Check RDS instance utilization and storage choices
Review Amazon RDS billing usage types separately so compute, storage, IOPS, backup, and deployment-related charges are not mistaken for database load.
Find answers to common questions about cloud and AI costs.
Review Amazon RDS billing usage types separately so compute, storage, IOPS, backup, and deployment-related charges are not mistaken for database load.
Review Cloud Storage versioning, soft delete, retention policies, and project-level billing views with a read-only console procedure.
Use Normalized RU Consumption, 429s, and partition-key RU logs to spot concentrated load before changing provisioned throughput.
Compare Azure Data Factory meter consumption with pipeline and activity runs to focus a design review on recurring orchestration, copy, or data-flow usage.
Trace Azure Backup protected-instance and storage charges to vault redundancy, retention policies, snapshots, and retained recovery points.
Measure Athena bytes scanned, require partition filters, set workgroup controls, and reuse eligible results without hiding limitations.
Choose a DynamoDB capacity mode by comparing traffic stability, consumed units, provisioned capacity, throttling, indexes, and request assumptions.
Use read-only Dataflow and Managed Service for Apache Spark monitoring to investigate errors, lag, resource pressure, backlog, and autoscaling limits.
Review BigQuery partition and clustering filters, estimate bytes with a dry run, and prepare a maximum-bytes-billed limit for on-demand queries.
Review a BigQuery dataset's location, encryption, project, billing, and API prerequisites before configuring Cloud Billing export.
Use supported Azure SQL metrics to identify provisioned databases that deserve a sizing review without assuming low CPU means excess capacity.
Review lifecycle transitions, Autoclass limits, storage-class durations, and retention controls before changing Cloud Storage rules.
Use a read-only AWS CLI inventory to review EBS volumes in available status, then check ownership and retention before any deletion decision.