Google Cloud Optimization
Committed Use Discounts, BigQuery cost intelligence, and autoscaling.
GCP's discount model rewards commitment, but only if the sizing is right
Committed Use Discounts lock you into a spend level for 1-3 years. Get it wrong and you're either overcommitted and paying for capacity you don't use, or undercommitted and leaving guaranteed savings unclaimed. Meanwhile, BigQuery's on-demand pricing can spike without warning.
Data-driven commitment sizing and query-level visibility
OptCloud analyzes your actual sustained usage before recommending any CUD purchase, and breaks BigQuery spend down to the query and job level, so you can see exactly which workloads are driving cost before choosing between on-demand and flat-rate slots.
What GCP teams get with OptCloud
See BigQuery cost at the query level
Slot usage and bytes-scanned tracking down to individual queries and scheduled jobs means you can catch an expensive query before it becomes next month's surprise line item.
142 TB scanned last month at on-demand rates, a flat-rate slot commitment is recommended.
Size Committed Use Discounts correctly, every time
We model your last 90 days of sustained Compute Engine and GKE usage against every available CUD term, showing the exact break-even point and expected savings before you commit, not after.
Right-size Compute Engine and GKE autoscaling
OptCloud reviews autoscaler configurations against real traffic patterns and flags over-provisioned node pools and instance groups that are scaling for peak load they rarely see.