Bucketbench is a simple framework for running defined sequences of lifecycle container operations against three different container engines today: the full Docker engine, OCI’s runc, and containerd.
Given a bucket is a physical type of container, the name is my attempt to get away from calling it “dockerbench,” given it runs against other container engines as well. All attempts to come up with a more interesting name failed before initial release. Suggestions welcome!
This project came about via some performance comparison work happening in the OpenWhisk serverless project. Developers in that project had a python script for doing similar comparisons, but agreed we should extend it to a more general framework which could be easily be extended for other lifecycle operation sequences, as the python script was hardcoded to a specific set of operations.
bucketbench to drive container operations against a specific
container runtime requires a configuration file written in a specific YAML
The current driver implementations each support a small set
of lifecycle operations (defined as an interface in
any benchmark definition can mix and match any of those operations within
reason. (Obviously operations must be ordered in a way supported by container
lifecycle–for example, you can’t do
stop prior to
Specific command usage for the
bucketbench program is as follows:
The YAML file provided via the --benchmark flag will determine which lifecycle container commands to run against which container runtimes, specifying iterations and number of concurrent threads. Results will be displayed afterwards. Usage: bucketbench run [flags] Flags: -b, --benchmark string YAML file with benchmark definition -h, --help help for run -o, --overhead Output daemon overhead -s, --skip-limit Skip 'limit' benchmark run -t, --trace Enable per-container tracing during benchmark runs Global Flags: --log-level string set the logging level (info,warn,err,debug) (default "warn")
A common invocation for running the “basic” example benchmark might look like:
$ sudo ./bucketbench --log-level=debug run -b examples/basic.yaml
Let’s look at the input YAML file format and define the components. Here’s the basic.yaml example:
name: Basic image: alpine:latest command: date rootfs: /home/estesp/containers/alpine detached: true drivers: - type: Docker threads: 5 iterations: 15 - type: Runc threads: 5 iterations: 50 commands: - run - stop - remove
The initial section sets up a name and a few key pieces of information required
for each engine to know what to run:
- name: Give the benchmark a name. This will be used in output and logs.
- image: Choose an image reference to be used by the image-based engine runtimes (containerd 1.0 and Docker). This can be any image reference accepted by the
docker pull command.
bucketbench will handle reconciling this reference to the format used by containerd 1.0 (e.g.
- command: [Optional] Specify an override for the image’s default command that will be used for the image-based engine runtimes.
- rootfs: For the
ctr (legacy containerd/0.2.x) drivers, you will need to provide an exploded rootfs and an OCI
config.json since neither of those engines support image/registry interactions.
- detached: Run the containers in detached/background mode.
The next two sections of the YAML provide 1) the configuration of which drivers to execute the benchmark against, and 2) which lifecycle commands to run against each engine.
Each driver has the following settings:
- type: One of the four implemented drivers:
- clientpath: [Optional] Path to the binary for client executable based drivers. In the case of containerd 1.0 and the CRI driver, this will be the unique UNIX socket path of the gRPC server. For client binary-based drivers, the driver will default to the standard binary name found in the current
- threads: Integer number of concurrent threads to run. The
bucketbench method is to execute 1..n runs, where
n is the number of threads and each run adds another concurrent thread. Run 1 only has one thread and Run N will have
n concurrent threads.
- iterations: Number of containers to create in each thread and execute the listed commands against.
DockerCLI support log driver configuration to measure overhead between different implementations. Allowed values can be found here.
- logOpts: Logger driver configuration, only used with
logDriver option. See
overhead-logdriver.yaml for examples.
- streamStats: Allows to explore the overhead of
stats queries for different drivers. Note that
docker driver supports streaming natively while
containerd supports direct API calls only, so you might want to send multiple queries to emulate streaming behavior (see statsIntervalSec)
- statsIntervalSec: Defines an interval in seconds between
stats queries to emulate streaming behaviour for
- cgroupPath: Path to a cgroup directory (for example:
Finally, the YAML input needs to have a list of container lifecycle commands. The following commands are accepted as input:
- run: (aliases: start) create and start a container.
- pause: pause a running container
- unpause: (aliases: resume) resume a paused container
- stop: (aliases: kill) stop/kill the running container processes
- remove: (aliases: erase,delete) remove/delete a container instance
- metrics: (aliases: stats) query container daemon stats. Note: if
streamStats = true, each metrics command will spawn separate goroutine and will stream metrics untill end of iteration.
- wait: wait for container stop
bucketbench is not handling any formal state validation on the list
of commands. It is currently up to the user to provide a valid/sane ordered
list of container lifecycle commands. The container runtimes will error out on
incorrect command states (e.g.
After the benchmark runs are complete,
bucketbench currently provides basic
output to show the overall rate (iterations of the operations/second) for each
of the thread counts:
Iter/Thd 1 thrd 2 thrds 3 thrds 4 thrds 5 thrds 6 thrds 7 thrds 8 thrds 9 thrds 10 thrds Limit 1000 1171.24 1957.17 2101.13 2067.83 1827.92 1637.32 1257.57 1582.36 1306.08 1699.56 Basic:Docker 15 1.40 2.21 2.81 Basic:Runc 50 8.38 15.85 23.00
If you add
bucketbench will measure container daemon cpu
and memory consumption. The output will look like:
Bench / driver / threads Min Max Avg Min Max Avg Mem % CPU x OverheadBench:Containerd:1 40 MB 42 MB 41 MB 0.00 % 6.00 % 0.32 % OverheadBench:Containerd:2 44 MB 46 MB 44 MB 0.00 % 10.00 % 0.57 % OverheadBench:Containerd:3 46 MB 46 MB 46 MB 0.00 % 14.00 % 0.73 % OverheadBench:Containerd:4 46 MB 47 MB 46 MB 0.00 % 20.00 % 0.94 % OverheadBench:Docker:1 64 MB 66 MB 64 MB 0.00 % 10.00 % 0.58 % +56.10% +1.84x OverheadBench:Docker:2 69 MB 73 MB 70 MB 0.00 % 20.00 % 1.29 % +59.09% +2.26x OverheadBench:Docker:3 73 MB 73 MB 73 MB 0.00 % 32.00 % 1.97 % +58.70% +2.70x OverheadBench:Docker:4 73 MB 73 MB 73 MB 0.00 % 27.99 % 2.67 % +58.70% +2.85x
More detailed information is collected during the runs and a future PR to
bucketbench will provide the raw performance data in a consumable format for
Containerd, or the legacy
you must use
sudo because of the requirements that those tools have for root
access. This tool does not manage the two daemon-based engines (containerd and
dockerd), and will fail if they are not up and running when the benchmark runs
The tool will start a significant number of containers against these daemons, but attempts to fully cleanup after running each iteration.
bucketbench tool is most likely only valuable on amd64/linux, as
runc are delivered today as binaries for those platforms.
It will most likely build for other platforms, and if run against a tool like
Docker for Mac, would probably work against the Docker engine, but not
All the necessary dependencies are vendored into the
bucketbench source tree.
bucketbench only requires that you have a valid Golang build/runtime
environment. Any recent release of Go will work, but it is currently building
with Go 1.9.x and 1.10. A simple
Makefile is available to simplify building
bucketbench as a dynamic or static binary.
make binary will build the
bucketbench binary and
make install will place it in your
should also be able to simply
go install github.com/estesp/bucketbench.
bucketbench offers cgroups
as more precise way of measuring resource usage. However some additional setup
is required before running tests.
bucketbench uses existing environment, so
a control group should be created for each container runtime and daemons should be
added to a corresponding cgroup (if systemd is used, cgroups are already created).
For each container runtime a path to cgroup should be passed via
Caveats and limitations
- Overhead benchmark implementation only covers
- Stats streaming are only supported by
- Cgroups are Linux only
- The benchmark uses process name matching to find relevant processes; you must
keep the expected process names (
docker-containerd-shimfor Docker and
containerd-shimfor containerd) and not run additional processes with the same names.
- Decide what to do with the
-traceflag, which was only useful with a private build of
runcwhich generated Go pprof traces. Possibly submit trace support to upstream runc.