Elasticsearch Kibana Installation notes
Kibana is a dashboard used for ElasticSearch analysis and query. It is worth noting that Kibana puts the analysis before the query, which is probably distinguished by other clients.
For more information about Kibana, see here.
Install Kibana
In addition, I still use head and bigdesk. Of course, their positioning is almost different. Head is easy to use for data browsing and query. bigdesk is used for ElasticSearch cluster status monitoring. What about Kibana? It has the query function, but the most attractive is its awesome icon and performance ability. At least I think so before going deeper.
Install
You almost do not need to install this item. download it from the official elasticsearch website --> overview --> kibana.
Find any web server (apache, nginx, and so on) and drop it (direct fs cannot be opened). Of course, as a Java hacker, I persistently chose Tomcat.
Before enabling kibana, open the config. js file in the kibana directory and edit the elasticsearch field to point to your es uri.
Function (Settings ){
/** @ Scratch/configuration/config. js/2
*
* === Parameters
*/
Return new Settings ({
Elasticsearch: "http: // 10.128.170.245: 9200 ",
....
Use
You can easily open http: // localhost: 8080/kibana. The previous section contains almost the most frequently-typed characters except "hello world :).
As shown in the preceding figure, you only need to pay attention to the lower left corner of the right panel: Sample Dashboard, Unconfigured Dashboard, and Blank Dashboard. Sample Dashboard is the most basic trial interface. Click here to see how beautiful kibana charts can be.
Things start from 3. Blank Dashboard. After clicking enter, a Blank Dashboard is opened.
- Save/open: the simplest two functions are described first. In the upper-right corner of the page, you can recognize the open and save buttons at a Glance. You also know what they do and what they do.
- Share: the button next to the Save button is the share button. You don't need to talk about how it works or what it does.
- Add row: the layout of Kibana is the row and column layout. Currently, you can see only one Query and Filter. Regardless of the two guys, take A look at the [add a row] in the lower right corner and click it. Then... Let's talk about it in step 5.
- Give a name to the Dashboard: The Title and Style items should be displayed after the click, and then we can see that this is the Dashboard Settings --- "General. Well, before you start adding rows, you want to give the Dashboard a name, save it, or wait.
- Add Row: If you click Save, click Add A Row again. Otherwise, click Row on the tab. This is actually adding a row. Enter a name in the input box on the right. Click create row and save. You have the first Kibana Row in your life...
- Add Panel: Add a Panel. Click a button with text on the Row or move the cursor to the left to display a menu [shrink, configure, and add panel ]. The add dialog box is displayed. Select table and span to 12 (this is the width and the maximum value is 12), and then save directly.
- Query: assume that your elasticsearch instance already has data. You can enter the keyword "your words" in the top Query column to view the table Query result. The same Filter can also be used.
- Add Type filter: scroll down to the bottom of the page, click Add a new Row, and place it on the top through the up button (convenient ). Add Panel, select term, name Type, field _ type (default), and click save. Then, all the types of the current elasticsearch instance are listed. If you click any one, you will find that one Filter condition exists in the Filter.
- Copy the pie chart: then draw the pie chart of the Sample Dashboard, add the Panel, select the term, select pie in the style, and save. Yes.
Finally, let's see:
Summary
Kibana provides a wide range of forms, which are easy to understand based on the instructions of each chart. I hope I have the opportunity to add more introductions to various charts.
ELK is a classic combination: ElasticSearch, LogStash, and Kibana. E solves storage and retrieval (temporary storage, such as 30d), L is used for log collection, K vividly shows the trend of data changes, and provides query capabilities.
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