<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Asset Bundles on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/asset-bundles/</link><description>Recent content in Asset Bundles on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 20 Dec 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/asset-bundles/index.xml" rel="self" type="application/rss+xml"/><item><title>CI/CD for Databricks Pipelines with Databricks Asset Bundles</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/14-ci-cd-databricks-bundles/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence-2/14-ci-cd-databricks-bundles/</guid><description>&lt;h2 id="chapter-14-cicd-for-databricks-pipelines-with-databricks-asset-bundles"&gt;Chapter 14: CI/CD for Databricks Pipelines with Databricks Asset Bundles&lt;/h2&gt;
&lt;h3 id="chapter-introduction"&gt;Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In previous chapters, we meticulously crafted robust data pipelines using Databricks Delta Live Tables (DLT) for real-time ingestion, Spark Structured Streaming for logistics cost monitoring, and various Spark jobs for tariff analysis and anomaly detection. We&amp;rsquo;ve built the individual components, but deploying and managing these complex pipelines across different environments (development, staging, production) can quickly become a significant challenge without proper automation. This is where Continuous Integration/Continuous Deployment (CI/CD) comes into play, ensuring that our code changes are consistently tested, validated, and deployed.&lt;/p&gt;</description></item><item><title>CI/CD for Databricks Pipelines with Databricks Asset Bundles</title><link>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/14-ci-cd-databricks-bundles/</link><pubDate>Sat, 20 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/realtime-supply-chain-intelligence/14-ci-cd-databricks-bundles/</guid><description>&lt;h2 id="chapter-14-cicd-for-databricks-pipelines-with-databricks-asset-bundles"&gt;Chapter 14: CI/CD for Databricks Pipelines with Databricks Asset Bundles&lt;/h2&gt;
&lt;h3 id="chapter-introduction"&gt;Chapter Introduction&lt;/h3&gt;
&lt;p&gt;In previous chapters, we meticulously crafted robust data pipelines using Databricks Delta Live Tables (DLT) for real-time ingestion, Spark Structured Streaming for logistics cost monitoring, and various Spark jobs for tariff analysis and anomaly detection. We&amp;rsquo;ve built the individual components, but deploying and managing these complex pipelines across different environments (development, staging, production) can quickly become a significant challenge without proper automation. This is where Continuous Integration/Continuous Deployment (CI/CD) comes into play, ensuring that our code changes are consistently tested, validated, and deployed.&lt;/p&gt;</description></item></channel></rss>