A safe query in PostgreSQL can become unexpectedly expensive due to data growth, shifting statistics, or changes in index availability. To manage this, developers should treat query plan behavior as a versioned production contract. This involves normalizing query shapes, capturing detailed plan information including schema and index versions, and defining workflow-specific budgets. Runtime controls like database-enforced timeouts and pool limits should remain authoritative, with operations that exceed budgets being narrowed, deferred, or flagged for review rather than silently increasing limits. AI
IMPACT Ensures predictable performance and cost for AI applications relying on PostgreSQL databases.
RANK_REASON The item discusses best practices for managing database query performance and cost, which falls under tooling and infrastructure management.
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