<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Hyeonho Kim &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/author/hyeonho-kim/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Thu, 14 Aug 2025 15:16:29 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.2</generator>
	<item>
		<title>How Karrot built a feature platform on AWS, Part 1: Motivation and feature serving</title>
		<link>https://noise.getoto.net/2025/08/14/how-karrot-built-a-feature-platform-on-aws-part-1-motivation-and-feature-serving/</link>
		
		<dc:creator><![CDATA[Hyeonho Kim]]></dc:creator>
		<pubDate>Thu, 14 Aug 2025 15:16:29 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[Amazon ElastiCache]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=2372e9b5ee49f4bbd1c3e4e898397817</guid>

					<description><![CDATA[This two-part series shows how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. This post starts by presenting our motivation, our requirements, and the solution architecture, focusing on feature serving.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How Karrot built a feature platform on AWS, Part 2: Feature ingestion</title>
		<link>https://noise.getoto.net/2025/08/14/how-karrot-built-a-feature-platform-on-aws-part-2-feature-ingestion/</link>
		
		<dc:creator><![CDATA[Hyeonho Kim]]></dc:creator>
		<pubDate>Thu, 14 Aug 2025 15:16:27 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Managed Streaming for Apache Kafka (Amazon MSK)]]></category>
		<category><![CDATA[AWS Batch]]></category>
		<category><![CDATA[AWS Fargate]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=60cc1c38a11c49fb014bae602c8b7702</guid>

					<description><![CDATA[This two-part series shows how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. This post covers the process of collecting features in real-time and batch ingestion into an online store, and the technical approaches for stable operation.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/

Object Caching 28/66 objects using Memcached
Page Caching using Disk: Enhanced 
Lazy Loading (feed)
Database Caching using Memcached

Served from: noise.getoto.net @ 2026-02-16 17:24:58 by W3 Total Cache
-->