Adds a killswitch called "filterExistingFlagNames". When enabled it will
filter out reported SDK metrics and remove all reported metrics for
names that does not match an exiting feature flag in Unleash.
This have proven critical in the rare case of an SDK that start sending
random flag-names back to unleash, and thus filling up the database. At
some point the database will start slowing down due to the noisy data.
In order to not resolve the flagNames all the time we have added a small
cache (10s) for feature flag names. This gives a small delay (10s) from
flag is created until we start allow metrics for the flag when
kill-switch is enabled. We should probably listen to the event-stream
and use that invalidate the cache when a flag is created.
We now have customers that exceed INT capacity, so we need to change
this to BIGINT in client_metrics_env_variants_daily as well.
Even heavy users only have about 10000 rows here, so should be a quick
enough operation.
## About the changes
When storing last seen metrics we no longer validate at insert time that
the feature exists. Instead, there's a job cleaning up on a regular
interval.
Metrics for features with more than 255 characters, makes the whole
batch to fail, resulting in metrics being lost.
This PR helps mitigate the issue while also logs long name feature names
This adds an extended metrics format to the metrics ingested by Unleash
and sent by running SDKs in the wild. Notably, we don't store this
information anywhere new in this PR, this is just streamed out to
Victoria metrics - the point of this project is insight, not analysis.
Two things to look out for in this PR:
- I've chosen to take extend the registration event and also send that
when we receive metrics. This means that the new data is received on
startup and on heartbeat. This takes us in the direction of collapsing
these two calls into one at a later point
- I've wrapped the existing metrics events in some "type safety", it
ain't much because we have 0 type safety on the event emitter so this
also has some if checks that look funny in TS that actually check if the
data shape is correct. Existing tests that check this are more or less
preserved
