A utilities billing RDS MySQL database shows rising p95 query latency after a schema growth year. Performance Insights highlights repeated full-table scans and suboptimal parameters. Which data-tier remediation best addresses the bottleneck?
Select an answer to reveal the explanation.
Short Explanation
When the billing ledger starts wheezing, you do not throw the filing cabinets into deep freeze—you fix the index cards and the engine knobs. Slow-query evidence plus parameter and index tuning is the grown-up move.
Full Explanation
Continuous improvement at the data tier starts with evidence: slow-query logs and Performance Insights identify missing indexes and poorly tuned engine parameters. Targeted index and parameter changes restore OLTP performance for utilities billing. Glacier is archival object storage, not an OLTP primary; deleting backups harms recoverability; stripping indexes from reporting paths typically worsens scans.