In order to prevent users from being able to assign roles/permissions
they don't have, this PR adds a check that the user performing the
action either is Admin, Project owner or has the same role they are
trying to grant/add.
This addAccess method is only used from Enterprise, so there will be a
separate PR there, updating how we return the roles list for a user, so
that our frontend can only present the roles a user is actually allowed
to grant.
This adds the validation to the backend to ensure that even if the
frontend thinks we're allowed to add any role to any user here, the
backend can be smart enough to stop it.
We should still update frontend as well, so that it doesn't look like we
can add roles we won't be allowed to.
## About the changes
Our frontend API creates new instances of unleash-client-proxy. Because
this is by-design, we don't want to log a warning that was designed to
warn users about potential misconfiguration of Unleash Proxy.
As an extra, I'm renaming ProxyController to FrontendAPIController to
better reflect the intent of this controller.
## About the changes
This is a rough initial version as a PoC for a permission matrix.
This is only available after enabling the flag `userAccessUIEnabled`
that is set to true by default in local development.
The access was added to the users' admin page but could be embedded in
different contexts (e.g. when assigning a role to a user):
This is how the matrix looks like
---------
Co-authored-by: Nuno Góis <github@nunogois.com>
Fixes ##5799 and #5785
When you do not provide a token we should resolve to the "default"
environment to maintain backward compatibility. If you actually provide
a token we should prefer that and even block the request if it is not
valid.
An interesting fact is that "default" environment is not available on a
fresh installation of Unleash. This means that you need to provide a
token to actually get access to toggle configurations.
---------
Co-authored-by: Thomas Heartman <thomas@getunleash.io>
Created a build script that generates orval schemas with automatic
cleanup. Also generating new ones.
1. yarn gen:api **(generates schemas)**
2. rm -rf src/openapi/apis **(remove apis)**
3. sed -i '1q' src/openapi/index.ts **(remove all rows except first)**
This change takes the (now rather involved) type used to send CR
schedule suspension emails and extracts it into a proper exported type.
This will allow us to import it in enterprise as well instead of
redefining it.
## About the changes
Implements a new store for collected traffic data usage that connects to
the new table `stat_traffic_data` primary key'd on [day, trafficGroup,
status_code_series].
Day being a date
Traffic group being which endpoint is being counted for, ie /api/admin,
/api/frontend etc
Status code series grouping 2xx status responses and 304 into their
respective 200 / 300 series.
No service here, this is for pro/enterprise
This PR adds an endpoint to Unleash that accepts an error message and
option error stack and logs it as an error. This allows us to leverage
errors in logs observability to catch UI errors consistently.
Considered a test, but this endpoint only accepts and logs input, so I'm
not sure how useful it would be.
## About the changes
Adds migration for creating table `stat_traffic_usage`.
This table primary-keys on day, traffic_group, and status_code_series.
Adds individual indexes for day, traffic_group, and status_code_series.
Traffic group is the grouping for API endpoints for which traffic is
counted.
status_code_series is 200/202 etc = 200, 304 etc = 300
## About the changes
App stats is mainly used to cap the number of applications reported to
Unleash based on the last 7 days information:
cc2ccb1134/src/lib/middleware/response-time-metrics.ts (L24-L28)
Instead of getting all stats, just calculate appCount statistics
Use scheduler service instead of setInterval
On all pods and instances, we run the same revision update query every
second. It is relatively fast when the application has started. This is
the single most ran query in unleash.
Benchmarks:
1. Running pod with existing revisionID:
- old 5.5ms
- new 0.028ms
2. New pod without existing revisionID
- old 9.329ms
- new 0.033ms
This query is getting optimized
7e66a79f9f/src/lib/features/events/event-store.ts (L161)
We have customers with tens or hundreds of thousands of applications,
and we have a scheduler running that sets application fields to
`announced` as true. However, every time it runs, it queries the entire
table, which is slow and causes database connection acquisition issues.
To make it faster, we added a partial index to the table.
This PR updates the change request email sending method to handle the
recent changes we have made. That means that the email now:
- says that change requests have been suspended instead of saying that
application will fail.
- handles cases where segments or strategies have been updated causing
potential conflicts.
I have updated the email templates and made some adjustments to the
email sending method. To make the transition from one to the other
easier, I have kept the original method as an interim solution until
enterprise has switched over.
## About the changes
getAllActive from api-tokens store is the second most frequent query
To prevent starving our db connections, we can cache this data that
rarely changes and clear the cache when we see changes. Because we will
only clear changes in the node receiving the change we're only caching
the data for 1 minute.
This should give us some room to test if this solution will work
---------
Co-authored-by: Nuno Góis <github@nunogois.com>
Adds a new Inactive Users list component to admin/users for easier cleanup of users that are counted as inactive: No sign of activity (logins or api token usage) in the last 180 days.
---------
Co-authored-by: David Leek <david@getunleash.io>
In the beginning we used process.nextTick() as a trick to load some data
initally in the constructor of a service.
This is a bad pattern and we should generally avoid any async operations
in the constructor. Today we have two alternatives:
1. Defer loading until data is needed (wrap it in async)
2. Use the schdule-service.
When a stop signal is sent to Unleash the scheduler-service should
cancel any scheduled jobs. This also applies to the job scheduled for
initial execution with jitter.
We observed that initial jobs was executed after the database
connections are terminated. This appears after v5.9.0 of Unleash.
```
Error: aborted
at Object.queryBuilder (/unleash/node_modules/knex/lib/knex-builder/make-knex.js:112:26)
at createQueryBuilder (/unleash/node_modules/knex/lib/knex-builder/make-knex.js:320:26)
at EventStore.knex [as db] (/unleash/node_modules/knex/lib/knex-builder/make-knex.js:101:12)
at EventStore.setUnannouncedToAnnounced (/unleash/node_modules/unleash-server/dist/lib/features/events/event-store.js:286:33)
at EventStore.publishUnannouncedEvents (/unleash/node_modules/unleash-server/dist/lib/features/events/event-store.js:293:35)
at EventAnnouncer.publishUnannouncedEvents (/unleash/node_modules/unleash-server/dist/lib/services/event-announcer-service.js:9:32)
at runScheduledFunctionWithEvent (/unleash/node_modules/unleash-server/dist/lib/features/scheduler/scheduler-service.js:30:23)
at Timeout.<anonymous> (/unleash/node_modules/unleash-server/dist/lib/features/scheduler/scheduler-service.js:50:27)
at runNextTicks (node:internal/process/task_queues:60:5)
at process.processTimers (node:internal/timers:509:9)
```
## About the changes
Queries on client-feature-toggle store have many purposes depending on
the requestType, making the query more complex or not depending on the
use case. Also, each use case has different frequencies (i.e. playground
is expected to be used rarely).
The name for the store metrics was wrong, copy&pasted from:
7b04db0547/src/lib/features/feature-toggle/feature-toggle-store.ts (L107)
Which was also present in feature-tag metrics:
7b04db0547/src/lib/db/feature-tag-store.ts (L37)
With this, we'll have more granularity to understand the execution time
and frequency of each
Usually maintenance mode is disabled. If the call throws, which we see a
lot of when a unleash instance is in terminating state, we should return
a default value.
By having it throw inside of the memoizee function, the response is not
cached, and it will trigger new calls until it return a cachable result.
