ARCHQORE / KNOWLEDGE

How to reduce backend requests and data costs

Published and updated: · Publisher: ArchQore

Measure the actual billing unit first; remove duplicate reads, bound results and cache appropriately without trading away authorization.

Know what the provider charges for

Billing models differ. Cloud Firestore documents charges for document reads, writes, deletes, storage and transfer, with some query patterns also incurring index-entry reads. Another backend may charge for requests, execution time or bandwidth. “Reduce API calls” is incomplete advice until you know which operation drives your own bill.

Measure one user journey across dashboard, list, detail and back navigation. Record requests, documents or rows read, transfer and latency. Use the provider’s usage reports instead of a fabricated monthly estimate.

  • Find the most-used journey and every operation it triggers.
  • Separate initial reads from later updates.
  • Account for rules, indexes and transfer where the provider does.

Remove duplication without hiding stale data

Read a bounded list once at the page boundary instead of repeating the same query in each component. Paginate and select only needed fields when supported. Combine related requests when it improves the pattern without bypassing authorization. Cache slowly changing public data with an explicit policy; never put personal responses in a shared cache.

Realtime listeners fit chats and rapidly changing state, but should not be attached to every static card by habit. Dispose of listeners when their screen is no longer active, and compare their cost with an appropriate refresh schedule rather than assuming one is always cheaper.

  • Eliminate N+1 and navigation-triggered duplicate reads.
  • Bound results and define when to refetch.
  • Choose a cache lifetime that matches the data.

Verify the whole outcome

Compare before and after on the same journey with representative data and traffic. Fewer reads do not help if customers see stale or cross-account data. ArchQore puts bounded queries, source of truth and caching rules in the technical foundation so performance decisions can be tested, not merely asserted.

  • Recheck freshness and authorization after caching.
  • Watch latency as well as cost.
  • Revisit current provider pricing before committing.

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