I checked your proposed solution:

(metric_b and metric_a>=3) or metric_a<bool 3

and it worked like expected, returning the value of metric_b when metric_a is >= 3, and 1 otherwise.

It's important to note that "VECTOR1 and VECTOR2" it's not necessarily equals to "VECTOR2 and VECTOR1". Take a look at the Prometheus documentation about this:

vector1 and vector2 results in a vector consisting of the elements of vector1 for which there are elements in vector2 with exactly matching label sets. Other elements are dropped.

The results are always from the first vector of the "and" clause.

For example, the following query:

Gives a different result of the following one:

Try the following query:

(always_exists - sometimes_exists) or (always_exists unless sometimes_exists)

It uses or and unless operators. See more details on these operators at https://prometheus.io/docs/prometheus/latest/querying/operators/#logical-set-binary-operators

P.S. The query can be simplified to sum(always_exists, -sometimes_exists) in VictoriaMetrics, since MetricsQL supports multiple arguments in aggregate functions such as sum. (I'm the core developer of VictoriaMetrics)

Your attempt is in correct direction. It's just that on() clause needs label common for both metrics, but based on your example, they are not.

This is not a problem though: label_replace can help us here.

metric_name1
 unless on(label1)
 label_replace(metric_name2, "label1", "$1", "label2", "(.*)")

Here, I copy label label2 into label1, and then use it in unless to exclude all the metrics with matching label1.

You don't need group_left since unless with on clause doesn't change left operand's labels set (unlike and with on clause).

• The by modifier groups aggregate function results by labels enumerated inside by(...).
• The without modifier groups aggregate function results by all the labels except those enumerated inside without(...).

For example, suppose process_resident_memory_bytes metric exists with job, instance and datacenter labels:

process_resident_memory_bytes{job="job1",instance="host1",datacenter="dc1"} N1
process_resident_memory_bytes{job="job1",instance="host2",datacenter="dc1"} N2
process_resident_memory_bytes{job="job1",instance="host1",datacenter="dc2"} N3
process_resident_memory_bytes{job="job2",instance="host1",datacenter="dc1"} N4

Then sum(process_resident_memory_bytes) by (datacenter) would return summary per-datacenter memory usage, while sum(process_resident_memory_bytes) without (instance) would return summary per-job per-datacenter memory usage.