<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Integrity on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/integrity/</link><description>Recent content in Integrity on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/integrity/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 10: Database Management, Backups, and Data Integrity</title><link>https://ai-blog.noorshomelab.dev/trackio-2026-guide/10-database-management-and-backups/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/trackio-2026-guide/10-database-management-and-backups/</guid><description>&lt;h2 id="chapter-10-database-management-backups-and-data-integrity"&gt;Chapter 10: Database Management, Backups, and Data Integrity&lt;/h2&gt;
&lt;p&gt;Welcome back, experimenter! In the previous chapters, you&amp;rsquo;ve mastered the art of tracking your machine learning experiments with Trackio, from logging parameters and metrics to visualizing them on an interactive dashboard. You&amp;rsquo;ve seen how easy it is to spin up new runs and even sync them to Hugging Face Spaces.&lt;/p&gt;
&lt;p&gt;But what happens to all that precious experiment data locally? Trackio, true to its &amp;ldquo;local-first&amp;rdquo; philosophy, stores all your experiment details right on your machine. This chapter is all about understanding how Trackio manages this local data, how to keep it safe through robust backup strategies, and how to ensure its integrity over time. Think of it as learning how to safeguard your scientific research notes – absolutely critical for reproducibility and avoiding heartbreak!&lt;/p&gt;</description></item></channel></rss>