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diff --git a/benchmarks/README.md b/benchmarks/README.md deleted file mode 100644 index 975321c99..000000000 --- a/benchmarks/README.md +++ /dev/null @@ -1,181 +0,0 @@ -# Benchmark tools - -These scripts are tools for collecting performance data for Docker-based tests. - -## Setup - -The scripts assume the following: - -* There are two sets of machines: one where the scripts will be run - (controller) and one or more machines on which docker containers will be run - (environment). -* The controller machine must have bazel installed along with this source - code. You should be able to run a command like `bazel run :benchmarks -- - --list` -* Environment machines must have docker and the required runtimes installed. - More specifically, you should be able to run a command like: `docker run - --runtime=$RUNTIME your/image`. -* The controller has ssh private key which can be used to login to environment - machines and run docker commands without using `sudo`. This is not required - if running locally via the `run-local` command. -* The docker daemon on each of your environment machines is listening on - `unix:///var/run/docker.sock` (docker's default). - -For configuring the environment manually, consult the -[dockerd documentation][dockerd]. - -## Running benchmarks - -### Locally - -Run the following from the benchmarks directory: - -```bash -bazel run :benchmarks -- run-local startup - -... -method,metric,result -startup.empty,startup_time_ms,652.5772 -startup.node,startup_time_ms,1654.4042000000002 -startup.ruby,startup_time_ms,1429.835 -``` - -The above command ran the startup benchmark locally, which consists of three -benchmarks (empty, node, and ruby). Benchmark tools ran it on the default -runtime, runc. Running on another installed runtime, like say runsc, is as -simple as: - -```bash -bazel run :benchmarks -- run-local startup --runtime=runsc -``` - -There is help: ``bash bash bazel run :benchmarks -- --help bazel -run :benchmarks -- run-local --help` `` - -To list available benchmarks, use the `list` commmand: - -```bash -bazel run :benchmarks -- list -ls - -... -Benchmark: sysbench.cpu -Metrics: events_per_second - Run sysbench CPU test. Additional arguments can be provided for sysbench. - - :param max_prime: The maximum prime number to search. -``` - -You can choose benchmarks by name or regex like: - -```bash -bazel run :benchmarks -- run-local startup.node -... -metric,result -startup_time_ms,1671.7178000000001 - -``` - -or - -```bash -bazel run :benchmarks -- run-local s -... -method,metric,result -startup.empty,startup_time_ms,1792.8292 -startup.node,startup_time_ms,3113.5274 -startup.ruby,startup_time_ms,3025.2424 -sysbench.cpu,cpu_events_per_second,12661.47 -sysbench.memory,memory_ops_per_second,7228268.44 -sysbench.mutex,mutex_time,17.4835 -sysbench.mutex,mutex_latency,3496.7 -sysbench.mutex,mutex_deviation,0.04 -syscall.syscall,syscall_time_ns,2065.0 -``` - -You can run parameterized benchmarks, for example to run with different -runtimes: - -```bash -bazel run :benchmarks -- run-local --runtime=runc --runtime=runsc sysbench.cpu -``` - -Or with different parameters: - -```bash -bazel run :benchmarks -- run-local --max_prime=10 --max_prime=100 sysbench.cpu -``` - -### On Google Compute Engine (GCE) - -Benchmarks may be run on GCE in an automated way. The default project configured -for `gcloud` will be used. - -An additional parameter `installers` may be provided to ensure that the latest -runtime is installed from the workspace. See the files in `tools/installers` for -supported install targets. - -```bash -bazel run :benchmarks -- run-gcp --installers=head --runtime=runsc sysbench.cpu -``` - -When running on GCE, the scripts generate a per run SSH key, which is added to -your project. The key is set to expire in GCE after 60 minutes and is stored in -a temporary directory on the local machine running the scripts. - -## Writing benchmarks - -To write new benchmarks, you should familiarize yourself with the structure of -the repository. There are three key components. - -## Harness - -The harness makes use of the [docker py SDK][docker-py]. It is advisable that -you familiarize yourself with that API when making changes, specifically: - -* clients -* containers -* images - -In general, benchmarks need only interact with the `Machine` objects provided to -the benchmark function, which are the machines defined in the environment. These -objects allow the benchmark to define the relationships between different -containers, and parse the output. - -## Workloads - -The harness requires workloads to run. These are all available in the -`workloads` directory. - -In general, a workload consists of a Dockerfile to build it (while these are not -hermetic, in general they should be as fixed and isolated as possible), some -parsers for output if required, parser tests and sample data. Provided the test -is named after the workload package and contains a function named `sample`, this -variable will be used to automatically mock workload output when the `--mock` -flag is provided to the main tool. - -## Writing benchmarks - -Benchmarks define the tests themselves. All benchmarks have the following -function signature: - -```python -def my_func(output) -> float: - return float(output) - -@benchmark(metrics = my_func, machines = 1) -def my_benchmark(machine: machine.Machine, arg: str): - return "3.4432" -``` - -Each benchmark takes a variable amount of position arguments as -`harness.Machine` objects and some set of keyword arguments. It is recommended -that you accept arbitrary keyword arguments and pass them through when -constructing the container under test. - -To write a new benchmark, open a module in the `suites` directory and use the -above signature. You should add a descriptive doc string to describe what your -benchmark is and any test centric arguments. - -[dockerd]: https://docs.docker.com/engine/reference/commandline/dockerd/ -[docker-py]: https://docker-py.readthedocs.io/en/stable/ |