Slow getPipelineDetails spends abnormally high CPU time

Summary

For a slow getPipelineDetails query of 1.624s it spends about 1.59s in cpu_s and only 0.04882s in db_duration_s indicating either inefficiency or if this is expected, incorrect Apdex score calculation

Steps to reproduce

This is happening on a Dedicated customer with large pipeline where the UI makes a graphql query of complexity of 198.

Example Project

What is the current bug behavior?

When the user views the pipeline via Gitlab UI it creates a drop in apdex and thus breach of SLO

What is the expected correct behavior?

The query either completes within expected time duration or the current behavior is considered normal and doesn't affect the apdex score

Relevant logs and/or screenshots

Output of checks

Results of GitLab environment info

Expand for output related to GitLab environment info

 (For installations with omnibus-gitlab package run and paste the output of: \`sudo gitlab-rake gitlab:env:info\`)  (For installations from source run and paste the output of: \`sudo -u git -H bundle exec rake gitlab:env:info RAILS_ENV=production\`)  

Results of GitLab application Check

Expand for output related to the GitLab application check

(For installations with omnibus-gitlab package run and paste the output of: `sudo gitlab-rake gitlab:check SANITIZE=true`)

(For installations from source run and paste the output of: `sudo -u git -H bundle exec rake gitlab:check RAILS_ENV=production SANITIZE=true`)

(we will only investigate if the tests are passing)

Possible fixes

Patch release information for backports

If the bug fix needs to be backported in a patch release to a version under the maintenance policy, please follow the steps on the patch release runbook for GitLab engineers.

Refer to the internal "Release Information" dashboard for information about the next patch release, including the targeted versions, expected release date, and current status.

High-severity bug remediation

To remediate high-severity issues requiring an internal release for single-tenant SaaS instances, refer to the internal release process for engineers.