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	<title>Antonio Vespoli &#8211; Noise</title>
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		<title>Real-time time series anomaly detection for streaming applications on Amazon Kinesis Data Analytics</title>
		<link>https://noise.getoto.net/2023/05/23/real-time-time-series-anomaly-detection-for-streaming-applications-on-amazon-kinesis-data-analytics/</link>
		
		<dc:creator><![CDATA[Antonio Vespoli]]></dc:creator>
		<pubDate>Tue, 23 May 2023 20:11:17 +0000</pubDate>
				<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Kinesis Data Analytics]]></category>
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					<description><![CDATA[Detecting anomalies in real time from high-throughput streams is key for informing on timely decisions in order to adapt and respond to unexpected scenarios. Stream processing frameworks such as Apache Flink empower users to design systems that can ingest and process continuous flows of data at scale. In this post, we present a streaming time […]]]></description>
		
		
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