I have a Prometheus alert that fires if a user sessions causing a lock on a resource. The problem is, sometimes multiple locks occur from different users which are never the same. If I add the user label which will only exist for a short time, will this still cause high cardinality, or it not an issue since the labels are never the same user? My data is stored for 2d in Prometheus and long term in Thanos storage. I usually get 2 usernames a day, so I'd be adding two new time series a day.
Prometheus short term label usage
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A time series is uniquely identified by its name plus all its
label="value"
pairs. So, if you adduser="some_value"
label to existing time series, then new time series are created every time whensome_value
changes, even if only a single sample is stored for the new time series (e.g. there are noshort-term
labels in Prometheus).If you are going to add
user="..."
label to 10 metrics, e.g.:Then 10 new time series are created with each new
user
value. If you have 2 new users per day, then10*2 = 20
new time series will be created per day. This is known aschurn rate
.20 new time series per day is very small churn rate for Prometheus, so it is safe to use
user
label in this case. But if theuser
label presents in 10K metrics and theuser
label gets 1K new values per day, then the daily churn rate would be10K * 1K = 10M
new time series per day. This is quite big number (known as high churn rate) and it can cause high memory usage and slow queries at Prometheus side.