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Allocate Shards of Indices to Specific Elasticsearch Nodes

A great way to save money when sizing compute and storage for an Elasticsearch cluster is by using hot-warm architectures. Especially for time series data, hot-warm architectures allow you to allocate your most relevant data (hot data) on your fastest nodes (hot nodes) and your less relevant data (warm data) on your slower nodes (warm nodes). This allows you to scale data retention with cheaper compute and storage and only pay a premium for your hot nodes. All this is made possible in Elasticsearch through the use of node attributes and allocation filtering, which can be used in any case where you want your index allocation to meet specific requirements. In this hands-on lab, you are given the opportunity to exercise the following: * Apply node attributes to each data node in a cluster * Configure indexes to allocate to specific nodes based on their attributes

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Path Info

Level
Clock icon Advanced
Duration
Clock icon 1h 30m
Last updated
Clock icon May 09, 2025

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Table of Contents

  1. Challenge

    Configure nodes data-1 and data-2 to have a "temp" node attribute of "hot".

    Using the Secure Shell (SSH), log in to the data-1 and data-2 nodes as cloud_user via the public IP address.

    Become the elastic user with:

    sudo su - elastic

    In the /home/elastic/elasticsearch/config/elasticsearch.yml file, change the following line:

    #node.attr.rack: r1

    to

    node.attr.temp: hot

    Restart the elasticsearch node with:

    pkill -F /home/elastic/elasticsearch/pid
/home/elastic/elasticsearch/bin/elasticsearch -d -p pid

  2. Challenge

    Configure nodes data-3 and data-4 to have a "temp" node attribute of "warm".

    Using the Secure Shell (SSH), log in to the data-3 and data-4 nodes as cloud_user via the public IP address.

    Become the elastic user with:

    sudo su - elastic

    In the /home/elastic/elasticsearch/config/elasticsearch.yml file, change the following line:

    #node.attr.rack: r1

    to

    node.attr.temp: warm

    Restart the elasticsearch node with:

    pkill -F /home/elastic/elasticsearch/pid
/home/elastic/elasticsearch/bin/elasticsearch -d -p pid

  3. Challenge

    Allocate the logs-03 index to the hot nodes.

    Use the Kibana console tool to execute the following:

    PUT logs-03/_settings
{
  "index.routing.allocation.require.temp": "hot"
}

  4. Challenge

    Allocate the logs-02 index to the warm nodes.

    Use the Kibana console tool to execute the following:

    PUT logs-02/_settings
{
  "index.routing.allocation.require.temp": "warm"
}

  5. Challenge

    Allocate the logs-01 index to the warm nodes.

    Use the Kibana console tool to execute the following:

    PUT logs-01/_settings
{
  "index.routing.allocation.require.temp": "warm"
}
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Pluralsight Skills

Pluralsight Skills gives leaders confidence they have the skills needed to execute technology strategy. Technology teams can benchmark expertise across roles, speed up release cycles and build reliable, secure products. By leveraging our expert content, skill assessments and one-of-a-kind analytics, keep up with the pace of change, put the right people on the right projects and boost productivity. It's the most effective path to developing tech skills at scale.

What's a lab?

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.

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Follow along with the author’s guided walkthrough and build something new in your provided environment!

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