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	<title>Gaurav Sharma &#8211; Noise</title>
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		<title>Building medallion architecture with Iceberg materialized views in Amazon SageMaker</title>
		<link>https://noise.getoto.net/2026/09/02/building-medallion-architecture-with-iceberg-materialized-views-in-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Gaurav Sharma]]></dc:creator>
		<pubDate>Wed, 02 Sep 2026 18:34:32 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[With Apache Iceberg materialized views in Amazon SageMaker, you can build a Bronze, Silver, and Gold medallion architecture as three SQL statements. This declarative approach folds transformation, orchestration, and incremental processing into per-layer definitions, with no ETL jobs, orchestrators, or change-data-capture code to maintain.]]></description>
		
		
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		<title>Define per-team resource limits for big data workloads using Amazon EMR Serverless</title>
		<link>https://noise.getoto.net/2023/10/05/define-per-team-resource-limits-for-big-data-workloads-using-amazon-emr-serverless/</link>
		
		<dc:creator><![CDATA[Gaurav Sharma]]></dc:creator>
		<pubDate>Thu, 05 Oct 2023 17:18:30 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[EMR Serverless]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Customers face a challenge when distributing cloud resources between different teams running workloads such as development, testing, or production. The resource distribution challenge also occurs when you have different line-of-business users. The objective is not only to ensure sufficient resources be consistently available to production workloads and critical teams, but also to prevent adhoc jobs […]]]></description>
		
		
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