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Prombench in GKE

Run prombench tests in Google Kubernetes Engine.

Setup prombench

  1. Create the main node
  2. Deploy monitoring components
  3. Start a benchmarking test manually

Create the Main Node

  • Create a new project on Google Cloud.

  • Create a Service Account on GKE with role Kubernetes Engine Service Agent & Kubernetes Engine Admin. If using gcloud cli add the roles/container.admin and roles/iam.serviceAccountUser roles to the GCP serviceAccount and download the json file.

  • Set the following environment variables and deploy the cluster.

export GKE_PROJECT_ID=<google-cloud project-id>
export CLUSTER_NAME=prombench
export ZONE=us-east1-b
export AUTH_FILE=<path to service-account.json>
export PROVIDER=gke

make cluster_create

Deploy monitoring components

Collecting, monitoring and displaying the test results and logs

  • [Optional] If used with the Github integration generate a GitHub auth token. 
export SERVICEACCOUNT_CLIENT_EMAIL=<client-email present in service-account.json>
export GRAFANA_ADMIN_PASSWORD=password
export DOMAIN_NAME=prombench.prometheus.io # Can be set to any other custom domain or an empty string when not used with the Github integration.
export OAUTH_TOKEN=<generated token from github or set to an empty string " ">
export WH_SECRET=<github webhook secret>
export GITHUB_ORG=prometheus
export GITHUB_REPO=prometheus

make cluster_resource_apply
  • The output will show the ingress IP which will be used to point the domain name to. Alternatively you can see it from the GKE/Services tab.
  • Set the A record for <DOMAIN_NAME> to point to nginx-ingress-controller IP address.
  • The services will be accessible at:
    • Grafana :: http://<DOMAIN_NAME>/grafana
    • Prometheus :: http://<DOMAIN_NAME>/prometheus-meta
    • Logs :: http://<DOMAIN_NAME>/grafana/explore
    • Profiles :: http://<DOMAIN_NAME>/profiles

Usage

Start a benchmarking test manually

  • Set the following environment variables.
export RELEASE=<master/main or any prometheus release(ex: v2.3.0) >
export PR_NUMBER=<PR to benchmark against the selected $RELEASE>
  • Create the nodepools for the k8s objects
make node_create
  • Deploy the k8s objects
make resource_apply

Stopping a benchmarking test manually

  • Set the following environment variables:
export GKE_PROJECT_ID=<google-cloud project-id>
export CLUSTER_NAME=prombench
export ZONE=us-east1-b
export AUTH_FILE=<path to service-account.json>
export PROVIDER=gke

export PR_NUMBER=<PR to benchmark against the selected $RELEASE>
  • To delete just the nodepool (while keeping the cluster's main node intact), run:
make clean
  • To delete everything (complete teardown of the entire cluster and all the resources), run:
make cluster_delete