GCP Cost Optimization: A Practical Guide for Engineering Teams

Published: 2026-05-20
Author: Saascutters
Read time: 7 minutes
Keywords: GCP cost optimization, Google Cloud spend reduction, GKE cost, BigQuery pricing, GCP FinOps

Google Cloud Platform bills differently than AWS. The pricing model is often more transparent, but the waste hides in different places — sustained use discounts that do not apply, BigQuery slots that never sleep, and Cloud Storage buckets left in Standard for years.

Here is what we look for in the first week of every GCP engagement.

1. Verify sustained use discounts are applied

GCP automatically applies sustained use discounts to VMs that run more than 25% of the month. But custom machine types, preemptible instances, and VMs with local SSDs do not qualify. Go to Billing → Cost Breakdown → Discounts and confirm every discount you expect is actually there. Missing discounts on a fleet of 40+ VMs can cost $10,000+ per year.

2. Rightsize your committed use discounts (CUDs)

CUDs are GCP's answer to reserved instances. They require a one- or three-year commitment. The trap: teams buy CUDs based on projected growth, then never grow into them. Check your CUD utilization in the Billing dashboard. Anything under 90% utilization means you committed to capacity you do not need.

3. Audit BigQuery slot consumption

BigQuery on-demand pricing charges per TB scanned. A single poorly written query can scan 5 TB and cost $25. If your monthly BigQuery bill is over $3,000, switch to flat-rate pricing and buy a reservation. Then enforce partitioned tables and require WHERE clauses on date partitions. The savings are immediate and large.

4. Fix Cloud Storage classes

Standard storage is the default for every new bucket. If your data is accessed less than once per month, move it to Nearline or Coldline. The price drop is 50–70%. Use Object Lifecycle Management to automate the transition after 30 or 90 days. One healthcare client was paying $4,200 per month for Standard storage on five-year-old logs. Coldline cut it to $840.

5. Review Cloud SQL instance sizing

Cloud SQL instances are often over-provisioned because the creation wizard defaults to db-n1-standard-2 or larger. Check your CPU and memory utilization over the last thirty days. If average CPU is under 15%, downgrade. If you are running a single read replica for reporting, consider Cloud SQL Insights first — the replica may not be necessary.

6. Check GKE autoscaling behavior

GKE clusters with node autoscaling enabled can scale up faster than they scale down. Review your node pool metrics. Nodes that have been running for weeks with average CPU under 10% are candidates for a smaller machine type or a second, smaller node pool for non-production workloads.

7. Validate your network egress

GCP charges for egress between regions, between zones in some cases, and to the internet. Use VPC Flow Logs to identify the largest egress flows. Common culprits: syncing Cloud Storage buckets across regions for "disaster recovery" that was never tested, and GKE clusters in us-central1 talking to Cloud SQL in us-east1.

When the audit is bigger than one sprint

If your monthly GCP spend is over $40,000, an internal audit will take two to three weeks of dedicated engineering time — time your team probably does not have. A performance-based engineering practice can run the full analysis, execute the changes, and verify the savings against your prior invoices.

Saascutters specializes in SaaS, cloud, and infrastructure cost reduction. We take thirty percent of verified first-year savings. No retainer. No upfront fee. Request a GCP audit →