I'm trying to analyze and optimize the cost of Cloud SQL backups in Google Cloud. In the GCP billing export, I see multiple line items with the SKU:
"Cloud SQL: Backups in [region]" (e.g., Northern Virginia)
Each line has different costs and usage amounts throughout the day, but no resource.id is attached, so I can't tell which Cloud SQL instance the charges belong to. What I'm trying to understand:
I’ve already tried:
Checking for labels in the billing export (none are present)
Looking at Cloud SQL monitoring metrics (backup_storage_used)
Searching Cloud Audit Logs for backup events
But none of these give me a clear cost breakdown per SQL instance.
Any tips, tools, or workflows to bridge the gap between backup costs and specific Cloud SQL instances?
How to attribute backup costs to specific Cloud SQL instances?
When you're tracking costs in Google Cloud, SKU Cloud SQL: Backups in [region] are billed based on usage, but the lack of a resource.id in the billing export makes it tough to tie these costs directly to specific Cloud SQL instances. However, work around would be by Instance naming convention and Using billing API filters.
Instance Naming Convention: While this doesn't appear in the billing export, you can match your billing entries with the Cloud SQL instance names manually. For example, if you have instances like prod-db, dev-db, etc., it can help you identify the backups by relating them to specific environments.
Use Billing API and create custom Filters: Even though resource.id isn’t available, you might be able to filter by SKU (e.g., "Cloud SQL: Backups"), regions, and time ranges to make educated guesses. This might still not give you the exact resource ID, but limiting by the filters can help you break down the cost.
Is there a way to correlate billing lines with instance names or labels?
Unfortunately, the billing export you have doesn’t contain labels or instance IDs, which would normally help tie the cost to specific instances. However, there’s a workaround:
Enable Label-based Billing on Cloud SQL: You can add labels to your Cloud SQL instances. Labels are key-value pairs that allow you to tag resources. Once you add labels (like instance-name or environment: production), you can filter the billing export by those labels and identify which instance is generating the backup costs.
Resource IDs for backups: While resource.id might not appear in your current export, you can try to enable more granular billing tracking for backups by using Cloud Monitoring (formerly Stackdriver) and creating custom reports based on your labels or instance names. This way, you could match metrics to billing costs.
How can I identify if a particular backup is unnecessary or consuming excessive storage?
To track excessive storage or unnecessary backups, it’s all about monitoring and data management.
Cloud SQL Monitoring Metrics: Check the backup_storage_used metric (you mentioned you've already checked it). This can help you identify the trends in storage usage and determine if a particular instance is using significantly more storage than expected.
Here’s what you need to look for and compare the expected size of your backups (based on the size of your databases) with the storage usage reported in the metric. If it’s unusually high, it might indicate that backups are growing unexpectedly due to things like; Unnecessary large data retention, Backup frequency, and Non-incremental backups.
Any tips, tools, or workflows to bridge the gap between backup costs and specific Cloud SQL instances?
Google Cloud Billing Reports: You can explore Google Cloud Cost Management tools, such as Cost Explorer or Reports, to break down costs based on project or label. Though not as granular as having a direct resource ID in the billing export, Cost Explorer helps you track costs over time.
Cloud Monitoring: This tool could set up usage-based alerts for your Cloud SQL instance's backup storage. By correlating Cloud SQL storage metrics (like backup_storage_used and total_backup_storage) with backup events, you can monitor abnormal growth or unnecessary backups.
BigQuery Billing Export: Set up BigQuery exports for your billing data. With BigQuery, you can analyze the billing data more flexibly. You could potentially join billing data with other instance-level data (like Cloud SQL instance IDs or tags) to get a clearer picture of which instance is incurring the backup costs.
Here are some helpful links that may help resolve your issue:
Find example queries for Cloud Billing data