<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ci/Cd on MacWorks</title><link>https://macworks.dev/tags/ci/cd/</link><description>Recent content in Ci/Cd on MacWorks</description><generator>Hugo</generator><language>en</language><atom:link href="https://macworks.dev/tags/ci/cd/index.xml" rel="self" type="application/rss+xml"/><item><title>2026-05-16</title><link>https://macworks.dev/docs/week/blogs/engineer-blogs-2026-05-16/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/blogs/engineer-blogs-2026-05-16/</guid><description>&lt;h1 id="engineering-reads--2026-05-16"&gt;Engineering Reads — 2026-05-16&lt;a class="anchor" href="#engineering-reads--2026-05-16"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="the-big-idea"&gt;The Big Idea&lt;a class="anchor" href="#the-big-idea"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;The defining challenge of modern engineering is resource management at the extremes—whether that means reclaiming CI/CD compute cycles from vendor lock-in via lower-level orchestration, or driving down the inference costs of long-context LLMs through architectural optimization.&lt;/p&gt;
&lt;h2 id="deep-reads"&gt;Deep Reads&lt;a class="anchor" href="#deep-reads"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Slowly going mad with power using Tekton&lt;/strong&gt; · xeiaso.net · &lt;a href="https://xeiaso.net/blog/2026/tekton/"&gt;Source&lt;/a&gt;
The author outlines a strategic migration away from GitHub Actions to mitigate platform lock-in, replacing it with Tekton, a Kubernetes-native CI/CD operator. Instead of relying on a managed platform&amp;rsquo;s implicit state and runner lifecycles, Tekton forces you to model CI as a series of lower-level Kubernetes primitives: Tasks, TaskRuns, Pipelines, and PipelineRuns. This requires explicitly managing the grimy details of distributed builds, such as configuring Persistent Volume Claims (PVCs) for repository clones and shared Go module caches. The explicit tradeoff here is operational overhead—like debugging vague VCS errors or manually configuring Kaniko forks for Docker builds—in exchange for leveraging idle homelab compute and achieving absolute vendor neutrality. Engineers looking to future-proof their deployment pipelines against platform decay should read this to understand the true operational cost of infrastructure independence.&lt;/p&gt;</description></item></channel></rss>