# Elasticsearch (v1)
## Introduction
This section explains how to add Elasticsearch data source, ingest data into Elasticsearch and query the data using AIOps/RDA environment.
## Adding Elasticsearch as Datasource in 'RDA':
RDA's user interface is used to configure Elasticsearch data source.
**Step 1: Accessing RDA UI**
Login into RDA's user interface using a browser.
**https\://\:9998**
Under '**Notebook**', click on '**CFXDX Python 3**' box
**Step 2: Adding Elasticsearch data source instance to RDA/AIOps**
In the '**Notebook**' command box, type **`botadmin()`** and **`alt (or option) + Enter`** to open the data source administration menu.
Click on the '**Add**' menu and under **Type** drop-down, select **`elasticsearch`**
* **Type:** Datasource/Extension type. In this context, it is '**elasticsearch**'
* **name**: Datasource/Extension label which should be unique within the RDA
* **Hostname:** Elasticsearch IP Address or FQDN/DNS name
* **Username**: User account that was created with 'read-only' permissions
* **Password**: User account's password
Click on '**Check Connectivity**' to verify the network access and credentials validity from RDA to Elasticsearch instance. Once it is validated, click on the '**Add**' button to add Elasticsearch as the data source
**Step 3: Adding tag definition in RDA and associate with Elasticsearch index**
Once the user completes **Step 2** and checks/validates connectivity from RDA to elasticsearch, the user can now add/define a tag in RDA which maps to elasticsearch index that was created earlier.
In the '**Notebook**' command box, type **`botadmin()`** and **`alt (or option) + Enter`** to open the data source administration menu.
Click on the '**Edit**' menu and under **Type** drop-down, select **'es/elasticsearch'** item that was created in step 2 (as shown in the below screenshot).
Note: In the above RDA tags definition, RDA keeps track of tag (rda-to-elasticsearch) to that of elasticsearch index (rda\_to\_elasticsearch\_idx with unique id as idx).
The code snippet is captured in the below code block.
```
- tag: rda-to-elasticsearch
index: rda_to_elasticsearch_idx
update:
index: rda_to_elasticsearch_idx
ids:
- idx
```
**Note: Before performing step 3, make sure elasticsearch index (rda\_to\_elasticsearch\_idx) has been created ahead in elasticsearch instance and verified using standard tools (e.g. curl or postman)**
**Step 4: Adding data using RDA and storing in Elasticsearch using the mapping that was created**
Create a pipeline "***rda\_to\_elasticsearch\_example\_1***" and copy the below code into your pipeline and perform the rest of the steps in your environment. \
\
\&#xNAN;*`##### This pipeline creates couple of user names and ids using RDA/AIOps Studio.`* \
*`##### RDA uses the mapping that was created and stores the records into elasticsearch`*\
\
*`--> @dm:empty`* \
*`--> @dm:addrow idx = 1 & name = 'David' & lastname = 'Eiger' & email = 'deiger@hello.com'`*\
*`--> @dm:addrow idx = 2 & name = 'Emma' & lastname = 'Edge' & email = 'eedge@hello.com'`*\
*`--> @dm:addrow idx = 3 & name = 'John' & lastname = 'Seagul' & email = 'jseagul@hello.com'`*\
*`--> @dm:addrow idx = 4 & name = 'Peter' & lastname = 'Samuel' & email = 'psamuel@hello.com'`*\
*`--> @dm:addrow idx = 5 & name = 'Sean' & lastname = 'Taylor' & email = 'staylor@hello.com'`*\
*`--> #es:rda-to-elasticsearch`*
**Step 5: Verify the above-added pipeline using AIOps/RDA by selecting the 'Verify' button as shown in the below screenshot**
**Step 6: Execute the pipeline by selecting the 'Execute' button as shown in the below screenshot**
**Step 7: Verify the data stored in Elasticsearch using RDA (and or using curl command).**
**Method A -- Using Curl command**
Step 1: Log in to the machine where Elasticsearch instance is running using putty or any other SSH tool
```
bash# ssh macaw@10.95.103.111
```
Step 2: Once you log in, run the following curl command to validate the data stored
```
curl -X GET 'http://localhost:9200/rda_to_elasticsearch_idx/_search'?pretty=true
```
The above curl command will return the data as pretty formatted JSON output as shown below.
**Method B -- Using RDA pipeline**
Step 1: Create a pipeline "***verify\_elasticsearch\_to\_rda\_data\_01***" and copy the below code into your pipeline and perform the rest of the steps in your environment.
*`##### This pipeline verifies the data stored via RDA pipeline`* \
*`#####`* \
*`--> @c:new-block`*\
*`--> #es:rda-to-elasticsearch`*
Step 2: Verify the above-created pipeline using RDA/AIOps studio as shown in the below screenshot
Step 3: Execute and verify the output of the data using RDA/AIOps studio as shown in the below screenshot
The above example walks through Elasticsearch integration with RDA using a simple inline dataset creation of users (name, last name, etc.). In addition, the datasets can come from files and/or other data sources like MySQL, etc. Users can explore other data sources using the above-explained steps.
Also, in the above example, a single Elasticsearch index 'idx' has been used to walk through the use case. Users can also extend or add additional indices to make a unique index based on the use case in context.