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	<title>Amazon FSx for Lustre &#8211; Noise</title>
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		<title>AWS Weekly Roundup: Amazon Aurora DSQL, MCP Servers, Amazon FSx, AI on EKS, and more (June 2, 2025)</title>
		<link>https://noise.getoto.net/2025/06/02/aws-weekly-roundup-amazon-aurora-dsql-mcp-servers-amazon-fsx-ai-on-eks-and-more-june-2-2025/</link>
		
		<dc:creator><![CDATA[Prasad Rao]]></dc:creator>
		<pubDate>Mon, 02 Jun 2025 15:00:32 +0000</pubDate>
				<category><![CDATA[Amazon Aurora]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Amazon FSx for NetApp ONTAP]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Network Firewall]]></category>
		<category><![CDATA[Cloud Cost Optimization]]></category>
		<category><![CDATA[DSQL]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[launch]]></category>
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		<category><![CDATA[Week in Review]]></category>
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					<description><![CDATA[It’s AWS Summit Season! AWS Summits are free in-person events that take place across the globe in major cities, bringing cloud expertise to local communities. Each AWS Summit features keynote presentations highlighting the latest innovations, technical sessions, live demos, and interactive workshops led by Amazon Web Services (AWS) experts. Last week, events took place at […]]]></description>
		
		
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		<title>Amazon FSx for Lustre launches new storage class with the lowest-cost and only fully elastic Lustre ﬁle storage</title>
		<link>https://noise.getoto.net/2025/05/29/amazon-fsx-for-lustre-launches-new-storage-class-with-the-lowest-cost-and-only-fully-elastic-lustre-%ef%ac%81le-storage/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Thu, 29 May 2025 20:55:51 +0000</pubDate>
				<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[announcements]]></category>
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					<description><![CDATA[Amazon FSx for Lustre Intelligent-Tiering storage class provides cost-effective, virtually unlimited elastic file storage for ML and HPC workloads that automatically optimizes costs by tiering data based on access frequency.]]></description>
		
		
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		<title>Amazon FSx for Lustre increases throughput to GPU instances by up to 12x</title>
		<link>https://noise.getoto.net/2024/11/28/amazon-fsx-for-lustre-increases-throughput-to-gpu-instances-by-up-to-12x/</link>
		
		<dc:creator><![CDATA[Danilo Poccia]]></dc:creator>
		<pubDate>Wed, 27 Nov 2024 22:13:37 +0000</pubDate>
				<category><![CDATA[Amazon FSx]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[Amazon FSx for Lustre now features Elastic Fabric Adapter and NVIDIA GPUDirect Storage for up to 12x higher throughput to GPUs, unlocking new possibilities in deep learning, autonomous vehicles, and HPC workloads.]]></description>
		
		
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		<title>New — File Release for Amazon FSx for Lustre</title>
		<link>https://noise.getoto.net/2023/08/09/new-file-release-for-amazon-fsx-for-lustre/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Wed, 09 Aug 2023 16:23:58 +0000</pubDate>
				<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[Amazon FSx for Lustre provides fully managed shared storage with the scalability and high performance of the open-source Lustre file systems to support your Linux-based workloads. FSx for Lustre is for workloads where storage speed and throughput matter. This is because FSx for Lustre helps you avoid storage bottlenecks, increase utilization of compute resources, and […]]]></description>
		
		
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		<item>
		<title>Designing a hybrid AI/ML data access strategy with Amazon SageMaker</title>
		<link>https://noise.getoto.net/2023/07/10/designing-a-hybrid-ai-ml-data-access-strategy-with-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Franklin Aguinaldo]]></dc:creator>
		<pubDate>Mon, 10 Jul 2023 16:05:42 +0000</pubDate>
				<category><![CDATA[Amazon Elastic File System (EFS)]]></category>
		<category><![CDATA[Amazon File Cache]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS DataSync]]></category>
		<category><![CDATA[AWS Direct Connect]]></category>
		<category><![CDATA[AWS Storage Gateway]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=8c8244c95a854f105af85ca136a41fad</guid>

					<description><![CDATA[Over time, many enterprises have built an on-premises cluster of servers, accumulating data, and then procuring more servers and storage. They often begin their ML journey by experimenting locally on their laptops. Investment in artificial intelligence (AI) is at a different stage in every business organization. Some remain completely on-premises, others are hybrid (both on-premises […]]]></description>
		
		
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		<title>Genomics workflows, Part 5: automated benchmarking</title>
		<link>https://noise.getoto.net/2023/03/24/genomics-workflows-part-5-automated-benchmarking/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Fri, 24 Mar 2023 16:59:30 +0000</pubDate>
				<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Batch]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=520a2cca0339da04d0d19c46450e8133</guid>

					<description><![CDATA[Launching and running genomics workflows can take hours and involves large pools of compute instances that process data at a petabyte scale. Benchmarking helps you evaluate workflow performance and discover faster and cheaper ways of running them. In practice, performance evaluations happen irregularly because of the associated heavy lifting. In this blog post, we discuss […]]]></description>
		
		
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		<item>
		<title>Improve the performance of Apache Iceberg’s metadata file operations using Amazon FSx for Lustre on Amazon EMR</title>
		<link>https://noise.getoto.net/2023/01/12/improve-the-performance-of-apache-icebergs-metadata-file-operations-using-amazon-fsx-for-lustre-on-amazon-emr/</link>
		
		<dc:creator><![CDATA[Rajarshi Sarkar]]></dc:creator>
		<pubDate>Thu, 12 Jan 2023 19:23:43 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Analytics]]></category>
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					<description><![CDATA[Apache Iceberg is an open table format for large datasets in Amazon Simple Storage Service (Amazon S3), and provides fast query performance over large tables, atomic commits, concurrent writes, and SQL-compatible table evolution. With Amazon EMR 6.5+, you can use Apache Spark on EMR clusters with the Iceberg table format. Iceberg helps data engineers manage […]]]></description>
		
		
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		<item>
		<title>AWS Week in Review – September 19, 2022</title>
		<link>https://noise.getoto.net/2022/09/19/aws-week-in-review-september-19-2022/</link>
		
		<dc:creator><![CDATA[Jeff Barr]]></dc:creator>
		<pubDate>Mon, 19 Sep 2022 19:13:12 +0000</pubDate>
				<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Elastic Container Service]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Amazon Lex]]></category>
		<category><![CDATA[Amazon WorkSpaces]]></category>
		<category><![CDATA[AWS Cloud Development Kit]]></category>
		<category><![CDATA[AWS Config]]></category>
		<category><![CDATA[AWS Outposts]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[Week in Review]]></category>
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					<description><![CDATA[Things are heating up in Seattle, with preparation for AWS re:Invent 2022 well underway. Later this month the entire News Blog team will participate in our now-legendary “speed storming” event. Over the course of three or four days, each of the AWS service teams with a launch in the works for re:Invent will give us […]]]></description>
		
		
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		<item>
		<title>Run Apache Spark with Amazon EMR on EKS backed by Amazon FSx for Lustre storage</title>
		<link>https://noise.getoto.net/2022/09/14/run-apache-spark-with-amazon-emr-on-eks-backed-by-amazon-fsx-for-lustre-storage/</link>
		
		<dc:creator><![CDATA[Vara Bonthu]]></dc:creator>
		<pubDate>Wed, 14 Sep 2022 15:44:27 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Analytics]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=caa3b71b6728bd17ef9719eb1b9f0421</guid>

					<description><![CDATA[Traditionally, Spark workloads have been run on a dedicated setup like a Hadoop stack with YARN or MESOS as a resource manager. Starting from Apache Spark 2.3, Spark added support for Kubernetes as a resource manager. The new Kubernetes scheduler natively supports the submission of Spark jobs to a Kubernetes cluster. Spark on Kubernetes provides […]]]></description>
		
		
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		<title>Migrating petabytes of data from on-premises file systems to Amazon FSx for Lustre</title>
		<link>https://noise.getoto.net/2022/03/18/migrating-petabytes-of-data-from-on-premises-file-systems-to-amazon-fsx-for-lustre/</link>
		
		<dc:creator><![CDATA[Vimala Pydi]]></dc:creator>
		<pubDate>Fri, 18 Mar 2022 17:03:44 +0000</pubDate>
				<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS DataSync]]></category>
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					<description><![CDATA[Many organizations use the Lustre filesystem for Linux-based applications that require petabytes of data and high-performance storage. Lustre file systems are used in machine learning (ML), high performance computing (HPC), big data, and financial analytics. Many such high-performance workloads are being migrated to Amazon Web Services (AWS) to take advantage of the scalability, elasticity, and […]]]></description>
		
		
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		<item>
		<title>Enhanced Amazon S3 Integration for Amazon FSx for Lustre</title>
		<link>https://noise.getoto.net/2021/12/01/enhanced-amazon-s3-integration-for-amazon-fsx-for-lustre/</link>
		
		<dc:creator><![CDATA[Sébastien Stormacq]]></dc:creator>
		<pubDate>Wed, 01 Dec 2021 00:21:40 +0000</pubDate>
				<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[news]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=d862aadbfc6dde2126fd85444fd3fbd3</guid>

					<description><![CDATA[Today, we are announcing two additional capabilities of Amazon FSx for Lustre. First, a full bi-directional synchronization of your file systems with Amazon Simple Storage Service (Amazon S3), including deleted files and objects. Second, the ability to synchronize your file systems with multiple S3 buckets or prefixes. Lustre is a large scale, distributed parallel file […]]]></description>
		
		
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		<item>
		<title>Fire Dynamics Simulation CFD workflow using AWS ParallelCluster, Elastic Fabric Adapter, Amazon FSx for Lustre and NICE DCV</title>
		<link>https://noise.getoto.net/2020/10/19/fire-dynamics-simulation-cfd-workflow-using-aws-parallelcluster-elastic-fabric-adapter-amazon-fsx-for-lustre-and-nice-dcv/</link>
		
		<dc:creator><![CDATA[Emma White]]></dc:creator>
		<pubDate>Mon, 19 Oct 2020 17:09:23 +0000</pubDate>
				<category><![CDATA[Amazon FSx for Lustre]]></category>
		<category><![CDATA[AWS ParallelCluster]]></category>
		<category><![CDATA[Compute]]></category>
		<category><![CDATA[Elastic Fabric Adapter]]></category>
		<category><![CDATA[high performance computing]]></category>
		<category><![CDATA[HPC]]></category>
		<category><![CDATA[NICE DCV]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[This post was written by By Kevin Tuil, AWS HPC consultant&#160; Modeling fires is key for many industries, from the design of new buildings, defining evacuation procedures for trains, planes and ships, and even the spread of wildfires. Modeling these fires is complex. It involves both the need to model the three-dimensional unsteady turbulent flow [&#8230;]]]></description>
		
		
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