<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Clustering on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/clustering/</link><description>Recent content in Clustering on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 18 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/clustering/index.xml" rel="self" type="application/rss+xml"/><item><title>Getting Started with Your Databricks Workspace</title><link>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/getting-started-workspace/</link><pubDate>Fri, 19 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/getting-started-workspace/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Welcome, aspiring data wizard! In this exciting first chapter, we&amp;rsquo;re going to embark on our journey into the powerful world of Databricks. Think of this as your grand tour of the Databricks &amp;ldquo;command center&amp;rdquo; – your workspace. We&amp;rsquo;ll start from the absolute basics, ensuring you feel comfortable and confident navigating this platform.&lt;/p&gt;
&lt;p&gt;By the end of this chapter, you&amp;rsquo;ll know how to access your Databricks workspace, understand its fundamental components like clusters and notebooks, and even run your very first piece of code. This foundational knowledge is crucial because the Databricks workspace is where all your data engineering, machine learning, and analytics magic happens. It&amp;rsquo;s the launchpad for every project we&amp;rsquo;ll build together!&lt;/p&gt;</description></item><item><title>Chapter 8: Unsupervised Learning: Finding Hidden Patterns</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/unsupervised-learning-intro/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/unsupervised-learning-intro/</guid><description>&lt;h2 id="introduction-the-detective-of-data"&gt;Introduction: The Detective of Data&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI wizard! So far in our journey, we&amp;rsquo;ve explored the exciting world of Supervised Learning. Remember how we trained models with labeled data, like teaching a child to identify cats by showing them pictures &lt;em&gt;labeled&lt;/em&gt; &amp;ldquo;cat&amp;rdquo;? We had a &amp;ldquo;teacher&amp;rdquo; telling the model what the correct answer was.&lt;/p&gt;
&lt;p&gt;But what if there&amp;rsquo;s no teacher? What if you have a huge pile of information and no one tells you what&amp;rsquo;s what? This is where a truly fascinating side of Machine Learning comes in: &lt;strong&gt;Unsupervised Learning&lt;/strong&gt;.&lt;/p&gt;</description></item><item><title>Advanced Topics: High Availability and Clustering</title><link>https://ai-blog.noorshomelab.dev/redis-guide/high-availability-and-clustering/</link><pubDate>Fri, 07 Nov 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/redis-guide/high-availability-and-clustering/</guid><description>&lt;p&gt;In production environments, simply running a single Redis instance is often not enough. You need to ensure your Redis service is &lt;strong&gt;highly available&lt;/strong&gt; (it remains operational even if a server fails) and &lt;strong&gt;scalable&lt;/strong&gt; (it can handle increased load and data volume). Redis offers two primary solutions for these challenges: &lt;strong&gt;Redis Sentinel&lt;/strong&gt; for high availability and &lt;strong&gt;Redis Cluster&lt;/strong&gt; for horizontal scaling.&lt;/p&gt;
&lt;p&gt;This chapter will guide you through:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;The concepts of High Availability (HA) and how Redis achieves it.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Redis Sentinel&lt;/strong&gt;: For automatic failover and monitoring of master-replica setups.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Redis Cluster&lt;/strong&gt;: For sharding data across multiple nodes and providing both HA and linear scalability.&lt;/li&gt;
&lt;li&gt;Understanding the trade-offs and when to use each.&lt;/li&gt;
&lt;/ul&gt;
&lt;h3 id="1-high-availability-with-redis-sentinel"&gt;1. High Availability with Redis Sentinel&lt;/h3&gt;
&lt;p&gt;Redis Sentinel is a distributed system that provides high availability for Redis. It continuously monitors your Redis instances (masters and replicas), and if a master goes down, it automatically promotes a replica to become the new master. Sentinel also reconfigures the other replicas to follow the new master and informs client applications about the change.&lt;/p&gt;</description></item></channel></rss>