Aurora Serverless is designed for workloads with unpredictable or intermittent usage patterns that benefit from automatic scaling. However, when used for databases with constant load, the service’s elasticity offers little advantage and adds cost overhead. Serverless instances run continuously in steady workloads, resulting in persistent ACU billing at a higher effective rate than a provisioned cluster of similar size. In addition, Serverless configurations cannot use Reserved Instances or Savings Plans, missing out on predictable cost reductions available to provisioned Aurora.
Aurora Serverless is designed for workloads with unpredictable or intermittent usage patterns that benefit from automatic scaling. However, when used for databases with constant load, the service’s elasticity offers little advantage and adds cost overhead. Serverless instances run continuously in steady workloads, resulting in persistent ACU billing at a higher effective rate than a provisioned cluster of similar size. In addition, Serverless configurations cannot use Reserved Instances or Savings Plans, missing out on predictable cost reductions available to provisioned Aurora.
Customers often delay upgrading Aurora clusters due to compatibility concerns or operational overhead. However, when older versions such as MySQL 5.7 or PostgreSQL 11 move into Extended Support, AWS applies automatic surcharges to ensure continued patching. These charges affect all clusters regardless of usage, creating unnecessary cost exposure across both production and non-production environments. For large Aurora fleets, the incremental expense can become significant if upgrades are not proactively managed.
Many Aurora clusters default to using the Standard configuration, which charges separately for I/O operations. For workloads with frequent read and write activity, this can lead to unnecessarily high costs. Aurora I/O-Optimized eliminates I/O charges entirely and simplifies cost predictability. In environments with consistently high I/O usage, switching to I/O-Optimized often results in lower total spend.
