5.6 KiB
Benchmark tools
These scripts are tools for collecting performance data for Docker-based tests.
Setup
The scripts assume the following:
- You have a local machine with bazel installed.
- You have some machine(s) with docker installed. These machines will be refered to as the "Environment".
- Environment machines have the runtime(s) under test installed, such that you
can run docker with a command like:
docker run --runtime=$RUNTIME your/image
. - You are able to login to machines in the environment with the local machine
via ssh and the user for ssh can run docker commands without using
sudo
. - 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.
Environment
All benchmarks require a user defined yaml file describe the environment. These files are of the form:
machine1: local
machine2:
hostname: 100.100.100.100
username: username
key_path: ~/private_keyfile
key_password: passphrase
machine3:
hostname: 100.100.100.101
username: username
key_path: ~/private_keyfile
key_password: passphrase
The yaml file defines an environment with three machines named machine1
,
machine2
and machine3
. machine1
is the local machine, machine2
and
machine3
are remote machines. Both machine2
and machine3
should be
reachable by ssh
. For example, the command ssh -i ~/private_keyfile username@100.100.100.100
(using the passphrase passphrase
) should connect to
machine2
.
The above is an example only. Machines should be uniform, since they are treated as such by the tests. Machines must also be accessible to each other via their default routes. Furthermore, some benchmarks will meaningless if running on the local machine, such as density.
For remote machines, hostname
, key_path
, and username
are required and
others are optional. In addition key files must be generated
using the instrcutions below.
The above yaml file can be checked for correctness with the validate
command
in the top level perf.py script:
bazel run :benchmarks -- validate $PWD/examples/localhost.yaml
Running benchmarks
To list available benchmarks, use the list
commmand:
bazel run :benchmarks -- list
...
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.
To run benchmarks, use the run
command. For example, to run the sysbench
benchmark above:
bazel run :benchmarks -- run --env $PWD/examples/localhost.yaml sysbench.cpu
You can run parameterized benchmarks, for example to run with different runtimes:
bazel run :benchmarks -- run --env $PWD/examples/localhost.yaml --runtime=runc --runtime=runsc sysbench.cpu
Or with different parameters:
bazel run :benchmarks -- run --env $PWD/examples/localhost.yaml --max_prime=10 --max_prime=100 sysbench.cpu
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. 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
parses 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:
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.
Generating SSH Keys
The scripts only support RSA Keys, and ssh library used in paramiko. Paramiko only supports RSA keys that look like the following (PEM format):
$ cat /path/to/ssh/key
-----BEGIN RSA PRIVATE KEY-----
...private key text...
-----END RSA PRIVATE KEY-----
To generate ssh keys in PEM format, use the -t rsa -m PEM -b 4096
.
option.