Multi-Region Storage Exceeds Target Threshold

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Source for automated Recommendations: Spend data in the CloudZero platform. Frequency: Checked once per day. If the Recommendation is marked as Ignored, it will still be updated, but notifications will no longer be sent for any updates.

This Recommendation focuses on optimizing GCP Cloud Storage with Multi-Region bucket location by spend. By default, buckets are set to the Multi-Region which is the most expensive and the most redundant configuration option. The threshold for Multi-Region bucket location spend is 30%. Additional spend over that can indicate that storage is not optimized.

Threshold: This Recommendation is created if the total real cost spend on Multi-Region storage class exceeds 30% of the total real cost for all GCP Cloud Storage and is at least $500. When the total spend for Multi Region storage falls below 30%, the Recommendation will automatically be closed.

GCP has two other bucket location types that should be considered based on data access patterns and redundancy needs:

Region: Optimized latency, bandwidth, and cross-zone redundancy. Example workloads: Analytics, Backup and Archive.

Dual-Region: Optimized latency, bandwidth, and cross-region redundancy. Example workloads: Analytics, Backup and Archive, Disaster Recovery.

Note that Region has the lowest data storage cost. Dual-Region has the highest base storage price but does not have outbound data transfer charges when reading data within either region, unlike Multi-Region.

Pricing costs for each bucket location in each region can be found in the GCP documentation.

Note that Bucket location cannot be changed after creation. To change the location, you can move your data to a bucket in a different location. Check the GCP documentation for any costs that may be incurred from moving data between locations.

The 90-day cost graph shows the daily total spend for all GCP Cloud Storage resources with Multi-Region storage locations and highlights the top five resources with the highest spend to consider optimizing.