By reading the official document of the Function score query, I still couldn’t get a sense of how to use it correctly. After reading through more articles written by others, here’s how I interpret it with the formula of the newly computed score:

function_score = min(score_mode(f1_score, f2_score, ...), max_boost)
_score = boost_mode(boost*query_score, function_score)

Example 1:

{
  "query": {
      "function_score": {
        "query": { "match_all": {} },
        "boost": "5",
        "random_score": {}, 
        "boost_mode": "multiply"
      }
   }
}

Score:

Here are the definitions from the official document for rate() and irate(). But if you still don’t quite understand, check the examples below.

In this example, I select all the values I have recorded within the last 1 minute for all time series that have the metric name prometheus_http_requests_total and a handler label set to /metrics:

prometheus_http_requests_total{handler=”/metrics”}[1m]

Output from the Prometheus UI:

# Element
prometheus_http_requests_total{code="200",handler="/metrics",instance="localhost:9090",job="prometheus"}
# ValueHere are the definitions from the official document for rate() and irate(). But if you still don’t quite understand, check the examples below.

In this example, I select all the values I have recorded within the last 1 minute for all time series that have the metric name prometheus_http_requests_total and a handler label set to /metrics: