Prerequisites

• If you don’t have Docker installed,download and install Docker Desktop for your operating system.

• If you’re using Microsoft Windows, then installWindows Subsystem for Linux (WSL).

Trial license

This setup comes with a one-month trial license that includes all Elastic features.

After the trial period, the license reverts toFree and open - Basic.Refer toElastic subscriptions for more information.

Runstart-local

To set up Elasticsearch and Kibana locally, run thestart-local script:

This script creates anelastic-start-local folder containing configuration files and starts both Elasticsearch and Kibana using Docker.

After running the script, you can access Elastic services at the following endpoints:

• Elasticsearch:http://localhost:9200

• Kibana:http://localhost:5601

The script generates a random password for theelastic user, which is displayed at the end of the installation and stored in the.env file.

API access

An API key for Elasticsearch is generated and stored in the.env file asES_LOCAL_API_KEY.Use this key to connect to Elasticsearch with aprogramming language client or theREST API.

From theelastic-start-local folder, check the connection to Elasticsearch usingcurl:

Using curl

Here’s an example curl command to create a new Elasticsearch index, using basic auth:

Using a language client

To connect to your local dev Elasticsearch cluster with a language client, you can use basic authentication with theelastic username and the password you set in the environment variable.

You’ll use the following connection details:

• Elasticsearch endpoint:http://localhost:9200

• Username:elastic

• Password:$ELASTIC_PASSWORD (Value you set in the environment variable)

For example, to connect with the Pythonelasticsearch client:

Using the Dev Tools Console

Kibana’s developer console provides an easy way to experiment and test requests.To access the console, open Kibana, then go toManagement >Dev Tools.

Add data

You index data into Elasticsearch by sending JSON objects (documents) through the REST APIs.Whether you have structured or unstructured text, numerical data, or geospatial data,Elasticsearch efficiently stores and indexes it in a way that supports fast searches.

For timestamped data such as logs and metrics, you typically add documents to adata stream made up of multiple auto-generated backing indices.

To add a single document to an index, submit an HTTP post request that targets the index.

This request automatically creates thecustomer index if it doesn’t exist,adds a new document that has an ID of 1, andstores and indexes thefirstname andlastname fields.

The new document is available immediately from any node in the cluster.You can retrieve it with a GET request that specifies its document ID:

To add multiple documents in one request, use the_bulk API.Bulk data must be newline-delimited JSON (NDJSON).Each line must end in a newline character (\n), including the last line.

Search

Indexed documents are available for search in near real-time.The following search matches all customers with a first name ofJenniferin thecustomer index.

Explore

You can use Discover in Kibana to interactively search and filter your data.From there, you can start creating visualizations and building and sharing dashboards.

To get started, create adata view that connects to one or more Elasticsearch indices,data streams, or index aliases.

1. Go toManagement > Stack Management > Kibana > Data Views.

2. SelectCreate data view.

3. Enter a name for the data view and a pattern that matches one or more indices,such ascustomer.

4. SelectSave data view to Kibana.

To start exploring, go toAnalytics > Discover.