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Graph/cross-process-scoped-cache-invalidation

Pattern

Cross-Process Cache Invalidation

cross-process-scoped-cache-invalidation

Cache directives and tag-based updates get ignored or misapplied when caching is scoped per process or per RTK Query instance, so cached session data doesn’t propagate and pagination merges replace instead of extending results.

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Public graph metadata

Updated6/26/2026

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30 linked nodes

would prefer to not call `convertDataToTasks` inline in JSX when rendering — React-Query to cache the data you want to render from. Tension: especially caching.

the query does not invalidate after a successful transaction. Tension: unless I manually invalidate it using the React Query DevTools or leave Chrome and come back. Outcome: which then triggers the invalidation (update).

TanStack Query cache is not being leveraged for Firestore data fetched manually

tRPC invalidate() on an inactive query does not refetch matching cached entries from another route

I am trying to cache the response of a query inside a server action file — export async function getCachedSession(userCacheToken: string, token: string) {. Tension: "use cache";. Outcome: I keep running into an.

the cache doesn't work across processes — workers might be pre-forked. Tension: is using lru caching doing what I am expecting, that is - will it only initialize sentry once even though i attempt to do it multiple times? Outcome: provided it's called within the same process.

I've noticed I've several caches that maybe don't need to be created. — I'm using the cache action in GitHub Actions workflows. Tension: even if it restores always the same cache, no matter if the dependencies are changed, it should still work fine. Outcome: it mostly depends on how different and big these caches are.

`chronicle recall` (and the warm-context renderer used at session start / by retrieveMemoryContext) hard-excludes them via a WHERE clause — Chronicle 2.0 memory recall. Tension: fresh writes appear in `chronicle search --tier short-term` but never in `chronicle recall`. Outcome: newly-saved facts are invisible for at least 24 hours unless explicitly saved with `--tier long-term`.

An async action attempted to dispatch multiple updates to a Redux Toolkit slice using RTK Query state (e.g., loading/error/data), but the dispatch/flow did not properly work. The goal was to store RTK Query results into the studentSlice state.

a read-looking endpoint (`GET /v2/packages`) enqueued a background job on a cache miss with no flag check. Tension: Any other caller of the same service bypassed the gate entirely. Outcome: An authenticated client could therefore drive arbitrary writes into production through the side door.

unstable_cache doesn't really cache anything

How to take RTK Query endpoint results, persist them as historical data for graphing, and also keep the normal RTK Query caching behavior. The user wants to “intercept” fulfilled query results inside the RTK Query flow rather than using component hooks.

In RTK Query, after performing a mutation (e.g., login), the developer cannot easily select/read the data that the mutation stored in the cache from another component/hook instance.

When following the RTK Query example for mutations without React hooks, it’s unclear what query key/argument should be passed to `api.util.updateQueryData` to optimistically update the cache for the last `getUsers` query. The snippet appears inconsistent about using `id` vs `count`.

The query result is being processed with `selectFromResult` using a memoized `createSelector` to prevent re-renders during RTKQ polling every 5 seconds. The question is whether this selector approach is correct and properly prevents unnecessary component updates.

The second click on the RTK Query lazy mutation/query trigger does not update the `isLoading` state; `isLoading` stays false on subsequent calls.

When multiple counter buttons in the same cart component trigger RTK Query mutations, the loading state becomes shared, causing spinners to appear on all counters when only one item is being updated.

RTK Query tag definitions for the 'Timeseries' endpoint cannot be set with an id; the developer cannot make tag-id behave as expected.

In an RTK Query endpoint, the request should include query parameters only when their values are not null, but optional params are being added unconditionally or require repetitive manual checks.

When navigating from a users list (getUsers query) to a single user page (getSingleUser query), Redux Toolkit refetches the user data instead of reusing the data from the previous cached tags. This results in multiple cache entries/tags for the same user ID.

A PostgreSQL query uses a CTE to select the old session_id and then performs an INSERT ... ON CONFLICT DO UPDATE, returning the CTE’s result as the previous value. The user needs to know whether PostgreSQL guarantees the CTE is evaluated before the INSERT/UPDATE so the returned value is correct.

Software actually aliasing NS and S accesses for RAMs means you can end up with two non-coherent copies of the same data in the caches — secure and non-secure data to be distinguished in caches. Tension: which can desync because of the lack of coherency. Outcome: This is why secure world page tables can be set up with NS=1 pages.

When ag-Grid data is updated every few seconds via async transactions, any in-progress filter changes selected in the filter popup (before clicking Apply) are applied to the grid. Additionally, the filter behavior is inconsistent when trying to have the filter update only after the user clicks Apply.

Using `unstable_cache` in a Next.js server component doesn’t cache results during local development; the fetch function runs and logs on every request, adding ~1s latency despite `revalidate` being set to 10 seconds.

When I run tests in parallel, I get random failures — one test interferes with the cache of another test. Tension: one test interferes with the cache of another test.

retrieval scoring omitted recency decay, normalized momentum, live-state retrieval bias, and multiplicative tier boost — A Phase 3 memory subsystem review found deviations from the authoritative memory spec. Tension: short-term memories were still eligible for episodic retrieval; the memory daemon did not reconnect after LISTEN connection errors; ILIKE patterns used unescaped user text; extractor errors could disappear from fire-and-forget timeouts; and memory migrations lacked partitioning/seed data details. Outcome: Read the corrective spec and compared it against the current TypeScript memory implementation, migrations, and tests.

runtime updates looked up rows by id only — After converting a memory events table to range partitioning by occurred_at. Tension: review found two production risks.

An in-process timer-flush queue loses all pending items on process crash or restart while reporting flushed successfully

Duplicate detection in an agent-driven Q&A system adds significant synchronous write-path latency when it embeds and cosine-compares before inserting. Additionally, downstream knowledge-graph entity extraction can create duplicate nodes due to concurrent merges without proper uniqueness enforcement.

Implementing a validation suite for an anonymization-pipeline backfill across "Cohort-D" tables — system-rendered / agent-internal: messages, message_audits, message_requests, scoped_messages, notifications, bug_reports, contact_submissions, chronicle_entries/crystals/lessons. Tension: Spec required 9 distinct cross-cohort invariants in a single validate.ts script, each with positive AND negative test coverage, runbook STOP criteria matching an existing A1 runbook shape, and stripping legacy KMS column-name references.

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