database-query-optimizer

N+1 queries occur when Django executes one initial query plus additional queries for each related object. Use select_related() for foreign keys and prefetch_related() for many-to-many and reverse relationships to load all data in two queries instead of N+1, significantly reducing database calls and API response time.

Slow endpoints typically result from inefficient queryset evaluation, missing database indexes, or N+1 patterns. Enable query logging to inspect executed SQL, identify bottlenecks, add indexes on frequently filtered fields, and apply ORM optimizations like select_related, prefetch_related, and values() to retrieve only needed columns.

Create database indexes on fields used in WHERE clauses and joins to speed lookups. Use only() and defer() to limit retrieved columns, and values() and values_list() for aggregations. Review Django migrations to ensure indexes are applied, then verify improvements by comparing query execution plans before and after optimization.

Yes. Enable query logging and explain plans to capture SQL execution details in production and Dockerized environments. Log query counts and execution time per endpoint, use Django Debug Toolbar in development, and integrate monitoring into CI pipelines to catch performance regressions in API endpoints and admin views.

Review migrations for missing indexes, inefficient schema changes, and performance pitfalls introduced during schema evolution. Analyze migration files for index definitions, field constraints, and PostgreSQL-specific features to ensure the database schema supports optimized query plans and prevents slow queries after deployment.