# Performance Considerations for High-Volume Multica Workspaces: Scaling Guide

> Discover performance considerations for high-volume Multica workspaces. Learn about scaling strategies like lock-striped fan-out, paginated SQL, and pgx pools for optimal performance.

- Repository: [multica-ai/multica](https://github.com/multica-ai/multica)
- Tags: scaling-guide
- Published: 2026-04-11

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**Multica workspaces scale horizontally through lock-striped WebSocket fan-out, paginated SQL queries with composite indexes, and tuned pgx connection pools, but require careful handling of back-pressure and deep pagination limits.**

When a Multica workspace grows to thousands of members and tens of thousands of issues, several architectural components in the `multica-ai/multica` codebase become critical to keep latency low and resource usage predictable. Real-time updates, database query patterns, and connection management must be carefully tuned to avoid bottlenecks. Below is a deep dive into the specific performance