Reduce Firebase Cost Before Launch

Before launch, list the screens that repeat often: feeds, search results, dashboards, notifications, and profile pages. For each screen, count the documents read, files downloaded, callable functions triggered, and refreshes caused by realtime listeners.

This usually finds the highest leverage fixes faster than changing providers. A feed that reads posts, authors, counters, and comments separately can be redesigned before real traffic makes the pattern expensive.

For list views, store display-ready fields such as authorName, thumbnailUrl, commentCount, likeCount, lastActivityAt, and status on the document that the list reads. Keep the canonical data elsewhere if needed, but avoid fetching several related documents just to render one row.

Also set page sizes intentionally. Infinite scroll, search autocomplete, and admin tables should have clear limits so one active user cannot trigger thousands of reads during normal browsing.

Storage downloads, Cloud Functions, and long retention periods can become the second wave of cost. Resize images before upload, cache public assets, delete temporary files, and keep logs or exports only as long as the product actually needs them.

After these checks, run the calculator with conservative and optimistic traffic assumptions. If the estimate is still dominated by Firestore reads or relational reporting needs, compare Cloud Run with Cloud SQL before locking the architecture.