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	<title>Redis &#8211; Noise</title>
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		<title>Evaluating performance impact of removing Redis-cache from a Scylla-backed service</title>
		<link>https://noise.getoto.net/2025/04/11/evaluating-performance-impact-of-removing-redis-cache-from-a-scylla-backed-service/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 11 Apr 2025 00:23:00 +0000</pubDate>
				<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Event Processing]]></category>
		<category><![CDATA[Optimisation]]></category>
		<category><![CDATA[Redis]]></category>
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					<description><![CDATA[Introduction

At Grab, we operate a set of services that manage and provide counts of various items. While this may seem straightforward, the scale at which this feature operates—benefiting millions of Grab users daily—introduces complexity. This featu...]]></description>
		
		
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		<item>
		<title>Evaluating performance impact of removing Redis-cache from a Scylla-backed service</title>
		<link>https://noise.getoto.net/2025/04/11/evaluating-performance-impact-of-removing-redis-cache-from-a-scylla-backed-service-2/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 11 Apr 2025 00:23:00 +0000</pubDate>
				<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Event Processing]]></category>
		<category><![CDATA[Optimisation]]></category>
		<category><![CDATA[Redis]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/evaluate-performance-remove-redis-from-scylla-service</guid>

					<description><![CDATA[Introduction

At Grab, we operate a set of services that manage and provide counts of various items. While this may seem straightforward, the scale at which this feature operates—benefiting millions of Grab users daily—introduces complexity. This featu...]]></description>
		
		
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		<title>Let’s Architect! Leveraging in-memory databases</title>
		<link>https://noise.getoto.net/2023/09/13/lets-architect-leveraging-in-memory-databases/</link>
		
		<dc:creator><![CDATA[Luca Mezzalira]]></dc:creator>
		<pubDate>Wed, 13 Sep 2023 15:36:46 +0000</pubDate>
				<category><![CDATA[Amazon ElastiCache]]></category>
		<category><![CDATA[Amazon MemoryDB for Redis]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[cost optimization]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Let's Architect]]></category>
		<category><![CDATA[Redis]]></category>
		<category><![CDATA[reInvent]]></category>
		<category><![CDATA[Thought Leadership]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=cc10d26fb24290ccbed2267c96869803</guid>

					<description><![CDATA[In-memory databases play a critical role in modern computing, particularly in reducing the strain on existing resources, scaling workloads efficiently, and minimizing the cost of infrastructure. The advanced performance capabilities of in-memory databases make them vital for demanding applications characterized by voluminous data, real-time analytics, and rapid response requirements. In this edition of Let’s Architect!, […]]]></description>
		
		
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		<title>Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support…</title>
		<link>https://noise.getoto.net/2022/09/28/timestone-netflixs-high-throughput-low-latency-priority-queueing-system-with-built-in-support/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Wed, 28 Sep 2022 15:40:35 +0000</pubDate>
				<category><![CDATA[distributed-systems]]></category>
		<category><![CDATA[priority-queue]]></category>
		<category><![CDATA[Redis]]></category>
		<guid isPermaLink="false">https://medium.com/p/1abf249ba95f</guid>

					<description><![CDATA[Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloadsby Kostas ChristidisIntroductionTimestone is a high-throughput, low-latency priority queueing system we built in-house to s...]]></description>
		
		
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		<item>
		<title>Exploring Data @ Netflix</title>
		<link>https://noise.getoto.net/2021/06/25/exploring-data-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Fri, 25 Jun 2021 11:03:04 +0000</pubDate>
				<category><![CDATA[cassandra]]></category>
		<category><![CDATA[dynomite]]></category>
		<category><![CDATA[nodejs]]></category>
		<category><![CDATA[Redis]]></category>
		<category><![CDATA[vuejs]]></category>
		<guid isPermaLink="false">https://medium.com/p/9d87e20072e3</guid>

					<description><![CDATA[By Gim Mahasintunan on behalf of Data Platform Engineering.Supporting a rapidly growing base of engineers of varied backgrounds using different data stores can be challenging in any organization. Netflix’s internal teams strive to provide leverage by i...]]></description>
		
		
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		<item>
		<title>Uncovering the truth behind Lua and Redis data consistency</title>
		<link>https://noise.getoto.net/2020/09/07/uncovering-the-truth-behind-lua-and-redis-data-consistency/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Mon, 07 Sep 2020 08:43:40 +0000</pubDate>
				<category><![CDATA[CPU Usage]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Lua Scripts]]></category>
		<category><![CDATA[Redis]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/uncovering-the-truth-behind-lua-and-redis-data-consistency</guid>

					<description><![CDATA[Uncovering the truth behind Lua and Redis data consistency

Our team at Grab uses Redis as one of our message queues. The Redis server is deployed in a master/replica setup. Quite recently, we have been noticing a spike in the CPU usage of the Redis re...]]></description>
		
		
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