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توضیحات

Benchmark Runner Tool

ویژگی	مقدار
سیستم عامل	-
نام فایل	benchmark-runner-1.0.99
نام	benchmark-runner
نسخه کتابخانه	1.0.99
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Red Hat
ایمیل نویسنده	ebattat@redhat.com
آدرس صفحه اصلی	https://github.com/redhat-performance/benchmark-runner
آدرس اینترنتی	https://pypi.org/project/benchmark-runner/
مجوز	Apache License 2.0

<div align="center"> <img src="https://github.com/redhat-performance/benchmark-runner/blob/main/media/benchmark_runner.png"><br> </div> ----------------- # Benchmark-Runner: Running benchmarks [![Actions Status](https://github.com/redhat-performance/benchmark-runner/workflows/CI/badge.svg)](https://github.com/redhat-performance/benchmark-runner/actions) [![PyPI Latest Release](https://img.shields.io/pypi/v/benchmark-runner.svg)](https://pypi.org/project/benchmark-runner/) [![Container Repository on Quay](https://quay.io/repository/projectquay/quay/status "Container Repository on Quay")](https://quay.io/repository/ebattat/benchmark-runner?tab=tags) [![Coverage Status](https://coveralls.io/repos/github/redhat-performance/benchmark-runner/badge.svg?branch=main)](https://coveralls.io/github/redhat-performance/benchmark-runner?branch=main&kill_cache=1) [![Documentation Status](https://readthedocs.org/projects/benchmark-runner/badge/?version=latest)](https://benchmark-runner.readthedocs.io/en/latest/?badge=latest) [![python](https://img.shields.io/pypi/pyversions/benchmark-runner.svg?color=%2334D058)](https://pypi.org/project/benchmark-runner) [![License](https://img.shields.io/pypi/l/benchmark-runner.svg)](https://github.com/redhat-performance/benchmark-runner/blob/main/LICENSE) ## What is it? **benchmark-runner** is a containerized Python lightweight and flexible framework for running benchmark workloads on Kubernetes/OpenShift runtype kinds Pod, kata and VM. This framework support the following embedded workloads: * [hammerdb](https://hammerdb.com/): running hammerdb workload on the following databases: MSSQL, Mariadb, Postgresql in Pod, Kata or VM with [Configuration](benchmark_runner/common/template_operations/templates/hammerdb) * [stressng](https://wiki.ubuntu.com/Kernel/Reference/stress-ng): running stressng workload in Pod, Kata or VM [Configuration](benchmark_runner/common/template_operations/templates/stressng) * [uperf](http://uperf.org/): running uperf workload in Pod, Kata or VM with [Configuration](benchmark_runner/common/template_operations/templates/uperf) * [vdbench](https://wiki.lustre.org/VDBench/): running vdbench workload in Pod, Kata or VM with [Configuration](benchmark_runner/common/template_operations/templates/vdbench) * [bootstorm](https://en.wiktionary.org/wiki/boot_storm): calculate VMs boot load time [Configuration](benchmark_runner/common/template_operations/templates/bootstorm) ** For hammerdb mssql must run once [permission](https://github.com/redhat-performance/benchmark-runner/blob/main/benchmark_runner/common/ocp_resources/custom/template/02_mssql_patch_template.sh) Benchmark-runner grafana dashboard example: ![](media/grafana.png) Reference: * The benchmark-runner package is located in [PyPi](https://pypi.org/project/benchmark-runner) * The benchmark-runner container image is located in [Quay.io](https://quay.io/repository/ebattat/benchmark-runner) ## Documentation Documentation is available at [benchmark-runner.readthedocs.io](https://benchmark-runner.readthedocs.io/en/latest/) ![](media/docker2.png) _**Table of Contents**_  - [Benchmark-Runner](#benchmark-runner) - [Documentation](#documentation) - [Run workload using Podman or Docker](#run-workload-using-podman-or-docker) - [Run workload in Pod using Kubernetes or OpenShift](#run-workload-in-pod-using-kubernetes-or-openshift) - [Grafana dashboards](#grafana-dashboards) - [Inspect Prometheus Metrics](#inspect-prometheus-metrics) - [How to develop in benchmark-runner](#how-to-develop-in-benchmark-runner)  ## Run workload using Podman or Docker The following options may be passed via command line flags or set in the environment: **mandatory:** WORKLOAD=$WORKLOAD **mandatory:** KUBEADMIN_PASSWORD=$KUBEADMIN_PASSWORD **mandatory:** $KUBECONFIG [ kubeconfig file path] Choose one from the following list: `['stressng_pod', 'stressng_vm', 'stressng_kata', 'uperf_pod', 'uperf_vm', 'uperf_kata', 'hammerdb_pod_mariadb', 'hammerdb_vm_mariadb', 'hammerdb_kata_mariadb', 'hammerdb_pod_mariadb_lso', 'hammerdb_vm_mariadb_lso', 'hammerdb_kata_mariadb_lso', 'hammerdb_pod_postgres', 'hammerdb_vm_postgres', 'hammerdb_kata_postgres', 'hammerdb_pod_postgres_lso', 'hammerdb_vm_postgres_lso', 'hammerdb_kata_postgres_lso', 'hammerdb_pod_mssql', 'hammerdb_vm_mssql', 'hammerdb_kata_mssql', 'hammerdb_pod_mssql_lso', 'hammerdb_vm_mssql_lso', 'hammerdb_kata_mssql_lso', 'vdbench_pod', 'vdbench_kata', 'vdbench_vm', 'clusterbuster', 'bootstorm_vm']` ** clusterbuster workloads: cpusoaker, files, fio, uperf. for more details [see](https://github.com/RobertKrawitz/OpenShift4-tools) **auto:** NAMESPACE=benchmark-operator [ The default namespace is benchmark-operator ] **auto:** ODF_PVC=True [ True=ODF PVC storage, False=Ephemeral storage, default True ] **auto:** EXTRACT_PROMETHEUS_SNAPSHOT=True [ True=extract Prometheus snapshot into artifacts, false=don't, default True ] **auto:** SYSTEM_METRICS=False [ True=collect metric, False=not collect metrics, default False ] **auto:** RUNNER_PATH=/tmp [ The default work space is /tmp ] **optional:** PIN_NODE_BENCHMARK_OPERATOR=$PIN_NODE_BENCHMARK_OPERATOR [node selector for benchmark operator pod] **optional:** PIN_NODE1=$PIN_NODE1 [node1 selector for running the workload] **optional:** PIN_NODE2=$PIN_NODE2 [node2 selector for running the workload, i.e. uperf server and client, hammerdb database and workload] **optional:** ELASTICSEARCH=$ELASTICSEARCH [ elasticsearch service name] **optional:** ELASTICSEARCH_PORT=$ELASTICSEARCH_PORT **optional:** CLUSTER=$CLUSTER [ set CLUSTER='kubernetes' to run workload on a kubernetes cluster, default 'openshift' ] **optional:scale** SCALE=$SCALE [For Vdbench/Bootstorm: Scale in each node] **optional:scale** SCALE_NODES=$SCALE_NODES [For Vdbench/Bootstorm: Scale's node] **optional:scale** REDIS=$REDIS [For Vdbench only: redis for scale synchronization] **optional:** LSO_DISK_ID=$LSO_DISK_ID [LSO_DISK_ID='scsi-<replace_this_with_your_actual_disk_id>' For using Local Storage Operator in hammerdb] **optional:** WORKER_DISK_IDS=$WORKER_DISK_IDS [WORKER_DISK_IDS For ODF/LSO workloads hammerdb/vdbench] For example: ```sh podman run --rm --workload=$WORKLOAD --kubeadmin-password=$KUBEADMIN_PASSWORD --pin-node-benchmark-operator=$PIN_NODE_BENCHMARK_OPERATOR --pin-node1=$PIN_NODE1 --pin-node2=$PIN_NODE2 --elasticsearch=$ELASTICSEARCH --elasticsearch-port=$ELASTICSEARCH_PORT -v $KUBECONFIG:/root/.kube/config --privileged quay.io/ebattat/benchmark-runner:latest ``` or ```sh podman run --rm -e WORKLOAD=$WORKLOAD -e KUBEADMIN_PASSWORD=$KUBEADMIN_PASSWORD -e PIN_NODE_BENCHMARK_OPERATOR=$PIN_NODE_BENCHMARK_OPERATOR -e PIN_NODE1=$PIN_NODE1 -e PIN_NODE2=$PIN_NODE2 -e ELASTICSEARCH=$ELASTICSEARCH -e ELASTICSEARCH_PORT=$ELASTICSEARCH_PORT -e log_level=INFO -v $KUBECONFIG:/root/.kube/config --privileged quay.io/ebattat/benchmark-runner:latest ``` SAVE RUN ARTIFACTS LOCAL: 1. add `-e SAVE_ARTIFACTS_LOCAL='True'` or `--save-artifacts-local=true` 2. add `-v /tmp:/tmp` 3. git clone -b v1.0.2 https://github.com/cloud-bulldozer/benchmark-operator /tmp/benchmark-operator ### Run vdbench workload in Pod using OpenShift ![](media/benchmark-runner-demo.gif) ### Run vdbench workload in Pod using Kubernetes ![](media/benchmark-runner-k8s-demo.gif) ## Run workload in Pod using Kubernetes or OpenShift [TBD] ## Grafana dashboards There are 2 grafana dashboards templates: 1. [grafana/func/benchmark-runner-ci-status-report.json](grafana/func/benchmark-runner-ci-status-report.json) ![](media/benchmark-runner-ci-status.png) 2. [grafana/func/benchmark-runner-report.json](grafana/func/benchmark-runner-report.json) ![](media/benchmark-runner-report.png) ** After importing json in grafana, you need to configure elasticsearch data source. (for more details: see [HOW_TO.md](HOW_TO.md)) ## Inspect Prometheus Metrics The CI jobs store snapshots of the Prometheus database for each run as part of the artifacts. Within the artifact directory is a Prometheus snapshot directory named: ``` promdb-YYYY_MM_DDTHH_mm_ss+0000_YYYY_MM_DDTHH_mm_ss+0000.tar ``` The timestamps are for the start and end of the metrics capture; they are stored in UTC time (`+0000`). It is possible to run containerized Prometheus on it to inspect the metrics. *Note that Prometheus requires write access to its database, so it will actually write to the snapshot.* So for example if you have downloaded artifacts for a run named `hammerdb-vm-mariadb-2022-01-04-08-21-23` and the Prometheus snapshot within is named `promdb_2022_01_04T08_21_52+0000_2022_01_04T08_45_47+0000`, you could run as follows: ``` $ local_prometheus_snapshot=/hammerdb-vm-mariadb-2022-01-04-08-21-23/promdb_2022_01_04T08_21_52+0000_2022_01_04T08_45_47+0000 $ chmod -R g-s,a+rw "$local_prometheus_snapshot" $ sudo podman run --rm -p 9090:9090 -uroot -v "$local_prometheus_snapshot:/prometheus" --privileged prom/prometheus --config.file=/etc/prometheus/prometheus.yml --storage.tsdb.path=/prometheus --storage.tsdb.retention.time=100000d --storage.tsdb.retention.size=1000PB ``` and point your browser at port 9090 on your local system, you can run queries against it, e.g. ``` sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) > 0 ``` It is important to use the `--storage.tsdb.retention.time` option to Prometheus, as otherwise Prometheus may discard the data in the snapshot. And note that you must set the time bounds on the Prometheus query to fit the start and end times as recorded in the name of the promdb snapshot. ## How to develop in benchmark-runner see [HOW_TO.md](HOW_TO.md)

نیازمندی

مقدار	نام
==21.4.0	attrs
==4.0.0	azure
==1.26.1	boto3
==1.29.1	botocore
==39.0.1	cryptography
==7.16.1	elasticsearch
==7.4.0	elasticsearch-dsl
==3.0.3	jinja2
==0.17.0	myst-parser
==1.0.17	openshift-client
==0.5.1	prometheus-api-client
-	pandas
==3.0.0	paramiko
==1.55	PyGitHub
==6.0	PyYAML
==4.5.0	sphinx
==1.0.0	sphinx-rtd-theme
==8.0.1	tenacity
==2.12.1	typeguard
==3.7.4.3	typing

نحوه نصب

نصب پکیج whl benchmark-runner-1.0.99:

pip install benchmark-runner-1.0.99.whl

نصب پکیج tar.gz benchmark-runner-1.0.99:

pip install benchmark-runner-1.0.99.tar.gz