Creating a Linux Based Virtual Machine on Azure for Elasticsearch

Table of Contents

Creating virtual machine

  1. Go to portal.azure.com.
  2. Select Virtual machines.

If it’s not on your main menu, look under More services.

  1. Select Create.

  1. Select Virtual machine.

  1. Pick your subscription, resource group, region, and operating system, and then name your virtual machine.

  1. Pick the size of your machine. You need at least B2 level. To see the sizes, select See all sizes.

  1. Make sure the "Password" checkbox is selected, then type in the username and password for the admin account.

  1. Make sure you have the SSH (22) inbound port selected.

  1. Select Review + create.

  1. Select Create.


Opening the VM’s ports in Azure

Once you create your machine, you will need to add more inbound rules in the networking section of your VM.

  1. Go to your VM.

  1. Go to Networking.

  1. Select Add inbound port rule.

  1. To allow the port of Elasticsearch to be accessed from the outside, change the "Destination port ranges" to 9200 and choose the TCP protocol.
  2. Name this rule "ElasticSearch."

  1. Select Add.
  2. Follow the same steps with "Destination port ranges" of 5601 and with a priority level of 315. Also, use the name "Kibana." This is a graphical interface that will have to be accessed from the outside, as the Linux virtual machine (VM) lacks a graphical interface.

Connecting to a Linux VM

To connect to a Linux virtual machine, you need to use SSH. To connect via SSH with PowerShell:

  1. Run PowerShell.

Example: ssh KanBo@230.127.115.130 -p 22

  1. After you run the command, you will see a message asking if you want to continue the connection. Type "yes" and press the "enter" key.
  2. You will then be asked to type in your password (you won't see what you're typing). Use the same password that you used for the username.
  3. After typing in the password, press the "Enter" key.

Now you are connected to the Elasticsearch virtual machine, and can start installing and configuring Elasticsearch for KanBo.

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