical savings: 25–40% of compute spend.
2. Unattached Persistent Disks
When you delete a VM, its boot disk persists by default. These accumulate silently.
# List unattached disks
gcloud compute disks list --filter="NOT users:*" --format="table(name,sizeGb,zone)"
3. Missing Committed Use Discounts (CUDs)
If you run workloads 24/7 for 12+ months, you're leaving 20–55% on the table by paying on-demand rates.
Purchase 1-year or 3-year CUDs for baseline workloads.
4. Inefficient Cloud Storage Classes
Standard storage is 3× the price of Nearline and 6× Coldline. Most teams store all data in Standard.
Fix: Enable Object Lifecycle Management:
{
"lifecycle": {
"rule": [
{
"action": { "type": "SetStorageClass", "storageClass": "NEARLINE" },
"condition": { "age": 30 }
}
]
}
}
5. Unoptimised Cloud SQL Instances
Cloud SQL instances charge for CPU and RAM even when idle. Many teams run dev/staging databases 24/7.
Fix: Set automatic stop schedules for non-production instances.
6. Egress Costs from Cross-Region Traffic
GCP charges for data leaving a region. Architectures with components in multiple regions generate hidden egress costs.
Audit: Review Network Intelligence Center for inter-region traffic patterns.
A Real Example
We reduced a UK FinTech's GCP bill from £14,500/month to £8,250/month - a 43% reduction - in two weeks. The changes were entirely configuration-based: no code changes, no architecture redesign, no risk.
Read the full case study for the detailed breakdown.
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