Will >> Will's blog

purpose: Will Kahn-Greene's blog of Miro, PyBlosxom, Python, GNU/Linux, random content, PyBlosxom, Miro, and other projects mixed in there ad hoc, half-baked, and with a twist of lemon

Wed, 14 May 2014

Fiddling with Kibana

I just kicked off a script that's going to take around 4 hours to complete mostly because the API it's running against doesn't want me doing more than 60 requests/minute. Given I've got like 13k requests to do, that takes a while.

I'm (ab)using Elasticsearch to store the data from my script so that I can analyze it more easily--terms facet is pretty handy here.

Given that I've got some free time now, I spent 5 minutes setting up Kibana.

Steps:

  1. download the tarball
  2. untar it into a directory
  3. edit kibana-3.0.1/config.js to point to my local Elasticsearch cluster (the defaults were fine, so I could have skipped this step)
  4. cd kibana-3.0.1/ and run python -m SimpleHTTPServer 5000 (I'm using a Python-y thing here, but you can use any web-server)
  5. point my browser to http://localhost:5000

Now I'm using Kibana.

Now that I've got it working, first thing I do is click on the cog in the upper right hand corner, click on the Index tab and change the index to the one I wanted to look at. Now I'm looking at the data my script is producing.

The Kibana site says Kibana excels at timestamped data, but I think it's helpful for what I'm looking at now despite it not being timestamped. I get immediate terms facets on the fields for the doc type I'm looking at. I can run queries, pick specific columns, reorder, do graphs, save my dashboard to look at later, etc.

If you're doing Elasticsearch stuff, it's worth looking at if only to give you another tool to look at data with.

Want to comment? Send an email to willkg at bluesock dot org. Include the url for the blog entry in your comment so I have some context as to what you're talking about.