## Context
This PR adds the core structure for RLS implementation:
- RLS data model
- RLS service layer
- RLS WorkspaceMigration and Syncable Entity + cache + Validations
- RLS resolver layer
- ORM layer with RLS Predicate to ORM WHERE clause conversion with
workspaceMember record transposition
Tests are missing though
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Establishes core row-level permissions infrastructure and enforcement
across the stack.
>
> - Backend: new `rowLevelPermissionPredicate` and
`rowLevelPermissionPredicateGroup` entities, TypeORM migration, feature
flag `IS_ROW_LEVEL_PERMISSION_PREDICATES_ENABLED`, flat-entity
maps/cache wiring, services and GraphQL resolvers for CRUD, and
inclusion of `workspaceMember` in auth context
> - ORM: applies row-level permission predicates to SELECT, DELETE, and
SOFT DELETE query builders; propagates context through
GlobalWorkspaceOrmManager/EntityManager
> - GraphQL: generated schema/types/queries/mutations for
creating/updating/deleting/fetching predicates and groups
> - Frontend: settings page adds a gated "Record-level" section
(placeholder) and metadata error handler labels for new entities
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
fe955cc4588a92157afa6795fb574189a4be1e93. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Félix Malfait <felix.malfait@gmail.com>
Removing the feature flag to enable read on replica for all workspaces.
It will still be possible to toggle off the feature by removing the env
variable `PG_DATABASE_REPLICA_URL`.
## Context
Following https://github.com/twentyhq/twenty/pull/16399
Now using the new global orm manager everywhere and returning a
GlobalDatasource/WorkspaceDatasource based on a feature flag.
This means we now need to wrap all our ORM calls within
executeInWorkspaceContext callback (at least for now) so the global
datasource can dynamically hydrate its context via the new store (the
global datasource does not store anything related to workspaces as it is
now a unique singleton). If feature flag is off it still uses local data
stored in the workspace datasource.
## Problem
buildEntityMetadatas in GlobalWorkspaceOrmManager is computationally
expensive and was running on every executeInWorkspaceContext call. This
method uses
TypeORM's EntitySchemaTransformer and EntityMetadataBuilder to build
metadata for all workspace entities (30-50+ objects with many fields
each).
The resulting EntityMetadata[] is not serialisable which means it cannot
be cached in Redis because they contain:
- Circular references
- Functions/methods
- References to the DataSource instance
## Solution
Extended the workspace cache system to support local-only caching, then
created a cache provider for entityMetadatas.
## Implementation details
Updated @WorkspaceCache decorator (workspace-cache.decorator.ts)
- Added localOnly?: boolean option to skip Redis storage for
non-serializable data
Created WorkspaceEntityMetadatasCacheService
- Computes entity metadatas from DB to avoid race condition, this is
acceptable
Simplified GlobalWorkspaceOrmManager
- Now fetches entityMetadatas from cache instead of rebuilding on every
call
Updated Workspace migration runner - the only entry point where metadata
can change
- Now invalidate the new 'entityMetadata' local cache when
shouldIncrementMetadataGraphqlSchemaVersion is true (== field/object
mutations)
## Context
We've recently introduced a new workspace cache service which now acts
as a cache access and local storage for all workspace related data,
deprecating the individual specific services.
- Better performance through multiple caching/fetching strategies
- Consistent data access patterns across the codebase
- Reduced redis queries through MGET/MSET/PIPELINE with multiple cache
keys
## Context
EntityMetadata was being rebuilt from scratch on every
findMetadata()/getMetadata() call (~20 times per request). This involved
running EntitySchemaTransformer.transform() and
EntityMetadataBuilder.build() repeatedly, causing unnecessary CPU
overhead.
## Implementation
Cache entityMetadatas in ORMWorkspaceContext: Build EntityMetadata once
during workspace context initialization instead of on every metadata
lookup
Remove redundant entitySchemas caching: Since flatMetadata is already
cached, the additional Redis cache for entitySchemaOptions was
unnecessary overhead
Remove WorkspaceEntitiesStorage: Replaced with direct lookup from
FlatObjectMetadataMap
Simplify getObjectMetadataFromEntityTarget: Now only accepts string
targets, using flat metadata maps directly
Also:
Removed unused injections in some services
## Context
Deprecating the old objectMetadataMap type in favour of split flat
entities to match with our new caching.
In the long run, trying to achieve:
- Better performance through caching
- Consistent data access patterns across the codebase
- Reduced database queries
Now that everything is based on flat entities, which are cached, we can
finish the refactoring of workspace context cache which should already
improve performances.
Then the last step will be to consume that new cache in the new global
datasource to get rid of the many workspace datasources stored in the
server
## Context
Deprecating legacy ObjectMetadata from cache in favor of flat entities.
Introducing utils to build byName/byNameSingular/byNamePlural in
isolated cases
## Next
- I had to introduce a util to build from flat to legacy
objectMetadataMaps, we should instead use flat maps directly when needed
(datasource, schema generation, etc)
- Deprecate metadata version in the cache
- Use the new cache strategy for flat entities with permissions and
feature flags and inject in the global datasource context
## Context
Implementing a single service managing all the cache scoped to a
workspace, this will be dynamically injected as a WorkspaceContext in
the app during a request lifetime (ingested by the future global
datasource for example).
Usage:
```typescript
this.globalWorkspaceOrmManager.executeInWorkspaceContext(
authContext,
async () => {
// Everything here will have access to a workspaceContext, containing all the cache data + a ready to use datasource with workspace scoped metadata, permissions, feature flags, etc...
// Internally will call loadWorkspaceContext
}
```
Note: executeInWorkspaceContext will probably be owned by a higher level
service later and not only the ORM.
```typescript
private async loadWorkspaceContext(
authContext: WorkspaceAuthContext,
): Promise<WorkspaceContext> {
const workspaceId = authContext.workspace.id;
const cache =
await this.workspaceContextCacheService.get<WorkspaceContextData>(
workspaceId,
[
'objectMetadataMaps',
'metadataVersion',
'featureFlagsMap',
'permissionsPerRoleId',
],
);
return {
authContext,
objectMetadataMaps: cache.objectMetadataMaps,
metadataVersion: cache.metadataVersion,
featureFlagsMap: cache.featureFlagsMap,
permissionsPerRoleId: cache.permissionsPerRoleId,
};
}
```
The cache retrieval strategy is as followed:
```
- Check if there is an ongoing promise fetching data from the cache =>
return the promise.
- Check in the local cache entry if lastCheckedAt has expired. If not,
return as it is without querying redis.
- Check in redis the cache entry hash and compare with local cache entry
hash, if they are the same return the local cache entry data
- Check in redis the cache entry data, if it's there return it and store
it into the local cache entry data and update local cache entry hash. If
it's not there recompute the data by querying the DB and update both
redis and local cache
```
Fixes https://github.com/twentyhq/twenty/issues/15809
## Context
We recently introduced a global datasource now consuming workspace
context from ALS store however the authContext was missing (only the
workspaceId was there) which "broke" event emission, now missing the
workspaceMemberId
This PR adds the missing authContext so we can access from anywhere in
the datasource. We are still passing it as a parameters on repository
level for legacy but in theory we should be able to remove it from
everywhere and consume the context
<img width="929" height="253" alt="Screenshot 2025-11-13 at 18 58 16"
src="https://github.com/user-attachments/assets/3e04f264-95e6-4831-94f3-fc01603f19bd"
/>
## Context
inferDeletionFromEntities only accepts a set of keys for each entities
that needs deletion. This could be error-prone if tmr we want to add a
new side effect and forget to add the entity when in practice you want
to delete all entities that are in the fromToAllFlatEntityMaps (this is
the case for applications for example)
## Context
This PR introduces a Global Workspace DataSource that consolidates
workspace-specific database access through a single TypeORM DataSource
instance with AsyncLocalStorage-based context management instead of N
workspace datasources.
- Created GlobalWorkspaceDataSource extending TypeORM's DataSource to
manage multiple workspaces with entity metadata caching (1-hour TTL)
- Implemented AsyncLocalStorage for workspace context propagation
(WorkspaceContextForStorage) containing workspace ID, metadata,
permissions, and feature flags
- Modified query execution flow to wrap operations in workspace context
via GlobalWorkspaceOrmManager.executeInWorkspaceContext()
- Added schema name to entity schemas for proper multi-tenant database
separation
Next:
- use the new global workspace datasource everywhere and deprecate
workspace datasource factory
- improve metadata caching using a short TTL to avoid multiple calls to
redis
- Leverage the new WorkspaceContextALS and put it higher in the request
hierarchy to have access to permission, metadata and featureflag
everywhere --- build it manually for commands --- find a way to
propagate it in jobs?
- Remove PG_POOL patch once we have a unique datasource and increase
global datasource pool size
## Implementation
Why ALS:
1. Automatic Per-Request Isolation
With schema-based multi-tenancy, each workspace has its own PostgreSQL
schema
(e.g. workspace_20202020-1c25-4d02-bf25-6aeccf7ea419).
The critical challenge is ensuring that concurrent requests from
different tenants don't interfere with each other.
```typescript
// Request A (Workspace 1) and Request B (Workspace 2) executing concurrently
// Without ALS: Race condition — they'd share the same global state!
// With ALS: Each request has isolated context ✓
```
ALS automatically isolates context per async execution chain, so:
- Request from Tenant A → ALS stores workspaceId: "tenant-a" → Queries
hit workspace_tenant_a schema
- Request from Tenant B → ALS stores workspaceId: "tenant-b" → Queries
hit workspace_tenant_b schema
✅ No interference, even when executing simultaneously on the same
Node.js event loop.
2. No Manual Context Passing
Before ALS, you'd need to pass workspaceId through every function call:
```typescript
// ❌ Without ALS - Context threading nightmare
getRepository(workspaceId, entity)
→ createEntityManager(workspaceId)
→ getMetadata(workspaceId, target)
→ findInCache(workspaceId, cacheKey)
```
With ALS:
```typescript
// ✅ With ALS - Clean, implicit context
getRepository(entity) // Reads workspaceId from ALS
→ createEntityManager() // Reads workspaceId from ALS
→ getMetadata(target) // Reads workspaceId from ALS
→ findInCache(cacheKey) // Reads workspaceId from ALS
```
example
```typescript
override findMetadata(target: EntityTarget<ObjectLiteral>): EntityMetadata | undefined {
const context = getWorkspaceContext(); // 👈 Automatically gets the right workspace!
const { workspaceId, metadataVersion } = context;
const cacheKey = `${workspaceId}-${metadataVersion}`;
// ... returns metadata for THIS workspace's schema
}
```
3. Async Chain Propagation
Node.js operations are heavily async. ALS automatically propagates
context through:
- async/await chains
- Promise chains
- Callbacks
```typescript
executeInWorkspaceContext(workspaceId, async () => {
await prepareContext(); // Has context ✓
const results = await run(); // Has context ✓
await enrichResults(); // Has context ✓
// Even nested async operations maintain context!
await Promise.all([
saveToCache(), // Has context ✓
emitEvent(), // Has context ✓
logMetrics(), // Has context ✓
]);
});
```
5. Schema-Specific Metadata Caching
The implementation caches entity metadata per workspace + version:
```typescript
// Cache key format: "workspaceId-metadataVersion"
const cacheKey = `${workspaceId}-${metadataVersion}`;
```
Why this matters with schemas:
- Each workspace has different table structures (custom fields, objects)
- EntitySchema includes schema: "workspace_xxx" property
- Each cached metadata points to the correct schema
ALS ensures getWorkspaceContext() returns the right workspaceId,
so you always get the correct schema's metadata from cache.
6. Single DataSource for All Tenants
The key change here:
```typescript
// ❌ Old approach: One DataSource per tenant
const dataSourceTenantA = new DataSource({ schema: 'workspace_a' });
const dataSourceTenantB = new DataSource({ schema: 'workspace_b' });
// Problem: Hundreds of DB connection pools!
```
```typescript
// ✅ New approach: One shared DataSource + ALS context
const globalDataSource = new GlobalWorkspaceDataSource();
// ALS determines which schema to use at runtime
```
When you call:
```typescript
globalDataSource.getRepository('person');
```
It internally does:
```typescript
const context = getWorkspaceContext(); // Gets current tenant from ALS
const metadata = this.findMetadata('person'); // Finds metadata for THIS tenant's schema
// EntityMetadata includes: schema: "workspace_20202020-1c25..."
// TypeORM automatically queries: SELECT * FROM "workspace_20202020-1c25...".person
```
7. Request Lifecycle Example
```typescript
// 1. GraphQL request arrives: "query people { ... }"
// 2. Middleware extracts authContext.workspace.id = "tenant-a"
// 3. Query runner wraps execution in ALS:
executeInWorkspaceContext("tenant-a", async () => {
// 4. Everything inside has access to workspace context:
const repo = getRepository('person'); // ALS → tenant-a
const metadata = getMetadata('person'); // ALS → tenant-a → cache["tenant-a-v5"]
// 5. TypeORM builds query with correct schema:
// SELECT * FROM "workspace_tenant_a"."person" WHERE ...
// 6. Even nested calls work:
await saveAuditLog(); // ALS → tenant-a → correct audit schema
await emitWebhook(); // ALS → tenant-a → correct tenant webhook
});
// 7. Request completes, ALS context automatically cleaned up
```
8. Safety & Error Prevention
```typescript
// If you forget to set context:
const context = getWorkspaceContext();
// ❌ Throws: "Workspace context not set..."
// Fails fast rather than querying wrong schema!
// Can't accidentally query wrong tenant:
// Context is immutable within execution scope
```
Weiko