https://linear.app/unleash/issue/2-2518/figure-out-how-to-create-the-initial-admin-user-in-unleash
The logic around `initAdminUser` that was introduced in
https://github.com/Unleash/unleash/pull/4927 confused me a bit. I wrote
new tests with what I assume are our expectations for this feature and
refactored the code accordingly, but would like someone to confirm that
it makes sense to them as well.
The logic was split into 2 different methods: one to get the initial
invite link, and another to send a welcome email. Now these two methods
are more granular than the previous alternative and can be used
independently of creating a new user.
---------
Co-authored-by: Gastón Fournier <gaston@getunleash.io>
For easy gitar integration, we need to have boolean in the event
payload.
We might rethink it when we add variants, but currently enabled with
variants is not used.
Changes the event search handling, so that searching by user uses the
user's ID, not the "createdBy" name in the event. This aligns better
with what the OpenAPI schema describes it.
After adding an index, the time for the new event search on 100k events
decreased from 5000ms to 4ms. This improvement is due to the query using
an index scan instead of a sequence scan.
Encountered this case after encrypting an already long email address.
This should mitigate the issue in demo instance. I don't think it's a
big issue to ignore the length when validating an email address cause
this is already limited at the DB layer by the column length
Adds an endpoint to return all event creators.
An interesting point is that it does not return the user object, but
just created_by as a string. This is because we do not store user IDs
for events, as they are not strictly bound to a user object, but rather
a historical user with the name X.
Previously people were able to send random data to feature type. Now it
is validated.
Fixes https://github.com/Unleash/unleash/issues/7751
---------
Co-authored-by: Thomas Heartman <thomas@getunleash.io>
Changed the url of event search to search/events to align with
search/features. With that created a search controller to keep all
searches under there.
Added first test.
This PR adds Grafana gauges for all the existing resource limits. The
primary purpose is to be able to use this in alerting. Secondarily, we
can also use it to get better insights into how many customers have
increased their limits, as well as how many people are approaching their
limit, regdardless of whether it's been increased or not.
## Discussion points
### Implementation
The first approach I took (in
87528b4c67),
was to add a new gauge for each resource limit. However, there's a lot
of boilerplate for it.
I thought doing it like this (the current implementation) would make it
easier. We should still be able to use the labelName to collate this in
Grafana, as far as I understand? As a bonus, we'd automatically get new
resource limits when we add them to the schema.
``` tsx
const resourceLimit = createGauge({
name: 'resource_limit',
help: 'The maximum number of resources allowed.',
labelNames: ['resource'],
});
// ...
for (const [resource, limit] of Object.entries(config.resourceLimits)) {
resourceLimit.labels({ resource }).set(limit);
}
```
That way, when checking the stats, we should be able to do something
like this:
``` promql
resource_limit{resource="constraintValues"}
```
### Do we need to reset gauges?
I noticed that we reset gauges before setting values in them all over
the place. I don't know if that's necessary. I'd like to get that double
clarified before merging this.
https://linear.app/unleash/issue/2-2501/adapt-origin-middleware-to-stop-logging-ui-requests-and-start
This adapts the new origin middleware to stop logging UI requests (too
noisy) and adds new Prometheus metrics.
<img width="745" alt="image"
src="https://github.com/user-attachments/assets/d0c7f51d-feb6-4ff5-b856-77661be3b5a9">
This should allow us to better analyze this data. If we see a lot of API
requests, we can dive into the logs for that instance and check the
logged data, like the user agent.
This PR adds some helper methods to make listening and emitting metric
events more strict in terms of types. I think it's a positive change
aligned with our scouting principle, but if you think it's complex and
does not belong here I'm happy with dropping it.
