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Pbench

A Benchmarking and Performance Analysis Framework

The code base includes three sub-systems. The first is the collection agent, pbench-agent, responsible for providing commands for running benchmarks across one or more systems, while properly collecting the configuration data for those systems, and specified telemetry or data from various tools (sar, vmstat, perf, etc.).

The second sub-system is the pbench-server, which is responsible for archiving result tar balls, indexing them, and unpacking them for display.

The third sub-system is the web-server JS and CSS files, used to display various graphs and results, and any other content generated by the pbench-agent during benchmark and tool post-processing steps.

The pbench Dashboard code lives in its own repository.

How is it installed?

Instructions on installing pbench-agent, can be found in the Pbench Agent Getting Started Guide.

For Fedora, CentOS, and RHEL users, we have made available COPR builds for the pbench-agent, pbench-server, pbench-web-server, and some benchmark and tool packages.

Install the pbench-web-server package on the machine from where you want to run the pbench-agent workloads, allowing you to view the graphs before sending the results to a server, or even if there is no server configured to send results.

You might want to consider browsing through the rest of the documentation.

How do I use pbench?

Refer to the Pbench Agent Getting Started Guide.

TL;DR? See "TL;DR - How to set up the pbench-agent and run a benchmark " in the main documentation for a super quick set of introductory steps.

Where is the source kept?

The latest source code is at https://github.com/distributed-system-analysis/pbench.

The pbench dashboard code is maintained separately at https://github.com/distributed-system-analysis/pbench-dashboard.

Is there a mailing list for discussions?

Yes, we use Google Groups

How do I report and issue?

Please use GitHub's issues.

Is there a place to track current and future work items?

Yes, we are using GitHub Projects. Please find projects covering the Agent, Server, Dashboardhttps://github.com/distributed-system-analysis/pbench/projects/1, and a project that is named the same as the current milestone.

How can I contribute?

Below are some simple steps for setting up a development environment for working with the Pbench code base. For more detailed instructions on the workflow and process of contributing code to Pbench, refer to the Guidelines for Contributing.

Getting the Code

$ git clone https://github.com/distributed-system-analysis/pbench
$ cd pbench

Running the Unit Tests

Install tox properly in your environment (Fedora/CentOS/RHEL):

$ sudo dnf install -y perl-JSON python3-pip python3-tox

Once tox is installed you can run the unit tests against different versions of python using the python environment short-hands:

  • tox -e py36 -- run all tests in a Python 3.6 environment (our default)
  • tox -e py39 -- run all tests in a Python 3.9 environment
  • tox -e py310 -- run all tests in a Python 3.10 environment
  • tox -e pypy3 -- run all tests in a PyPy 3 environment
  • tox -e pypy3.8 -- run all tests in a PyPy 3.8 environment

See https://tox.wiki/en/latest/example/basic.html#a-simple-tox-ini-default-environments.

Each time tests are run, the linting steps (black and flake8) are run first.

You can provide arguments to the tox invocation to request sub-sets of the available tests be run.

For example, if you want to just run the agent or server tests, you'd invoke tox as follows:

  • tox -- agent -- runs only the agent tests
  • tox -- server -- runs only the server tests

Each of the "agent" and "server" tests can be further subsetted as follows:

  • agent

    • python -- runs the python tests (via pytest)
    • legacy -- runs all the legacy tests
    • datalog -- runs only the legacy tool data-log tests, agent/tool-scripts/datalog/unittests
    • postprocess -- runs only the legacy tool/bench-scripts post-processing tests, agent/tool-scripts/postprocess/unittests
    • tool-scripts -- runs only the legacy tool-scripts tests, agent/tool-scripts/unittests
    • util-scripts -- runs only the legacy util-scripts tests, agent/util-scripts/unittests
    • bench-scripts -- runs only the legacy bench-scripts tests, agent/bench-scripts/unittests
  • server

    • python -- runs the python tests (via python)
    • legacy -- runs the legacy tests

For example:

  • tox -- agent legacy -- run agent legacy tests
  • tox -- server legacy -- run server legacy tests
  • tox -- server python -- run server python tests (via pytest)

For any of the test sub-sets on either the agent or server sides of the tree, one can pass additional arguments to the specific sub-system test runner. This allows one to request a specific test, or set of tests, or command line parameters to modify the test behavior:

  • tox -- agent bench-scripts test-CL -- run bench-scripts' test-CL
  • tox -- server legacy test-28 test-32 -- run server legacy tests 28 & 32
  • tox -- server python -v -- run server python tests verbosely

For the agent/bench-scripts tests, one can run entire sub-sets of tests using a sub-directory name found in agent/bench-scripts/tests. For example:

  • tox -- agent bench-scripts pbench-fio
  • tox -- agent bench-scripts pbench-uperf pbench-linpack

The first runs all the pbench-fio tests, while the second runs all the pbench-uperf and pbench-linpack tests.

Finally, see the jenkins/Pipeline.gy file for how the unit tests are run in our CI jobs.

Python formatting

This project uses the flake8 method of code style enforcement, linting, and checking.

All python code contributed to pbench must match the style requirements. These requirements are enforced by the pre-commit hook using the black Python code formatter and the isort Python import sorter.

Use pre-commit to set automatic commit requirements

This project makes use of pre-commit to do automatic lint and style checking on every commit containing Python files.

To install the pre-commit hook, run the executable from your Python 3 framework while in your current pbench git checkout:

$ cd ~/pbench
$ pip3 install pre-commit
$ pre-commit install --install-hooks

Once installed, all commits will run the test hooks. If your changes fail any of the tests, the commit will be rejected.

Pbench Release Tag Scheme (GitHub)

We employ a simple major, minor, release, build (optional) scheme for tagging starting with the v0.70.0 release (v<Major>.<Minor>.<Release>[-<Build>]). Prior to the v0.70.0 release, the scheme used was mostly v<Major>.<Minor>, where we only had minor releases (Major = 0).

The practice of using -agent or -server is also ending with the v0.70.0 release.

Container Image Tags

This same GitHub "tag" scheme is used with tags applied to container images we build, with the following exceptions for tag names:

  • latest - always points to the "latest" container image pushed to a repository

  • v<Major>-latest - always points to the "latest" Major released image

  • v<Major>.<Minor>-latest - always points to the "latest" release for Major.Minor released images

  • <SHA1 git hash> (9 characters) - commit hash of the checked out code

References to Container Image Repositories

The operation of our functional tests, the Pbench Server "in-a-can" used in the functional tests, and other verification and testing environments use container images from public repositories and non-public ones. The CI jobs obtain references to those repositories using Jenkins credentials. When a developer runs those same jobs locally, you can create two files with the appropriate contents locally:

  • ${HOME}/.config/pbench/ci_registry.name
  • ${HOME}/.config/pbench/public_registry.name

If those files are not provided local execution will report an error when those values are missing.