MySQL Performance Doctor

MySQL Performance Doctor: practical plan

MySQL diagnostic sequence

Establish context

Capture MySQL version, query, parameters, table sizes, indexes, row counts, workload timing and when the regression began. Compare old and new query behavior.

Explain the plan

Use EXPLAIN and, where safe and supported, EXPLAIN ANALYZE. Review chosen index, estimated rows, join order, access type, temporary tables and filesort. Compare estimates with actual rows.

Predicate and index review

Check whether the new filter is selective, type-compatible and sargable. Look for functions or implicit casts on indexed columns. Evaluate composite index column order against real predicates and sort needs; account for write and storage cost.

System bottlenecks

Inspect CPU, I/O, buffer-pool hit patterns, lock waits, connection saturation and replication. Check for parameter skew and concurrency differences.

Safe change

Test query rewrite or index in staging with representative data. Measure p50/p95 latency and write impact. Roll out with monitoring and a rollback plan. Avoid copying generic tuning settings without evidence.

Measurement and review

Record the baseline, source, date range, denominator and owner. Use one primary measure plus quality guardrails; compare like-for-like cohorts and disclose missing data. Treat estimates as scenarios, not observed outcomes.

Risks and controls

Check relevance, consent, disclosure, workload and downside before scaling. Keep an evidence trail, obtain human review for material commitments, and pause if trust, quality or compliance signals deteriorate.

Next steps

1. Confirm the goal, audience and available capacity.
2. Gather the minimum evidence for a first test.
3. Assign an owner, budget and review date.
4. Run a small pilot, record outcomes and decide whether to iterate, expand or stop.