<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cicd on Ghafoor's Personal Blog</title><link>http://ghafoorsblog.com/tags/cicd/</link><description>Recent content in Cicd on Ghafoor's Personal Blog</description><generator>Hugo</generator><language>en</language><managingEditor>noreply@example.com (AG Sayyed)</managingEditor><webMaster>noreply@example.com (AG Sayyed)</webMaster><copyright>Copyright © 2024-2026 AG Sayyed. All Rights Reserved.</copyright><lastBuildDate>Sat, 16 May 2026 17:37:05 +0100</lastBuildDate><atom:link href="http://ghafoorsblog.com/tags/cicd/index.xml" rel="self" type="application/rss+xml"/><item><title>CI/CD Automation</title><link>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/14-generative-ai/02-module/001-ci-cd-automation/</link><pubDate>Fri, 29 Nov 2024 01:31:24 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/14-generative-ai/02-module/001-ci-cd-automation/</guid><description>&lt;p class="lead text-primary"&gt;
CI/CD leverages automation to frequently deliver applications, and AI enhances this process by automating testing, optimizing code, and facilitating intelligent release orchestration. AI-based monitoring tools ensure system reliability by detecting issues and analysing user feedback. Popular AI-enabled CI/CD tools include Jenkins, IBM Watson Studio, Codefresh, GitLab CI/CD, PagerDuty AIOps, Harness, Snyk, and Dynatrace's Davis AI. Future trends in AI for CI/CD involve AI-driven operationalisation, enhanced delivery health insights, and automated verification.
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