# Inefficient Use of Reservations in BigQuery

Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/inefficient-use-of-reservations-in-bigquery

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

# Inefficient Use of Reservations in BigQuery

## Explanation

Teams often adopt flat-rate pricing (slot reservations) to stabilize costs or optimize for heavy, recurring workloads. However, if query volumes drop - due to seasonal cycles, architectural shifts (e.g., workload migration), or inaccurate forecasting - those reserved slots may sit underused. This inefficiency is easy to miss, as the cost remains fixed and detached from usage volume. Unlike autoscaling models, reservations require active monitoring and manual adjustment. In some organizations, multiple projects reserve separate slot pools, exacerbating waste through fragmentation.

## Relevant Billing Model

BigQuery offers two primary billing models: \*  On-Demand:  Billed per TB of data scanned. \*  Flat-Rate Reservations:  Billed based on dedicated slots reserved, regardless of actual usage. Flat-rate pricing is ideal for consistent, high-volume workloads. However, when workload patterns are unpredictable or seasonal, reserved slots may remain idle, generating cost without performance benefit. Slot commitments are billed per second with a minimum duration, and unused capacity is not refunded or reallocated automatically.

## Detection

- Review reservation utilization trends over a representative period

- Compare committed slots vs. actual slots used per project or workload

- Identify whether query concurrency or runtime metrics justify reservation size

- Assess whether workloads could be served equally well with on-demand or flex slots

- Review historical query demand to identify periods of persistent underutilization

## Remediation

- Reduce reservation size if sustained usage is consistently lower than commitment

- Consolidate slot reservations across projects to improve pool utilization

- Switch low-concurrency or unpredictable workloads back to on-demand or flex slots

- Implement governance to review reservation adjustments regularly

- Leverage the Reservation Assignment API to dynamically reassign slot pools based on usage

## Relevant Documentation

[Submit Feedback](https://hub.pointfive.co/inefficiencies/inefficient-use-of-reservations-in-bigquery)

## At a glance

Reference

CER-0069

Cloud provider

GCP

Service

GCP BigQuery

Category

[Databases](https://www.pointfive.co/efficiency-hub/service-category/databases)

Inefficiency type

Underutilized Commitment

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