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	<title>Jeremy Ber &#8211; Noise</title>
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		<title>In-place version upgrades for applications on Amazon Managed Service for Apache Flink now supported</title>
		<link>https://noise.getoto.net/2024/05/23/in-place-version-upgrades-for-applications-on-amazon-managed-service-for-apache-flink-now-supported/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Thu, 23 May 2024 16:10:44 +0000</pubDate>
				<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Managed Service for Apache Flink is a fully managed, serverless experience in running Apache Flink applications, and now supports Apache Flink 1.18.1, the latest released version of Apache Flink at the time of writing. In this post, we explore in-place version upgrades, a new feature offered by Managed Service for Apache Flink. We provide guidance on getting started and offer detailed insights into the feature. Later, we deep dive into how the feature works and some sample use cases.]]></description>
		
		
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		<title>Real-time cost savings for Amazon Managed Service for Apache Flink</title>
		<link>https://noise.getoto.net/2024/03/11/real-time-cost-savings-for-amazon-managed-service-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Mon, 11 Mar 2024 17:05:15 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[When running Apache Flink applications on Amazon Managed Service for Apache Flink, you have the unique benefit of taking advantage of its serverless nature. This means that cost-optimization exercises can happen at any time—they no longer need to happen in the planning phase. With Managed Service for Apache Flink, you can add and remove compute […]]]></description>
		
		
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		<title>Real-time inference using deep learning within Amazon Kinesis Data Analytics for Apache Flink</title>
		<link>https://noise.getoto.net/2023/06/01/real-time-inference-using-deep-learning-within-amazon-kinesis-data-analytics-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Thu, 01 Jun 2023 19:57:29 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Kinesis Data Analytics]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Apache Flink is a framework and distributed processing engine for stateful computations over data streams. Amazon Kinesis Data Analytics for Apache Flink is a fully managed service that enables you to use an Apache Flink application to process streaming data. The Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. […]]]></description>
		
		
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		<title>Build highly available streams with Amazon Kinesis Data Streams</title>
		<link>https://noise.getoto.net/2023/01/17/build-highly-available-streams-with-amazon-kinesis-data-streams/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Tue, 17 Jan 2023 18:52:41 +0000</pubDate>
				<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Kinesis Data Streams]]></category>
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					<description><![CDATA[Many use cases are moving towards a real-time data strategy due to demand for real-time insights, low-latency response times, and the ability to adapt to the changing needs of end-users. For this type of workload, you can use Amazon Kinesis Data Streams to seamlessly provision, store, write, and read data in a streaming fashion. With […]]]></description>
		
		
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		<title>Query your data streams interactively using Kinesis Data Analytics Studio and Python</title>
		<link>https://noise.getoto.net/2022/04/13/query-your-data-streams-interactively-using-kinesis-data-analytics-studio-and-python/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Wed, 13 Apr 2022 15:06:33 +0000</pubDate>
				<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Kinesis Data Analytics]]></category>
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					<description><![CDATA[Amazon Kinesis Data Analytics Studio makes it easy for customers to analyze streaming data in real time, as well as build stream processing applications powered by Apache Flink using standard SQL, Python, and Scala. Just a few clicks in the AWS Management console lets customers launch a serverless notebook to query data streams and get […]]]></description>
		
		
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		<title>Kinesis Data Firehose now supports dynamic partitioning to Amazon S3</title>
		<link>https://noise.getoto.net/2021/09/03/kinesis-data-firehose-now-supports-dynamic-partitioning-to-amazon-s3/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Fri, 03 Sep 2021 02:27:18 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Kinesis Data Firehose]]></category>
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					<description><![CDATA[Amazon Kinesis Data Firehose provides a convenient way to reliably load streaming data into data lakes, data stores, and analytics services. It can capture, transform, and deliver streaming data to Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon Elasticsearch Service, generic HTTP endpoints, and service providers like Datadog, New Relic, MongoDB, and Splunk. It […]]]></description>
		
		
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		<title>Top 10 Flink SQL queries to try in Amazon Kinesis Data Analytics Studio</title>
		<link>https://noise.getoto.net/2021/06/16/top-10-flink-sql-queries-to-try-in-amazon-kinesis-data-analytics-studio/</link>
		
		<dc:creator><![CDATA[Jeremy Ber]]></dc:creator>
		<pubDate>Wed, 16 Jun 2021 13:24:20 +0000</pubDate>
				<category><![CDATA[Kinesis Data Analytics]]></category>
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					<description><![CDATA[Amazon Kinesis Data Analytics Studio makes it easy to analyze streaming data in real time and build stream processing applications using standard SQL, Python, and Scala. With a few clicks on the AWS Management Console, you can launch a serverless notebook to query data streams and get results in seconds. Kinesis Data Analytics reduces the […]]]></description>
		
		
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