# Which Problems Are Solved
The event execution system currently uses a projection handler that
subscribes to and processes all events for all instances. This creates a
high static cost because the system over-fetches event data, handling
many events that are not needed by most instances. This inefficiency is
also reflected in high "rows returned" metrics in the database.
# How the Problems Are Solved
Eliminate the use of a project handler. Instead, events for which
"execution targets" are defined, are directly pushed to the queue by the
eventstore. A Router is populated in the Instance object in the authz
middleware.
- By joining the execution targets to the instance, no additional
queries are needed anymore.
- As part of the instance object, execution targets are now cached as
well.
- Events are queued within the same transaction, giving transactional
guarantees on delivery.
- Uses the "insert many fast` variant of River. Multiple jobs are queued
in a single round-trip to the database.
- Fix compatibility with PostgreSQL 15
# Additional Changes
- The signing key was stored as plain-text in the river job payload in
the DB. This violated our [Secrets
Storage](https://zitadel.com/docs/concepts/architecture/secrets#secrets-storage)
principle. This change removed the field and only uses the encrypted
version of the signing key.
- Fixed the target ordering from descending to ascending.
- Some minor linter warnings on the use of `io.WriteString()`.
# Additional Context
- Introduced in https://github.com/zitadel/zitadel/pull/9249
- Closes https://github.com/zitadel/zitadel/issues/10553
- Closes https://github.com/zitadel/zitadel/issues/9832
- Closes https://github.com/zitadel/zitadel/issues/10372
- Closes https://github.com/zitadel/zitadel/issues/10492
---------
Co-authored-by: Stefan Benz <46600784+stebenz@users.noreply.github.com>
(cherry picked from commit a9ebc06c77)
# Which Problems Are Solved
We identified the need of caching.
Currently we have a number of places where we use different ways of
caching, like go maps or LRU.
We might also want shared chaches in the future, like Redis-based or in
special SQL tables.
# How the Problems Are Solved
Define a generic Cache interface which allows different implementations.
- A noop implementation is provided and enabled as.
- An implementation using go maps is provided
- disabled in defaults.yaml
- enabled in integration tests
- Authz middleware instance objects are cached using the interface.
# Additional Changes
- Enabled integration test command raceflag
- Fix a race condition in the limits integration test client
- Fix a number of flaky integration tests. (Because zitadel is super
fast now!) 🎸🚀
# Additional Context
Related to https://github.com/zitadel/zitadel/issues/8648
* fix: assign instance ID to aggregate ID when converting from v1 to v2 feature
This change fixes a mismatch between v1 and v2 aggregate IDs for instance feature events.
The old v1 used a random aggregate ID, while v2 uses the instance ID as aggregate ID.
The adapter was not correctly mapping, which resulted in the projections.instance_features table being filled with wrong instance IDs.
Closes#7501
* fix unit test
* partial work done
* test IAM membership roles
* org membership tests
* console :(, translations and docs
* fix integration test
* fix tests
* add EnableImpersonation to security policy API
* fix integration test timestamp checking
* add security policy tests and fix projections
* add impersonation setting in console
* add security settings to the settings v2 API
* fix typo
* move impersonation to instance
---------
Co-authored-by: Livio Spring <livio.a@gmail.com>
* feat(api): feature API proto definitions
* update proto based on discussion with @livio-a
* cleanup old feature flag stuff
* authz instance queries
* align defaults
* projection definitions
* define commands and event reducers
* implement system and instance setter APIs
* api getter implementation
* unit test repository package
* command unit tests
* unit test Get queries
* grpc converter unit tests
* migrate the V1 features
* migrate oidc to dynamic features
* projection unit test
* fix instance by host
* fix instance by id data type in sql
* fix linting errors
* add system projection test
* fix behavior inversion
* resolve proto file comments
* rename SystemDefaultLoginInstanceEventType to SystemLoginDefaultOrgEventType so it's consistent with the instance level event
* use write models and conditional set events
* system features integration tests
* instance features integration tests
* error on empty request
* documentation entry
* typo in feature.proto
* fix start unit tests
* solve linting error on key case switch
* remove system defaults after discussion with @eliobischof
* fix system feature projection
* resolve comments in defaults.yaml
---------
Co-authored-by: Livio Spring <livio.a@gmail.com>
