The goal of Kubebench is to make it easy to run benchmark jobs on Kubeflow with various system and model settings. Kubebench enables benchmarks by leveraging Kubeflow's capability of managing TFJobs, as well as Argo based workflows.
NOTE: the quick start guide serves as a demo that helps you quickly go through a Kubebench Job. The components installed may not be suitable for production use. Please refer to detailed user guide for proper configuration of Kubebench Jobs.
- Kubernetes >= 1.8
- Ksonnet >= 0.11
- Kubeflow >= 0.3
- Required modules: argo, tf-operator
- For the quick-starter installation, Kubernetes nodes need to support NFS mounting
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Install Dependencies (Kubebench depends on an existing Kubeflow deployment. For details about using Kubeflow, please refer to Kubeflow documentation)
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Install Kubebench quick-starter package
In your Ksonnet app root, run the followings:
export KB_VERSION=master export KB_ENV=default curl https://raw.githubusercontent.com/kubeflow/kubebench/master/scripts/install_quickstarter.sh | bash
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View the Kubebench directory contents
The installer comes with a simple file server that allows you to view the contents of Kubebench directory through browser. You may find details of the file server service through:
kubectl get svc kubebench-nfs-file-server-svc -o wide
Alternatively, you can also access the deployed NFS service directly. You may find details of the nfs service through:
kubectl get svc kubebench-nfs-svc -o wide
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Create a kubebench-job
JOB_NAME="my-benchmark" ks pkg install kubeflow/kubebench@${KB_VERSION} ks generate kubebench-job ${JOB_NAME} ks apply ${KB_ENV} -c ${JOB_NAME}
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Track the status of your job
The Kubebench Job will be deployed as an Argo Workflow, you may go to Argo dashboard to track the progress of the job.
Alternatively, you can also use the followings in command line:
kubectl get -o yaml workflows ${JOB_NAME}
- Once the job is finished, you can find the results under the experiment directory in the NFS, the details of the particular experiment is located at
/experiments/<EXPERIMENT_UID>
. You may also see a csv file at/experiments/report.csv
, if you run multiple experiments, the aggregated results will be recorded here.
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Delete the kubebench-job
ks delete ${KB_ENV} -c ${JOB_NAME}
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Uninstall quickstarter
curl https://raw.githubusercontent.com/kubeflow/kubebench/master/scripts/uninstall_quickstarter.sh | bash
For additional information about motivation and design for this project please refer to kubebench_design.md
Ensure you run $ make verify
before submitting PRs.
// TODO post detailed development guide.