sqooba / scala-promql-client   0.6.0

Apache License 2.0 GitHub

A Scala client for running queries against a Prometheus backend.

Scala versions: 2.13 2.12

Scala Prometheus Query Client

Welcome to scala-promql-client.

This is an sttp based scala client for issuing queries against a Prometheus server.

This is not a library to instrument your scala application.

This library is relied on in contexts where we use a Prometheus instance as a time-series store and wish to run queries for analytical purposes from a Scala application.

Some commands are specific to the promQL compatible VictoriaMetrics server and not supported in the original Prometheus server though.

It is in a draft state at the moment: we will avoid deep API changes if possible, but can't exclude them.


The library is available on sonatype, to use it in an SBT project add the following line:

libraryDependencies += "io.sqooba.oss" %% "scala-promql-client" % "0.5.0"

For maven:




In order to work properly, the client needs a configuration. This configuration is available and can be constructed using a PrometheusClientConfig case class. The following parameters are required:

  • Server's hostname or ip
  • Server's port
  • The maximum number of points a prometheus endpoint can return before we have to split queries (defined by the server, VictoriaMetrics has this value set to 30 000 by default)
  • Number of retries to perform in case of a failed query
  • Number of requests that can be made in parallel when splitting queries, be careful when changing this value

It is also possible to load this configuration from a file. The PrometheusClient.liveDefault method will look inside application.conf for a block named promql-client and that contains the following values:

promql-client {
    host = localhost
    port = 8428
    ssl = true
    maxPointsPerTimeseries = 30000
    retryNumber = 3
    parallelRequests = 1

For authentication add a sub-configuration section such as :

promql-client {
  auth-basic-credentials {
    username: "username"
    password: "password"
  //------- OR -------
  auth-basic-token {
    token: "xxxx"
  //------- OR -------
  auth-bearer {
    bearer: "xxxxx"

Note : Prefer the use of environment variables to provide secrets to your application, such as PROMQL_CLIENT_AUTH_BASIC_PASSWORD in the previous example. Your can rename those example environment variables as you wish.

Both live methods inside the PrometheusClient object can be used to create a layer providing a PrometheusService given a configuration.

Importing data

PrometheusService has a put method that can be used to insert datapoints inside VictoriaMetrics, it can be used that way:

import java.time.Instant
import io.sqooba.oss.promql.metrics.PrometheusInsertMetric
import io.sqooba.oss.promql.{PrometheusClient, PrometheusService}

object Main extends zio.App {

  def run(args: List[String]) = {
    val now = Instant.now
    val layer = PrometheusClient.liveDefault // Load configuration from file

              "__name__" -> "timeseries_label"
            Seq(1, 2, 3),
            Seq(now.toEpochMilli, now.minusSeconds(60).toEpochMilli, now.minusSeconds(120).toEpochMilli)


This will insert three points with value 1, 2 and 3 for the last three minutes.

Prometheus does not support manually importing, other than backfilling.

Addings tags

It is possible to add tags to a timeseries by using the Map given as first argument to PrometheusInsertMetric. The tag called __name__ is a special tag that contains the name of the timeseries in prometheus.

Running queries

Using the query method available on a PrometheusService it is possible to run arbitrary Prometheus queries. As described on Prometheus' documentation, there are a few different queries that can be run, this client currently supports:

  • InstantQuery documentation to run a query at a single point in time
  • RangeQuery documentation to run a query over a range of time

The following meta queries allow querying the set of available metrics for a specific time range:

SeriesQuery documentation to find the metrics, identified by combinations of labels - returns MetricListReponseData or EmptyResponseData

  • LabelsQuery documentation to get a list of actually used lables
    • returns StringListResponsedata or EmptyResponseData
  • LabelValuesQuery documentation to get a list of actually used values for a given label
    • returns StringListResponsedata or EmptyResponseData

The meta queries are not precisely specified, and the behaviour may differ sightly from one promQL compatible server implementation to another.

The query can be used in the following way:

import java.time.Instant
import scala.concurrent.duration._
import io.sqooba.oss.promql.metrics.PrometheusInsertMetric
import io.sqooba.oss.promql.{RangeQuery, PrometheusClient, PrometheusService}

object Main extends zio.App {

  def run(args: List[String]) = {
    val start = Instant.now.minusSeconds(24 * 60 * 60)
    val layer = PrometheusClient.liveDefault

    val query = RangeQuery(



A way to run multiple queries is by using a for-comprehension:

for {
  firstData <- PrometheusService.query(query)
  secondData <- PrometheusService.query(secondQuery)
} yield {
  (firstData, secondData) match {
    case (x@MatrixResponseData(_), y@MatrixResponseData(_)) => Some(x.merge(y))
    case _ => None

Don't forget to pattern match and provide for a regular case _. Meta queries have to deal with empty responses by the means of the EmptyResponseData type.


Container based testing

Most unit tests are run against mocked data. Basing your "*Spec" suite object on io.sqooba.oss.promql_container.PromClientRunnable instead instanciates a fresh docker container for every test.

Note that the OSAG CI pipeline currently does not execute Docker-based unit tests!

Multiple container versions

To account for potentially different behaviour of various versions of VictoriaMetrics, use for a check against a single version or MultiVersionVictoriaClientRunnable to run the whole suite of tests against a list of versions at once.

The MultiVersionPromClientRunnable will instantiate a original Prometheus container. Obviously, the "put" command will fail on this one. As an alternative, the contents of the metrics resource file is pre-loaded.

Currently, in this library, the Victoriametetrics versions "v1.47.0", "v1.53.1", " v1.61.1" are checked by default.

Starting tests

The tests involving containers will be run by sbt test.

However, the following JUnit tests have to be started manually (e.g "run" in your favourite IDE), because sbt test will not pick them up:

  • PrometheusClientSpec
  • PrometheusInsertMetricSpec
  • PrometheusQuerySpec
  • PrometheusResponseSpec
  • PrometheusScalarResponseSpec

The reason is the ZIO-Testrunner annotation. We haven't found a way to marry it with sbt and JUnit.


use the multi version facility by specifying your test suite as :

object PrometheusAppSpec extends MultiVersionPromClientRunnable {

optionally giving a custom list of Versions for your test suite :

override val versions: Seq[String] = Seq("v1.61.1")

When using higher level clients that use a promql-client layer, you can define a new *Runnable class extending the MultiVersionPromClient with your needed Environment Layers. (e.g. for Chronos):

abstract class ChronosRunnable extends MultiVersionPromClient[ChronosEnv] {
  override val versions: Seq[String] = Seq("v1.42.0", "v1.47.0", "v1.53.1", "v1.61.1")

  type ChronosRunnable = ZSpec[ChronosEnv, Any]

   * Create a test environment by spawning a VictoriaMetrics container, building a client configuration
   * as well as a ChronosClient to be used by the tests
  override def buildLayer(v: String): ULayer[ChronosEnv] =
    victoriaLayer(v) >+> ChronosClient.live


Versions and releases

See the changelog for more details.