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2019-10-16 16:56:13 -06:00

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* [cloud-native-setup metrics report generator](#cloud-native-setup-metrics-report-generator)
* [Data gathering](#data-gathering)
* [Report generation](#report-generation)
* [Debugging and development](#debugging-and-development)
# cloud-native-setup metrics report generator
The files within this directory can be used to generate a 'metrics report'
for Kubernetes.
The primary workflow consists of two stages:
1) Run the provided report metrics data gathering scripts on the system(s) you wish
to analyze.
2) Run the provided report generation script to analyze the data and generate a
report file.
## Data gathering
Data gathering is provided by the `grabdata.sh` script. When run, this script
executes a set of tests from the `cloud-native-setup/metrics` directory. The JSON results files
will be placed into the `cloud-native-setup/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 subfolders of `tests/metrics/results` when
generating the report.
You can restrict the subset of tests run by `grabdata.sh` via its commandline parameters:
| Option | Description |
| ------ | ----------- |
| -a | Run all tests (default) |
| -s | Run the scaling tests |
| -h | Print this help |
## Report generation
Report generation is provided by the `makereport.sh` script. By default this script
processes all subdirectories of the `cloud-native-setup/metrics/results` directory to generate the report.
To run in the default mode, execute the following:
```sh
$ ./makereport.sh
```
The report generation tool uses [Rmarkdown](https://github.com/rstudio/rmarkdown),
[R](https://www.r-project.org/about.html) and [pandoc](https://pandoc.org/) 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` subdir of the `report`
directory.
## Debugging and development
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 `tidy_scaling.R` script, you can execute:
```bash
$ ./makereport.sh -d
...
Successfully built eea7d6ac6fa7
Successfully tagged metrics-report:latest
root@<hostname>:/# R
> source('/inputdir/Env.R')
> source('/scripts/tidy_scaling.R')
## Edit script on host, and re-load/run...
> source('/scripts/tidy_scaling.R')
```