I found here this solution: {__name__=~"metricA|metricB|metricC",container_name=~"frontend|backend|db"}.

First of all, for more complex graphing you should definitely investigate Grafana. The built-in Prometheus graphs are useful eg. for debugging, but definitely more limited. In particular one graph will only display the results of one query.

Now for a hack that I definitely do not recommend:

flink_taskmanager_job_task_operator_numRecordsInPerSecond{operator_name="Map"}
or
label_replace(flink_taskmanager_job_task_operator_numRecordsOutPerSecond{operator_name="Map"}, "distinct", "foo", "job", ".*")

Since, as documented

vector1 or vector2 results in a vector that contains all original elements (label sets + values) of vector1 and additionally all elements of vector2 which do not have matching label sets in vector1.

you can add a new label that is not present in the labels on the first vector to the second vector and thus keep all elements from both.

You need to put the rate before the labels. This should work:

/api/v1/query?query=rate({__name__=~"metric1|metric2|metric3",service=~"testservice"}[30s])

Note that you must have at least one datapoint in the 30s period for each of the metrics.

You can use the argument list of group_left to include extra labels from the right operand (parentheses and indents for clarity):

(
  max(consul_health_service_status{status="critical"}) 
  by (service_name,status,node) == 1
)
   + on(service_name,node) group_left(env)
(
   0 * consul_service_tags
)

The important part here is the operation + on(service_name,node) group_left(env):

• the + is "abused" as a join operator (fine since 0 * consul_service_tags always has the value 0)
• group_left(env) is the modifier that includes the extra label env from the right (consul_service_tags)

First of all, consider converting you metrics to the best practices of Prometheus. I anticipate something like this:

mysystem_request_duration_seconds_sum{type="XXXX"}
mysystem_request_duration_seconds_count{type="XXXX"}
mysystem_request_duration_seconds_sum{type="YYYY"}
mysystem_request_duration_seconds_count{type="YYYY"}

This way you wouldn't need all this hustle with metric names.

In this case your query would look like this:

sum by (container) (
rate(mysystem_request_duration_seconds_sum{type="$myVar"}[5m]) / 
rate(mysystem_request_duration_seconds_count{type="$myVar"}[5m]) )

For your current situation you'll need to employ a couple of tricks:

1. Since you can't query multiple metrics by name with regex, you'll need to use {__name__=~"${myVar_metrics}_sum"}.
2. To divide metrics, you need them to have matching labels.
   You can add label to metric based on metrics name using label_replace:

label_replace({__name__=~"${myVar_metrics}_sum"} ,"foo", "$1", "__name__", "(${myVar_metrics})_sum")

3. Range selector can be applied only to a metric selector. Since label_replace is a function and not a metric selector, you'll need to use subquery syntax. Basically, the difference is addition of semicolon into range selector:

rate(label_replace({__name__=~"${myVar_metrics}_sum"} ,"foo", "$1", "__name__", "(${myVar_metrics})_sum")[5m : ])

Resulting query would look like this:

sum by (container) (
 rate(
  label_replace(
   {__name__=~"${myVar_metrics}_sum"} ,
   "foo", "$1",
   "__name__", "(${myVar_metrics})_sum")
  [5m : ])
/rate(
  label_replace(
   {__name__=~"${myVar_metrics}_count"} ,
   "foo", "$1", 
   "__name__", "(${myVar_metrics})_count")
  [5m : ])
)