kibana-software-metrics

Utilities to gather software metrics from tools (SONAR, etc) and store them into ElasticSearch for later display using Kibana.

How to Run

You haver to make sure you have docker support in your machine - either native or with boot2docker or similar alternatives such as docker toolbox.

After you git clone this project, you need to:

• Build the docker image: docker build -rm -t=elasticsearch-kibana .
• Run the elasticsearch & kibana servers under docker: docker run -d -p 8000:8000 -p 9200:9200 elasticsearch-kibana
• If you are running boot2docker or similar ones under VirtualBox, make sure to define port forwards in VirtualBox for these 2 ports (8000 and 9200) in Settings/Network/Port Forwarding.
• Wait 2 or 3 minutes for the services to be running
• Populate elasticsearch with some data:
  • For Structure101 data: python s101_to_kibana.py -e "http://localhost:9200" -s "http://pgbuild:8280/s101g/tracker/size.plot"
    • NOTE: in order to run the script above, you need to make sure your python install has the requirements: pip install -r requirements.txt
• Visit http://localhost:8000
• Create an index in Kibana, to start: s101-*
• Create dashboards as you wish to visualize the data

Gotchas

If you run the script twice, the data will be logged twice. There is no checking for "but I have already submitted this data before". We plan to add command-line flags such as --afterDate and --upToDate so you can run multiple times and process data by "time slices". This could be used in a continuous build, for example.

Tip

If you are experimenting and want to toss all the data, the quick&dirty solution is to destroy the docker image running the servers and recreate it.

• docker ps
• docker stop
• docker rm

To kill all zombie docker images:

• docker rm -v $(docker ps -aq -f status=exited)
• docker rmi -f $(docker images -f "dangling=true" -q)
• docker run -v /var/run/docker.sock:/var/run/docker.sock -v /var/lib/docker:/var/lib/docker --rm martin/docker-cleanup-volumes

Thank you!

Special thanks to Softplan for sponsoring this project/experiment. In particular, Anderson Soffa for the support.