User-visible latency
Connect slow checkout, booking, search, dashboard, and reporting paths to the database calls behind them.
Performance audit intent
A database performance audit turns slow systems into measurable findings.
Use a database performance audit when latency, timeouts, CPU pressure, lock waits, or report delays are visible to the business but the database cause is still unclear.
Workload pressure
Review load patterns, concurrency, waits, memory pressure, temporary work, storage growth, and connection behavior.
Query and index evidence
Separate expensive SQL, missing index opportunities, stale access patterns, and table growth from infrastructure guesswork.
Audit before tuning
A database performance audit should not start with a random index or configuration change. It should explain which workload is slow, which database evidence supports the finding, what risk exists, and which optimization step deserves review first.
Map symptoms
List the slow workflows, affected users, time windows, and service-level impact.
Collect database facts
Use query timing, plans, index usage, wait signals, table size, and capacity metrics.
Rank findings
Prioritize bottlenecks by user impact, change risk, confidence, and operational cost.
Review next steps
Turn findings into human-reviewed query, index, maintenance, schema, or capacity work.
Move from performance audit to the right optimization path
Use the database optimization guide when the audit points to broad query, index, table, and capacity tradeoffs. Use the query optimization path when a small set of SQL statements explains most of the impact.
What does a database performance audit check first?
Start with measurable symptoms: slow transactions, timeout patterns, high database load, query timing, index usage, and capacity pressure.
How is it different from database optimization?
The audit creates evidence and priorities before changes are made. Optimization uses those findings to plan reviewable improvements.
Where does PostgreSQL fit?
When the database is PostgreSQL, continue from the broad audit into the PostgreSQL optimization path for engine-specific review.