The files within this directory can be used to generate a "metrics report" for Kata Containers.
The primary workflow consists of two stages:
- Run the provided report metrics data gathering scripts on the system(s) you wish to analyze.
- Run the provided report generation script to analyze the data and generate a report file.
Data gathering is provided by the grabdata.sh script. When run, this script
executes a set of tests from the tests/metrics directory. The JSON results files
will be placed into the tests/metrics/results directory.
Once the results are generated, create a suitably named subdirectory of
tests/metrics/results, and move the JSON files into it.
Repeat this process if you want to compare multiple sets of results. Note, the
report generation scripts process all subdirectories of tests/metrics/results when
generating the report.
Note: By default, the
grabdata.shscript tries to launch some moderately large containers (i.e. 8Gbyte RAM) and may fail to produce some results on a memory constrained system.
You can restrict the subset of tests run by grabdata.sh via its commandline parameters:
| Option | Description |
|---|---|
| -a | Run all tests (default) |
| -d | Run the density tests |
| -h | Print this help |
| -s | Run the storage tests |
| -t | Run the time tests |
Report generation is provided by the makereport.sh script. By default this script
processes all subdirectories of the tests/metrics/results directory to generate the report.
To run in the default mode, execute the following:
$ ./makereport.shThe report generation tool uses Rmarkdown,
R and Pandoc to produce
a PDF report. To avoid the need for all users to set up a working environment
with all the necessary tooling, the makereport.sh script utilises a Dockerfile with
the environment pre-defined in order to produce the report. Thus, you need to
have Docker installed on your system in order to run the report generation.
The resulting metrics_report.pdf is generated into the output subdirectory of the report
directory.
To aid in script development and debugging, the makereport.sh script offers a debug
facility via the -d command line option. Using this option will place you into a bash
shell within the running Dockerfile image used to generate the report, whilst also
mapping your host side R scripts from the report_dockerfile subdirectory into the
container, thus facilitating a "live" edit/reload/run development cycle.
From there you can examine the Docker image environment, and execute the generation scripts.
E.g., to test the scaling.R script, you can execute:
$ makereport.sh -d
# R
> source('/inputdir/Env.R')
> source('/scripts/lifecycle-time.R')You can then edit the report_dockerfile/lifecycle-time.R file on the host, and re-run
the source('/scripts/lifecycle-time.R') command inside the still running R container
to re-execute the newly edited script.