Followup to #7566 | Story: https://linear.app/n8n/issue/PAY-926
### Manual workflow activation and deactivation
In a multi-main scenario, if the user manually activates or deactivates
a workflow, the process (whether leader or follower) that handles the
PATCH request and updates its internal state should send a message into
the command channel, so that all other main processes update their
internal state accordingly:
- Add to `ActiveWorkflows` if activating
- Remove from `ActiveWorkflows` if deactivating
- Remove and re-add to `ActiveWorkflows` if the update did not change
activation status.
After updating their internal state, if activating or deactivating, the
recipient main processes should push a message to all connected
frontends so that these can update their stores and so reflect the value
in the UI.
### Workflow activation errors
On failure to activate a workflow, the main instance should record the
error in Redis - main instances should always pull activation errors
from Redis in a multi-main scenario.
### Leadership change
On leadership change...
- The old leader should stop pruning and the new leader should start
pruning.
- The old leader should remove trigger- and poller-based workflows and
the new leader should add them.
Story: https://linear.app/n8n/issue/PAY-926
This PR coordinates workflow activation on instance startup and on
leadership change in multiple main scenario in the internal API. Part 3
on manual workflow activation and deactivation will be a separate PR.
### Part 1: Instance startup
In multi-main scenario, on starting an instance...
- [x] If the instance is the leader, it should add webhooks, triggers
and pollers.
- [x] If the instance is the follower, it should not add webhooks,
triggers or pollers.
- [x] Unit tests.
### Part 2: Leadership change
In multi-main scenario, if the main instance leader dies…
- [x] The new main instance leader must activate all trigger- and
poller-based workflows, excluding webhook-based workflows.
- [x] The old main instance leader must deactivate all trigger- and
poller-based workflows, excluding webhook-based workflows.
- [x] Unit tests.
To test, start two instances and check behavior on startup and
leadership change:
```
EXECUTIONS_MODE=queue N8N_LEADER_SELECTION_ENABLED=true N8N_LICENSE_TENANT_ID=... N8N_LICENSE_ACTIVATION_KEY=... N8N_LOG_LEVEL=debug npm run start
EXECUTIONS_MODE=queue N8N_LEADER_SELECTION_ENABLED=true N8N_LICENSE_TENANT_ID=... N8N_LICENSE_ACTIVATION_KEY=... N8N_LOG_LEVEL=debug N8N_PORT=5679 npm run start
```
This PR ensures `MultiMainInstancePublisher` is initialized before
checking if the instance is leader or follower. Followers skip license
init, license check, and pruning start and stop.
Due to a change, during the credentials import command, the core's
Credential object is being called through its prototype. This caused the
Credential's cipher variable to not be set, thus no cipher service being
available during import. This fix catches this edge case and provides a
fix.
https://linear.app/n8n/issue/PAY-933/set-up-leader-selection-for-multiple-main-instances
- [x] Set up new envs
- [x] Add config and license checks
- [x] Implement `MultiMainInstancePublisher`
- [x] Expand `RedisServicePubSubPublisher` to support
`MultiMainInstancePublisher`
- [x] Init `MultiMainInstancePublisher` on startup and destroy on
shutdown
- [x] Add to sandbox plans
- [x] Test manually
Note: This is only for setup - coordinating in reaction to leadership
changes will come in later PRs.
This change ensures that things like `encryptionKey` and `instanceId`
are always available directly where they are needed, instead of passing
them around throughout the code.
In a rare edge case an undefined queue could be returned - this should
not happen and now an error is thrown.
Also using the opportunity to remove a cyclic dependency from the Queue.
This PR adds a message for queue mode which triggers an external secrets
provider reload inside the workers if the configuration has changed on
the main instance.
It also refactors some of the message handler code to remove cyclic
dependencies, as well as remove unnecessary duplicate redis clients
inside services (thanks to no more cyclic deps)
all commands sent between main instance and workers need to contain a
server id to prevent senders from reacting to their own messages,
causing loops
this PR makes sure all sent messages contain a sender id by default as
part of constructing a sending redis client.
---------
Co-authored-by: कारतोफ्फेलस्क्रिप्ट™ <aditya@netroy.in>
Depends on: #7092 | Story:
[PAY-768](https://linear.app/n8n/issue/PAY-768)
This PR:
- Generalizes the `IBinaryDataManager` interface.
- Adjusts `Filesystem.ts` to satisfy the interface.
- Sets up an S3 client stub to be filled in in the next PR.
- Turns `BinaryDataManager` into an injectable service.
- Adjusts the config schema and adds new validators.
Note that the PR looks large but all the main changes are in
`packages/core/src/binaryData`.
Out of scope:
- `BinaryDataManager` (now `BinaryDataService`) and `Filesystem.ts` (now
`fs.client.ts`) were slightly refactored for maintainability, but fully
overhauling them is **not** the focus of this PR, which is meant to
clear the way for the S3 implementation. Future improvements for these
two should include setting up a backwards-compatible dir structure that
makes it easier to locate binary data files to delete, removing
duplication, simplifying cloning methods, using integers for binary data
size instead of `prettyBytes()`, writing tests for existing binary data
logic, etc.
---------
Co-authored-by: कारतोफ्फेलस्क्रिप्ट™ <aditya@netroy.in>
Github issue / Community forum post (link here to close automatically):
---------
Co-authored-by: Omar Ajoue <krynble@gmail.com>
Co-authored-by: कारतोफ्फेलस्क्रिप्ट™ <aditya@netroy.in>
Based on #7065 | Story: https://linear.app/n8n/issue/PAY-771
n8n on filesystem mode marks binary data to delete on manual execution
deletion, on unsaved execution completion, and on every execution
pruning cycle. We later prune binary data in a separate cycle via these
marker files, based on the configured TTL. In the context of introducing
an S3 client to manage binary data, the filesystem mode's mark-and-prune
setup is too tightly coupled to the general binary data management
client interface.
This PR...
- Ensures the deletion of an execution causes the deletion of any binary
data associated to it. This does away with the need for binary data TTL
and simplifies the filesystem mode's mark-and-prune setup.
- Refactors all execution deletions (including pruning) to cause soft
deletions, hard-deletes soft-deleted executions based on the existing
pruning config, and adjusts execution endpoints to filter out
soft-deleted executions. This reduces DB load, and keeps binary data
around long enough for users to access it when building workflows with
unsaved executions.
- Moves all execution pruning work from an execution lifecycle hook to
`execution.repository.ts`. This keeps related logic in a single place.
- Removes all marking logic from the binary data manager. This
simplifies the interface that the S3 client will meet.
- Adds basic sanity-check tests to pruning logic and execution deletion.
Out of scope:
- Improving existing pruning logic.
- Improving existing execution repository logic.
- Adjusting dir structure for filesystem mode.
---------
Co-authored-by: कारतोफ्फेलस्क्रिप्ट™ <aditya@netroy.in>
This PR implements the updated license SDK so that worker and webhook
instances do not auto-renew licenses any more.
Instead, they receive a `reloadLicense` command via the Redis client
that will fetch the updated license after it was saved on the main
instance
This also contains some refactoring with moving redis sub and pub
clients into the event bus directly, to prevent cyclic dependency
issues.
# Motivation
In Queue mode, finished executions would cause the main instance to
always pull all execution data from the database, unflatten it and then
use it to send out event log events and telemetry events, as well as
required returns to Respond to Webhook nodes etc.
This could cause OOM errors when the data was large, since it had to be
fully unpacked and transformed on the main instance’s side, using up a
lot of memory (and time).
This PR attempts to limit this behaviour to only happen in those
required cases where the data has to be forwarded to some waiting
webhook, for example.
# Changes
Execution data is only required in cases, where the active execution has
a `postExecutePromise` attached to it. These usually forward the data to
some other endpoint (e.g. a listening webhook connection).
By adding a helper `getPostExecutePromiseCount()`, we can decide that in
cases where there is nothing listening at all, there is no reason to
pull the data on the main instance.
Previously, there would always be postExecutePromises because the
telemetry events were called. Now, these have been moved into the
workers, which have been given the various InternalHooks calls to their
hook function arrays, so they themselves issue these telemetry and event
calls.
This results in all event log messages to now be logged on the worker’s
event log, as well as the worker’s eventbus being the one to send out
the events to destinations. The main event log does…pretty much nothing.
We are not logging executions on the main event log any more, because
this would require all events to be replicated 1:1 from the workers to
the main instance(s) (this IS possible and implemented, see the worker’s
`replicateToRedisEventLogFunction` - but it is not enabled to reduce the
amount of traffic over redis).
Partial events in the main log could confuse the recovery process and
would result in, ironically, the recovery corrupting the execution data
by considering them crashed.
# Refactor
I have also used the opportunity to reduce duplicate code and move some
of the hook functionality into
`packages/cli/src/executionLifecycleHooks/shared/sharedHookFunctions.ts`
in preparation for a future full refactor of the hooks
This PR adds new endpoints to the REST API:
`/orchestration/worker/status` and `/orchestration/worker/id`
Currently these just trigger the return of status / ids from the workers
via the redis back channel, this still needs to be handled and passed
through to the frontend.
It also adds the eventbus to each worker, and triggers a reload of those
eventbus instances when the configuration changes on the main instances.
* refactor: Set up ownership service
* refactor: Specify cache keys and values
* refactor: Replace util with service calls
* test: Mock service in tests
* refactor: Use dependency injection
* test: Write tests
* refactor: Apply feedback from Omar and Micha
* test: Fix tests
* test: Fix missing spot
* refactor: Return user entity from cache
* refactor: More dependency injection!
