Documentation Grafana k6 Using k6 Workaround to calculate iteration_duration
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Workaround to calculate iteration_duration

A common requested case is to track the iteration_duration metric without including time spent for setup and teardown functions. This feature is not yet available but a threshold on iteration_duration or any pre-existing metrics can be used as a workaround.

It’s based on the concept of creating thresholds for sub-metrics created by tags for the required scope and setting the criteria that always pass. It works with any enabled tags that already works with threshold, for example:

  • iteration_duration{scenario:default} generates a sub-metric collecting samples only for the default scenario’s iteration. scenario:default is used because that’s the internal k6 scenario name when we haven’t specified options. scenarios` explicitly and are just using the execution shortcuts instead.
  • iteration_duration{group:::setup} or iteration_duration{group:::teardown} create sub-metrics collecting the duration only for setup and teardown. k6 implicitly creates groups for setup and teardown, and :: is the group separator.
  • http_req_duration{scenario:default} can be useful as well for isolating executed long-running requests.
import { sleep } from 'k6';
import http from 'k6/http';

export const options = {
  vus: 1,
  iterations: 1,
  thresholds: {
    'iteration_duration{scenario:default}': [`max>=0`],
    'iteration_duration{group:::setup}': [`max>=0`],
    'iteration_duration{group:::teardown}': [`max>=0`],
    'http_req_duration{scenario:default}': [`max>=0`],

export function setup() {

export default function () {

export function teardown() {

Dedicated sub-metrics have been generated collecting samples only for the scope defined by thresholds:

http_req_duration..............: avg=1.48s    min=101.95ms med=148.4ms  max=5.22s    p(90)=4.21s    p(95)=4.71s
  { expected_response:true }...: avg=1.48s    min=101.95ms med=148.4ms  max=5.22s    p(90)=4.21s    p(95)=4.71s
✓ { scenario:default }.........: avg=148.4ms  min=103.1ms  med=148.4ms  max=193.7ms  p(90)=184.64ms p(95)=189.17ms

iteration_duration.............: avg=5.51s    min=1.61s    med=6.13s    max=8.81s    p(90)=8.27s    p(95)=8.54s
✓ { group:::setup }............: avg=6.13s    min=6.13s    med=6.13s    max=6.13s    p(90)=6.13s    p(95)=6.13s
✓ { group:::teardown }.........: avg=8.81s    min=8.81s    med=8.81s    max=8.81s    p(90)=8.81s    p(95)=8.81s
✓ { scenario:default }.........: avg=1.61s    min=1.61s    med=1.61s    max=1.61s    p(90)=1.61s    p(95)=1.61s