Elasticsearch is an open-source, distributed search and analytics engine built on top of Apache Lucene. It is designed to provide powerful search capabilities, enabling full-text search, structured search, and real-time data analytics. The engine’s architecture is highly scalable, allowing it to handle vast amounts of data with ease and efficiency. Its distributed nature ensures that data is spread across multiple nodes, providing high availability and fault tolerance.

One of the standout features of Elasticsearch is its ability to perform complex queries at high speeds, making it ideal for applications requiring fast search capabilities and real-time analytics. It supports a wide range of data types and formats, from structured numerical data to unstructured text, and offers advanced features like faceting, filtering, and aggregation. This makes Elasticsearch suitable for diverse use cases, including log and event data analysis, full-text search on websites and applications, and business intelligence.

Elasticsearch provides a RESTful API, which simplifies integration with various applications and services. This API allows users to index, search, and manage data with ease, using standard HTTP methods. Additionally, Elasticsearch’s integration with other tools in the Elastic Stack, such as Logstash for data ingestion and Kibana for visualization, enhances its capabilities and makes it a comprehensive solution for data analysis and visualization. Whether used for enterprise search, data analytics, or operational intelligence, Elasticsearch stands out for its performance, scalability, and flexibility.

To subscribe to this product from Azure Marketplace and initiate an instance using the Azure compute service, follow these steps:

1. Navigate to Azure Marketplace and subscribe to the desired product.
2. Search for “virtual machines” and select “Virtual machines” under Services.
3. Click on “Add” in the Virtual machines page, which will lead you to the Create a virtual machine page.
4. In the Basics tab:

• • Ensure the correct subscription is chosen under Project details.
  • Opt for creating a new resource group by selecting “Create new resource group” and name it as “myResourceGroup.”

5. Under Instance details:

• • Enter “myVM” as the Virtual machine name.
  • Choose “East US” as the Region.
  • Select “Ubuntu 18.04 LTS” as the Image.
  • Leave other settings as default.

6. For Administrator account:

• • Pick “SSH public key.”
  • Provide your user name and paste your public key, ensuring no leading or trailing white spaces.

7. Under Inbound port rules > Public inbound ports:

• • Choose “Allow selected ports.”
  • Select “SSH (22)” and “HTTP (80)” from the drop-down.

8. Keep the remaining settings at their defaults and click on “Review + create” at the bottom of the page.
9. The “Create a virtual machine” page will display the details of the VM you’re about to create. Once ready, click on “Create.”
10. The deployment process will take a few minutes. Once it’s finished, proceed to the next section.

To connect to the virtual machine:

1. Access the overview page of your VM and click on “Connect.”
2. On the “Connect to virtual machine” page:

• • Keep the default options for connecting via IP address over port 22.
  • A connection command for logging in will be displayed. Click the button to copy the command. Here’s an example of what the SSH connection command looks like:
    “`
    ssh [email protected]
    “`

3. Using the same bash shell that you used to generate your SSH key pair, you can either reopen the Cloud Shell by selecting >_ again

or going to https://shell.azure.com/bash.
4. Paste the SSH connection command into the shell to initiate an SSH session.

Usage/Deployment Instructions

Note: Search product on Azure marketplace and click on “Get it now”

Click on Continue

Click on Create

Creating a virtual machine, enter or select appropriate values for zone, machine type, resource group and so on as per your choice.

After Process of Create Virtual Machine. You have got an Option Go to Resource Group Click Go to Resource Group

Click on the Network Security Group: elasticsearch-nsg

Click on Inbound Security Rule

Click on Add & 3000

 Add Port