Cloud Sql Postgres Oom Work Mem Tuning

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A data engineering team maintains a Cloud SQL for PostgreSQL instance that serves data models for executive reporting dashboards. During morning peak hours, numerous concurrent dashboard sessions execute complex queries involving large ORDER BY, GROUP BY, and multi-table join operations.

Database logs reveal recurring Out of Memory: Killed process (postgres) errors and connection terminations (terminating connection due to administrator command). Monitoring shows high active session counts and severe RAM saturation.

Which resource configuration adjustment should the data engineer implement to balance query performance and prevent out-of-memory errors?

Set a conservative global work_mem value at the instance level and allocate higher work_mem settings at the session level for heavy reporting workloads, while adjusting shared_buffers if additional workspace is required.

Scale down the instance compute size to clear cached buffer memory, then scale back up immediately during dashboard peak hours.

Increase the global work_mem flag to maximum capacity across the entire instance to ensure all sort operations use in-memory quick sort instead of disk merge sort.

Increase shared_buffers to allocate all available instance RAM and disable the default huge_pages configuration.

Professional Cloud Data Engineer

Cloud Sql Postgres Oom Work Mem Tuning

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