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  Elasticsearch Kibana installation notes
     
  Add Date : 2017-08-31      
         
       
         
  Kibana is a query and analysis for ElasticSearch dashboard, original presentation on Kibana so. It is noteworthy that the analysis Kibana placed in front of the query, it is probably Kibana distinguished from other clients place.

About Kibana introduction and documentation please refer to here.

In addition I used the head and bigdesk, of course, they are almost a different location. head for data browsing and querying is quite easy to use profile, bigdesk for ElasticSearch cluster status monitoring, Kibana it? With the search function, but it should be the most attractive and fast hardware performance capabilities icon bar. At least until further I think so.

installation

This thing almost no installation, elasticsearch official web side - Download> kibana in -> overview.

Find any web server (apache, nginx, etc.) to throw into (not open directly fs), of course, as a persistent Java Cock I chose Tomcat.

Before turning on the one thing we need to do, open the directory where config.js kibana files, edit "elasticsearch" field points to your es uri.

function (Settings) {
  
 
  / ** @scratch /configuration/config.js/2
  *
  * === Parameters
  * /
  return new Settings ({
 
    
    elasticsearch: "http://10.128.170.245:9200",
    ....

Use

Hundreds of times to open http: // localhost: 8080 / kibana, that part of the front is almost a "hello world" outside Java Cock knock most of the characters of the bar.

As interface, seemingly only need to focus on the lower left corner of the right panel: Sample Dashboard, Unconfigured Dashboard, Blank Dashboard. Sample Dashboard trial is a basic interface, it may go in and see kibana point chart can be made more beautiful.

3. Blank Dashboard things from the start, click into the open after a blank Dashboard.

 

Save / Open: start with the simplest two functions. In the upper right corner of the page a few pictures instantly recognize open, save button, they are doing, how to do I do not say you know.
Share: Save button next to the button that is to share, how to do it, you do not need to say any more.
Add the line: Kibana layout is the layout of the ranks, you can currently see only a Query and Filter. Regardless first guy and maybe, take a look at a lower right corner of the ADD A ROW, the decisive click. then. . . We say to 5.
Dashboard to give a name: Click after the eye should be the Title Style and two, that point of view again found it to be Dashboard Settings --- "General. Before you begin adding ah row Dashboard want to give it a name, then save or the like.
Add the line: If you save a point on once again points Add A Row, otherwise click directly on the tab Row. This time really is to add the line, the right of the input box to name, create row and then click save. You have a life first Kibana Row. . .
Add Panel: Add panel. Row directly on point with the text of the button or move the mouse appears to the left menu contraction, configuration, adding the panel. Click after the emergence of the Add dialog box, where the election table, span Select 12 (when is the width, maximum 12) and then directly save.
Query: This assumes that you have to have the ES data, and casually enter the keyword "your words" at the top Query column, you can see the table to the query results. Filter can be so similar play.
Add Type Filter: then rolled bottom of the page, click Add a new Row, and by up button placed on top of it (convenient only). Add Panel, select the term, the name Type, field _type (default) click save. Then a list of all the current ES type, click on any one you will find more than one filter in the Filter criteria.
Copy the pie chart: Sample Dashboard then draw a pie chart, still add Panel, select the term, select the style pie, then save it. Become.

to sum up

In fact, nothing good summary, Kibana provides a rich form of expression, based on the description of each chart like to play up slowly. I hope I have the opportunity to gradually introduce Cadogan for each chart.

ELK is a classic fit: ElasticSearch, LogStash, Kibana. E solves the storage and retrieval (staging Kazakhstan, such as 30d), L for log collection, K vividly shows trends in data, and provides query capabilities.
     
         
       
         
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