<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: How to create an image from a cluster so that the compute environment can be replicated in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/how-to-create-an-image-from-a-cluster-so-that-the-compute/m-p/165072#M55384</link>
    <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/182577"&gt;@NW1000&lt;/a&gt;&amp;nbsp;,&lt;/P&gt;&lt;P&gt;For Classic Compute, the best approach is using Databricks Container Services (DCS). This lets you package your exact OS, system libraries, and Python environment into a custom Docker image. You just push that image to a private registry and point your cluster to it. Your version-controlled Dockerfile then acts as the exact audit trail your regulators need. You can find the detailed guide for this here: &lt;A class="" href="https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers" target="_blank" rel="noopener"&gt;https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers&lt;/A&gt;&lt;/P&gt;&lt;P&gt;For Serverless Compute, custom Docker images aren't supported because Databricks fully manages the underlying infrastructure. Instead, you replicate the environment by locking in a specific Databricks Runtime (DBR) version and using a strict requirements.txt file to pin your exact package versions. Storing those requirements and your cluster definitions (like JSON or Terraform) in Git gives you the verifiable history required for compliance.&lt;/P&gt;&lt;P&gt;Hope this points you in the right direction!&lt;/P&gt;</description>
    <pubDate>Fri, 07 Aug 2026 06:16:41 GMT</pubDate>
    <dc:creator>ShamenParis</dc:creator>
    <dc:date>2026-08-07T06:16:41Z</dc:date>
    <item>
      <title>How to create an image from a cluster so that the compute environment can be replicated</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-create-an-image-from-a-cluster-so-that-the-compute/m-p/165049#M55383</link>
      <description>&lt;P&gt;I am working in a regulated industry. It is necessary to document and replicate the compute environment. I guess to do this for a classic cluster vs a serverless one is different. Anyone knows how to do it? Thank you for your assistance.&lt;/P&gt;</description>
      <pubDate>Thu, 06 Aug 2026 19:15:49 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-create-an-image-from-a-cluster-so-that-the-compute/m-p/165049#M55383</guid>
      <dc:creator>NW1000</dc:creator>
      <dc:date>2026-08-06T19:15:49Z</dc:date>
    </item>
    <item>
      <title>Re: How to create an image from a cluster so that the compute environment can be replicated</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-create-an-image-from-a-cluster-so-that-the-compute/m-p/165072#M55384</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/182577"&gt;@NW1000&lt;/a&gt;&amp;nbsp;,&lt;/P&gt;&lt;P&gt;For Classic Compute, the best approach is using Databricks Container Services (DCS). This lets you package your exact OS, system libraries, and Python environment into a custom Docker image. You just push that image to a private registry and point your cluster to it. Your version-controlled Dockerfile then acts as the exact audit trail your regulators need. You can find the detailed guide for this here: &lt;A class="" href="https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers" target="_blank" rel="noopener"&gt;https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers&lt;/A&gt;&lt;/P&gt;&lt;P&gt;For Serverless Compute, custom Docker images aren't supported because Databricks fully manages the underlying infrastructure. Instead, you replicate the environment by locking in a specific Databricks Runtime (DBR) version and using a strict requirements.txt file to pin your exact package versions. Storing those requirements and your cluster definitions (like JSON or Terraform) in Git gives you the verifiable history required for compliance.&lt;/P&gt;&lt;P&gt;Hope this points you in the right direction!&lt;/P&gt;</description>
      <pubDate>Fri, 07 Aug 2026 06:16:41 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-create-an-image-from-a-cluster-so-that-the-compute/m-p/165072#M55384</guid>
      <dc:creator>ShamenParis</dc:creator>
      <dc:date>2026-08-07T06:16:41Z</dc:date>
    </item>
  </channel>
</rss>

