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	<title>data &#8211; Noise</title>
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	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Mon, 01 Dec 2025 00:00:10 +0000</lastBuildDate>
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		<title>A Decade of Defense: Celebrating Grab&#8217;s 10th Year Bug Bounty Program</title>
		<link>https://noise.getoto.net/2025/12/01/a-decade-of-defense-celebrating-grabs-10th-year-bug-bounty-program/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Mon, 01 Dec 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/a-decade-of-defense</guid>

					<description><![CDATA[Introduction

Ten years ago, we launched our bug bounty program in partnership with HackerOne. Beyond a security initiative, it represented an open invitation to collaborative development.
As pioneers in Southeast Asia, we began the program with 23 ini...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Real-time data quality monitoring: Kafka stream contracts with syntactic and semantic test</title>
		<link>https://noise.getoto.net/2025/11/26/real-time-data-quality-monitoring-kafka-stream-contracts-with-syntactic-and-semantic-test/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Wed, 26 Nov 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data processing]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[kafka]]></category>
		<category><![CDATA[Performance]]></category>
		<category><![CDATA[Real-time streaming]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/real-time-data-quality-monitoring</guid>

					<description><![CDATA[Introduction

In today’s data-driven landscape, monitoring data quality has become a critical need for ensuring reliable and efficient data usage across domains. High-quality data is the backbone of AI innovation, driving efficiency and unlocking new o...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>SpellVault’s evolution: Beyond LLM apps, towards the agentic future</title>
		<link>https://noise.getoto.net/2025/11/21/spellvaults-evolution-beyond-llm-apps-towards-the-agentic-future/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 21 Nov 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/spellvault-evolution-beyond-llm</guid>

					<description><![CDATA[Introduction

At Grab, innovation isn’t just about building new features; it’s about evolving our platforms to meet the changing needs of our users and the broader technological landscape. SpellVault, our internal AI platform, exemplifies this philosop...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How We Built a Custom Vision LLM to Improve Document Processing at Grab</title>
		<link>https://noise.getoto.net/2025/11/04/how-we-built-a-custom-vision-llm-to-improve-document-processing-at-grab/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 04 Nov 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/custom-vision-llm-at-grab</guid>

					<description><![CDATA[Introduction

In the world of digital services, accurate extraction of information from user-submitted documents such as identification (ID) cards, driver’s licenses, and registration certificates is a critical first step for processes like electronic ...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Machine-learning predictive autoscaling for Flink</title>
		<link>https://noise.getoto.net/2025/10/30/machine-learning-predictive-autoscaling-for-flink/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Thu, 30 Oct 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/ml-predictive-autoscaling-for-flink</guid>

					<description><![CDATA[Introduction

As Grab transitions to derive more valuable insights from our wealth of operational data, we are witnessing a steep increase in stream-processing applications. Over the past year, the number of Flink applications grew 2.5 times, driven by...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Modernising Grab’s model serving platform with NVIDIA Triton Inference Server</title>
		<link>https://noise.getoto.net/2025/10/21/modernising-grabs-model-serving-platform-with-nvidia-triton-inference-server/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 21 Oct 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/modernising-grab-model-serving-platform</guid>

					<description><![CDATA[Introduction

Catwalk is Grab’s machine learning (ML) model serving platform, designed to enable data scientists and engineers in deploying production-ready inference APIs. Currently, Catwalk powers hundreds of ML models and online deployments. To acco...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>100X Faster: How We Supercharged Netflix Maestro’s Workflow Engine</title>
		<link>https://noise.getoto.net/2025/09/29/100x-faster-how-we-supercharged-netflix-maestros-workflow-engine/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Mon, 29 Sep 2025 16:10:40 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[distributed-systems]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Orchestration]]></category>
		<category><![CDATA[workflow]]></category>
		<guid isPermaLink="false">https://medium.com/p/028e9637f041</guid>

					<description><![CDATA[By Jun He, Yingyi Zhang, Ely SpearsTL;DRWe recently upgraded the Maestro engine to go beyond scalability and improved its performance by 100X! The overall overhead is reduced from seconds to milliseconds. We have updated the Maestro open source project...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>R2 SQL: a deep dive into our new distributed query engine</title>
		<link>https://noise.getoto.net/2025/09/25/r2-sql-a-deep-dive-into-our-new-distributed-query-engine/</link>
		
		<dc:creator><![CDATA[Yevgen Safronov]]></dc:creator>
		<pubDate>Thu, 25 Sep 2025 14:00:00 +0000</pubDate>
				<category><![CDATA[Birthday Week]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[deep dive]]></category>
		<category><![CDATA[Edge Computing]]></category>
		<category><![CDATA[R2]]></category>
		<category><![CDATA[Rust]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[sql]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ab1627715b21eef517b35ab98c180785</guid>

					<description><![CDATA[R2 SQL provides a built-in, serverless way to run ad-hoc analytic queries against your R2 Data Catalog. This post dives deep under the Iceberg into how we built this distributed engine.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Powering Partner Gateway metrics with Apache Pinot</title>
		<link>https://noise.getoto.net/2025/09/23/powering-partner-gateway-metrics-with-apache-pinot/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 23 Sep 2025 00:00:10 +0000</pubDate>
				<category><![CDATA[Apache]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/pinot-partnergateway-tech-blog</guid>

					<description><![CDATA[Introduction

Grab operates as a dynamic ecosystem involving partners and various service providers, necessitating real-time intelligence and decision-making for seamless integration and service delivery. To facilitate this, GrabDeveloper serves as Gra...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>From Facts &#038; Metrics to Media Machine Learning: Evolving the Data Engineering Function at Netflix</title>
		<link>https://noise.getoto.net/2025/08/21/from-facts-metrics-to-media-machine-learning-evolving-the-data-engineering-function-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Thu, 21 Aug 2025 17:39:40 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Technology]]></category>
		<guid isPermaLink="false">https://medium.com/p/6dcc91058d8d</guid>

					<description><![CDATA[By Dao Mi, Pablo Delgado, Ryan Berti, Amanuel Kahsay, Obi-Ike Nwoke, Christopher Thrailkill, and Patricio GarzaAt Netflix, data engineering has always been a critical function to enable the business’s ability to understand content, power recommendation...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Data mesh at Grab part I: Building trust through certification</title>
		<link>https://noise.getoto.net/2025/08/19/data-mesh-at-grab-part-i-building-trust-through-certification/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 19 Aug 2025 00:23:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/signals-market-place</guid>

					<description><![CDATA[Introduction

At Grab, our journey towards a more robust and scalable data ecosystem has been a continuous evolution.

Considering the size of our data lake and complexity of our ecosystem, with businesses spanning across ride hailing, food delivery, a...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Building Jetflow: a framework for flexible, performant data pipelines at Cloudflare</title>
		<link>https://noise.getoto.net/2025/07/23/building-jetflow-a-framework-for-flexible-performant-data-pipelines-at-cloudflare/</link>
		
		<dc:creator><![CDATA[Harry Hough]]></dc:creator>
		<pubDate>Wed, 23 Jul 2025 14:00:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[design]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Go]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=5282ec36a5804ca53ca287da709b0dce</guid>

					<description><![CDATA[Faced with a data-ingestion challenge at a massive scale, Cloudflare's Business Intelligence team built a new framework called Jetflow.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Counter Service: How we rewrote it in Rust</title>
		<link>https://noise.getoto.net/2025/06/20/counter-service-how-we-rewrote-it-in-rust/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 20 Jun 2025 00:23:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Rust]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/counter-service-how-we-rewrote-it-in-rust</guid>

					<description><![CDATA[Abstract

The Integrity Data Platform (IDP) team decided to rewrite one of our heavy Queries Per Second (QPS) Golang microservices in Rust. It resulted in 70% infrastructure savings at a similar performance, but was not without its pitfalls. This artic...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Introducing Impressions at Netflix</title>
		<link>https://noise.getoto.net/2025/02/15/introducing-impressions-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Sat, 15 Feb 2025 01:13:20 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[data-engineering]]></category>
		<category><![CDATA[distributed-systems]]></category>
		<guid isPermaLink="false">https://medium.com/p/e2b67c88c9fb</guid>

					<description><![CDATA[Part 1: Creating the Source of Truth for ImpressionsBy: Tulika BhattImagine scrolling through Netflix, where each movie poster or promotional banner competes for your attention. Every image you hover over isn’t just a visual placeholder; it’s a critica...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Over 700 million events/second: How we make sense of too much data</title>
		<link>https://noise.getoto.net/2025/01/27/over-700-million-events-second-how-we-make-sense-of-too-much-data/</link>
		
		<dc:creator><![CDATA[Constantin Pan]]></dc:creator>
		<pubDate>Mon, 27 Jan 2025 14:00:00 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Bugs]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[deep dive]]></category>
		<category><![CDATA[Go]]></category>
		<category><![CDATA[GraphQL]]></category>
		<category><![CDATA[Sampling]]></category>
		<category><![CDATA[sql]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=f9a05ae9fe6026e15a99e751b3214ea6</guid>

					<description><![CDATA[Here we explain how we made our data pipeline scale to 700 million events per second while becoming more resilient than ever before. We share some math behind our approach and some of the designs of]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Cloudflare incident on November 14, 2024, resulting in lost logs</title>
		<link>https://noise.getoto.net/2024/11/26/cloudflare-incident-on-november-14-2024-resulting-in-lost-logs/</link>
		
		<dc:creator><![CDATA[Jamie Herre]]></dc:creator>
		<pubDate>Tue, 26 Nov 2024 16:00:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Log Push]]></category>
		<category><![CDATA[Logs]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=f57b19fc13ca993f681ca603e01857ad</guid>

					<description><![CDATA[On November 14, 2024, Cloudflare experienced a Cloudflare Logs outage, impacting the majority of customers using these products. During the ~3.5 hours that these services were impacted, about 55% of the logs we normally send to customers were not sent and were lost. The details of what went wrong and why are interesting both for customers and practitioners.]]></description>
		
		
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			</item>
		<item>
		<title>Maestro: Netflix’s Workflow Orchestrator</title>
		<link>https://noise.getoto.net/2024/07/22/maestro-netflixs-workflow-orchestrator/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Mon, 22 Jul 2024 17:38:23 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[distributed-systems]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Orchestration]]></category>
		<category><![CDATA[workflow]]></category>
		<guid isPermaLink="false">https://medium.com/p/ee13a06f9c78</guid>

					<description><![CDATA[By Jun He, Natallia Dzenisenka, Praneeth Yenugutala, Yingyi Zhang, and Anjali NorwoodTL;DRWe are thrilled to announce that the Maestro source code is now open to the public! Please visit the Maestro GitHub repository to get started. If you find it usef...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>A Recap of the Data Engineering Open Forum at Netflix</title>
		<link>https://noise.getoto.net/2024/06/20/a-recap-of-the-data-engineering-open-forum-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Thu, 20 Jun 2024 15:01:27 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[data-engineering]]></category>
		<category><![CDATA[software engineering]]></category>
		<category><![CDATA[Technology]]></category>
		<guid isPermaLink="false">https://medium.com/p/6b4d4410b88f</guid>

					<description><![CDATA[A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024The Data Engineering Open Forum at Netflix on April 18th, 2024.At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role...]]></description>
		
		
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			</item>
		<item>
		<title>Our First Netflix Data Engineering Summit</title>
		<link>https://noise.getoto.net/2023/12/14/our-first-netflix-data-engineering-summit/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Thu, 14 Dec 2023 16:54:11 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[data-engineer]]></category>
		<category><![CDATA[data-engineering]]></category>
		<category><![CDATA[data-visualization]]></category>
		<guid isPermaLink="false">https://medium.com/p/f326b0589102</guid>

					<description><![CDATA[Holden Karau Elizabeth Stone Pedro Duarte Chris Stephens Pallavi Phadnis Lee Woodridge Mark Cho Guil Pires Sujay Jain Tristan Reid Senthilnathan Athinarayanan Bharath Mummadisetty Abhinaya Shetty Judit Lantos Amanuel Kahsay Dao Mi Mick Dreeling Chris C...]]></description>
		
		
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		<item>
		<title>Sliding window rate limits in distributed systems</title>
		<link>https://noise.getoto.net/2023/12/14/sliding-window-rate-limits-in-distributed-systems/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Thu, 14 Dec 2023 00:00:10 +0000</pubDate>
				<category><![CDATA[Big Data]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[distributed-systems]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Frequency capping]]></category>
		<category><![CDATA[Rate-limiting]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/frequency-capping</guid>

					<description><![CDATA[Like many other companies, Grab uses marketing communications to notify users of promotions or other news. If a user receives these notifications from multiple companies, it would be a form of information overload and they might even start considering ...]]></description>
		
		
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