convex-performance-audit

To diagnose Convex performance issues, gather signals from CLI insights and dashboards to identify the strongest problem class, such as hot-path reads or subscription costs. The workflow then maps these signals to reference patterns for targeted fixes.

Frequent mutation retries in Convex are typically caused by OCC (optimistic concurrency control) conflicts during write contention. An audit identifies these signals and prescribes minimal, scoped fixes across related functions to reduce conflicts.

Reduce high Convex subscription costs by auditing reactivity across UI, functions, and queries. The audit identifies the strongest performance signal and guides targeted improvements to prevent regressive hotspots and lower overall subscription expenses.

The best way to fix Convex hot-path issues is to map CLI and dashboard signals to reference patterns, then apply the smallest high-impact fix first. This targeted workflow ensures safe changes while addressing function budgets and read limits.

A Convex feature may remain slow if refactoring misses the strongest performance signal or creates regressive hotspots. A structured audit validates scoped fixes across related functions and reviews to ensure the changes actually resolve the bottleneck.

Yes, you can audit Convex performance using code audits if CLI insights are unavailable. The workflow accommodates multiple signal sources to identify problem classes like subscription cost or OCC conflicts and guide targeted improvements.