TanStack Query Integration: Invalidate First, Patch Selectively Volume 07 - Advanced Application Architecture
Default strategy Realtime event + TanStack Query
Broadcast event Handler invalidateQueries API INSERT/UPDATE/DELETE small + idempotent taskKeys.all refetch
Why invalidate first? The backend already owns authorization, filters, pagination and derived state.
Patch the cache directly only when the event contract is stable and the update is easy to prove correct.
Why invalidate is the safe default • NestJS already owns authorization and business rules.
• Phase 15 already owns search, filters, sorting, pagination and metadata.
• Phase 25 already owns optimistic local UX for the current user.
• A Realtime event can simply mark cached Task data stale and let the API rebuild the correct view.
Targeted invalidation options // Simple and safe: queryClient.invalidateQueries({ queryKey: taskKeys.all, })
// Narrower when the event contract gives a reliable Task id: queryClient.invalidateQueries({ queryKey: taskKeys.detail(taskId), }) queryClient.invalidateQueries({ queryKey: taskKeys.lists(), })
When direct cache patching is justified Patch with setQueryData only when the event schema is stable, the update is easy to prove correct, and you are not rebuilding authorization/filter/pagination logic in the browser. Otherwise invalidate.
Burst events A later optimization may debounce/coalesce invalidations for high-frequency streams. Start correct first, then measure network churn before adding complexity.
TanStack Query is a server-state synchronization system, not merely a fetch helper. Cache identity, freshness, invalidation, and mutation semantics are the core model.
Restate the goal of “TanStack Query Integration” as one observable behavior. Write the success signal before touching code.
Trace the boundary map: component → query key → cache state → fetch/mutation → reconciliation. Mark the one boundary this lesson changes.
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
Connect the slice to TaskFlow’s phase artifact: Realtime task updates that merge into TanStack Query state with scoped subscriptions and reconnect behavior.. Verify behavior from the outside as a user or API client would.
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
export const taskKeys = {
all: ["tasks"] as const,
list: (filters: TaskFilters) => ["tasks", "list", filters] as const,
detail: (id: string) => ["tasks", "detail", id] as const,
};Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.
Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.
Without copying the final source, create a second small scenario that applies “TanStack Query Integration” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Choose the exact collaborative event that benefits from realtime rather than subscribing to everything.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Events for other tenants visible to a client
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.