Introduction Kibana reads properties from the configuration file kibana.yml when it starts up. The location of this file depends on how you installed Kibana. For example, the default location for kibana.yml is $KIBANA_HOME/config if you installed Kibana from an archive distribution such as a .tar.gz or .zip file. However, the its default location will be … Continued

Introduction The Console plugin for Elasticsearch includes a UI to interact with Elasticsearch’s REST API. Console has two main areas, including the editor and response panes. You can compose responses to Elasticsearch in the editor pane, and the response panes displays Elasticsearch’s responses. This tutorial shows how to display query results Kibana console. Prerequisites Elastic … Continued

Introduction This tutorial will help you easily learn how to upload CSV data using the Kibana UI and import your semi-structured text into Elasticsearch directly from the Kibana utility. Uploading you CSV data will allow you to organize your time-sensitive information, view your files across various dashboards and display the results as visualized data in … Continued

Introduction Elastricsearch is a powerful service that is enhanced further by incorporating the available tools from Elastic that integrate into it. Kibana is one of those tools and it brings a whole new dimension to using the service. You can learn how to set up and connect Kibana with Elasticsearch by following the process laid … Continued

Introduction To get the most out of the capability of the Elasticsearch service, it is best to install the entire Elastic Stack. This includes the user interface tool called Kibana, which brings the features onto the screen in a friendly layout. To establish the display options ability to access the data index patterns must be … Continued

Introduction If you want to provide the best possible search experience for your users, you need to make sure they’re getting the results they want. The problem is, sometimes users make mistakes. If you’re only querying for exact matches, simple typos and spelling errors can lead to empty results– not an ideal user experience. This … Continued

Introduction There’s a good chance that not all of the data the typical user stores in Elasticsearch will end up being used in queries. For example, a user might be using Elasticsearch to store web session data. While it makes sense that a user would want to query on fields like the last update time … Continued

Introduction When you’re working with data in Elasticsearch, there will likely be situations when you need to delete an index. You might have created an index just to test out some feature, but you don’t need to keep it permanently. You might have changed your overall data structure and find that you’re no longer using … Continued

Introduction If you’re familiar with Mongo or SQL databases, an index has the same function as those database technologies. Just like a database, an index holds documents. Databases use tables to differentiate between the kinds of documents while indexes characterize by document type. The latter lets you dig deep into the meaning of your data. … Continued

Introduction When importing data into Elasticsearch it will infer the types it uses based on the data that it is categorizing. It might be necessary to be explicit with details in Kibana if the working data is ambiguous or Elasticsearch is inferring the wrong type. Explicitly creating an object mapping is also good practice because … Continued