If you want to run the test manually, you will need these tools:
- kubectl
- oc
- jq
Setup the OpenShift cluster (assuming oc login ... happened already):
export DEPLOYMENT_TYPE="downstream"
export DEPLOYMENT_VERSION="1.15"
export DEPLOYMENT_PIPELINES_CONTROLLER_HA_REPLICAS=""
export DEPLOYMENT_CHAINS_CONTROLLER_HA_REPLICAS=""
export DEPLOYMENT_PIPELINES_KUBE_API_QPS=""
export DEPLOYMENT_PIPELINES_KUBE_API_BURST=""
export DEPLOYMENT_PIPELINES_THREADS_PER_CONTROLLER=""
export DEPLOYMENT_CHAINS_KUBE_API_QPS=""
export DEPLOYMENT_CHAINS_KUBE_API_BURST=""
export DEPLOYMENT_CHAINS_THREADS_PER_CONTROLLER=""
export DEPLOYMENT_PIPELINES_CONTROLLER_RESOURCES="1/2Gi/1/2Gi"
# export INSTALL_RESULTS="true"
# export STORE_LOGS_IN_S3="true"
# export DEPLOYMENT_TYPE_RESULTS="downstream" # "upstream" (Default: downstream)
# export DEPLOYMENT_RESULTS_UPSTREAM_VERSION="v0.11.0" # Used only for upstream (Default: latest)
# export RUN_LOCUST="true"
# export DEPLOYMENT_RESULTS_DOWNSTREAM_VERSION="1.16" (Default: 1.16)
# export AWS_REGION="eu-west-1"
# export AWS_ENDPOINT="https://s3.eu-west-1.amazonaws.com"
# export DEPLOYMENT_VERSION="1.14"
# export DEPLOYMENT_VERSION="1.13"
ci-scripts/setup-cluster.sh
Run the test:
export TEST_NAMESPACE="1"
export TEST_DO_CLEANUP="false"
export TEST_TOTAL="100"
export TEST_CONCURRENT="10"
export TEST_TIMEOUT=18000
export TEST_SCENARIO="math" # pick this scenario or some of these below
# export TEST_SCENARIO="build"
# export TEST_SCENARIO="signing-ongoing"
# export TEST_SCENARIO="signing-bigbang"
# export TEST_SCENARIO="signing-tr-varying-concurrency"
# export TEST_SCENARIO="cluster-resolver"
# export CHAINS_ENABLE_TIME=0
# ...and more
ci-scripts/load-test.sh
Collect the results:
ci-scripts/collect-results.sh
This is what I did recently on RHEL9 to make test run:
# Packages
rpm -ivh https://dl.fedoraproject.org/pub/epel/epel-release-latest-9.noarch.rpm
dnf install tmux python3-pip jq parallel git-core
# kubectl
curl -Lso /usr/local/bin/kubectl https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl
chmod +x /usr/local/bin/kubectl
# oc from https://access.redhat.com/downloads/content/290
curl -o oc-4.15.0-linux.tar.gz -L "https://access.cdn.redhat.com/content/origin/files/sha256/f0/f0.../oc-4.15.0-linux.tar.gz?user=...&_auth_=..."
tar xzf oc-4.15.0-linux.tar.gz
cp oc /usr/local/bin/oc
chmod +x /usr/local/bin/oc
# cosign
curl -O -L "https://github.com/sigstore/cosign/releases/latest/download/cosign-linux-amd64"
mv cosign-linux-amd64 /usr/local/bin/cosign
chmod +x /usr/local/bin/cosign
# Login to OCP cluster
oc login https://...:6443 --username ... --password ... --insecure-skip-tls-verify
You can run multiple different scenarios.
These are configured via TEST_SCENARIO environment variable.
To learn what each scenario does, check readme files in tests/scaling-pipelines/scenario/ subfolders.
This section describes what is configured where when it comes to automated runs of this test in OpenShift CI/Prow system.
To execute the tests we are using Prow. Jobs in Prow were configured in openshift/release PR#44206.
Nice documentation on how to onboard new test is OpenShift CI Scenario Onboarding Guide.
Description of ci-operator configuration is in Types of Tests.
If we ever need to add some secrets to the test, review OpenShift CI Interop Scenario Secrets Guide docs. There is openshift-pipelines-perfscale collection in OpenShift CI Secret Collection Management. Login there and ping @jhutar to make you a member to be able to see it. Once added, you should be able to see the secret in OpenShift CI Vault. In the job, secrets needs to be mounted under /usr/local/ci-secrets/openshift-pipelines-perfscale directory (it was removed as not necessary after initial PR).
In openshift/release repo PR, you can trigger the test with /pj-rehearse pull-ci-openshift-pipelines-performance-master-scaling-pipelines. Also twice a day (02:00 and 14:00 UTC) Prow will trigger periodic-ci-openshift-pipelines-performance-master-scaling-pipelines-daily (history).
Test code is in tests/scalingPipelines/ directory. See readme in that directory for more info.
Every hour we run a CI puller script (see ci-scripts/prow-to-storage.sh) via Jenkins job. There is a Jenkinsfile and JobDSL file for this job.
Script ci-scripts/prow-to-storage.sh lists N recent Prow builds of the job and if not pushed already, pushes their results JSON file to Horreum and OpenSearch. After uploading to Horreum, script checks if change detection detected some change, and if so, adds a "result" key to the JSON with "FAIL" value, otherwise "PASS". Upload to OpenSearch happens with this value in place.
Horreum instance we are using is: https://horreum.corp.redhat.com/ (managed by Horreum team: Horreum Google Chat space). It is meant to help spot failing test by comparing it with historical data.
You can browse data and graphs without login, but to change the configuration, you will need an account. In Horreum we have a team Openshift-pipelines. Ping @johara in above linked Google Chat space to create you a user and then @kbaig or @jhutar to add you to the team.
Current test configuration:
- JSON schema: urn:openshift-pipelines-perfscale-scalingPipelines:0.1
- Test definition and changes detection configuration: openshift-pipelines-perfscale-scalingPipelines (in
Openshift-pipelinesfolder) - Test runs: openshift-pipelines-perfscale-scalingPipelines Runs
- Change detection: openshift-pipelines-perfscale-scalingPipelines Changes
Check test change detection settings to understand under which circumstances Horreum tags new result as a "change".
OpenSearch (a.k.a. ElasticSearch) instance we are using: http://elasticsearch.intlab.perf-infra.lab.eng.rdu2.redhat.com/ and OpenSearch Dashboard (a.k.a. Kibana) instance we are using: http://kibana.intlab.perf-infra.lab.eng.rdu2.redhat.com/ (managed by Perf&Scale Integrations lab team: INTLAB Jira). It is meant to provide useful dashboard and a way how to explore historical test data.
All data are being pushed to pipelines_ci_status_data index in OpenSearch. You can browse the data in "Discover" section with that index selected. As basic insight into the data you can use this dashboard. It's JSON definition is backed up in config/kibana/ directory.