S3 Standard is the default storage class and is often used by default even for data that is rarely accessed. Keeping large volumes of infrequently accessed data in S3 Standard leads to unnecessary costs. Data such as backups, logs, archives, or historical snapshots are often strong candidates for migration to colder tiers like S3 Glacier or Deep Archive. If access patterns are unknown or variable, S3 Intelligent-Tiering can reduce costs without requiring manual transitions.

CloudWatch log groups often persist long after their usefulness has expired. In some cases, they are associated with applications or resources that are no longer active. In other cases, the systems may still be running, but the log data is no longer being reviewed, analyzed, or used by any team. Regardless of the reason, retaining logs that no one is monitoring or using results in unnecessary storage costs. If log data is not needed for operational visibility, debugging, compliance, or auditing purposes, it should either be deleted or managed with a shorter retention policy.

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.

While On-Demand mode is well-suited for unpredictable or bursty workloads, it is often cost-inefficient for applications with consistent throughput. In these cases, shifting to Provisioned mode with Auto Scaling allows teams to set a baseline level of capacity and scale incrementally as needed—often yielding substantial cost savings without compromising performance.