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	<title>apache flink &#8211; Noise</title>
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		<title>Achieve full control over your data encryption using customer managed keys in Amazon Managed Service for Apache Flink</title>
		<link>https://noise.getoto.net/2025/09/05/achieve-full-control-over-your-data-encryption-using-customer-managed-keys-in-amazon-managed-service-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Fri, 05 Sep 2025 20:33:20 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Kinesis Data Analytics]]></category>
		<category><![CDATA[Security, Identity & Compliance]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Encryption of both data at rest and in transit is a non-negotiable feature for most organizations. Furthermore, organizations operating in highly regulated and security-sensitive environments—such as those in the financial sector—often require full control over the cryptographic keys used for their workloads. Amazon Managed Service for Apache Flink makes it straightforward to process real-time data […]]]></description>
		
		
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		<title>Deep dive into the Amazon Managed Service for Apache Fink application lifecycle – Part 2</title>
		<link>https://noise.getoto.net/2025/09/04/deep-dive-into-the-amazon-managed-service-for-apache-fink-application-lifecycle-part-2/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Wed, 03 Sep 2025 21:21:35 +0000</pubDate>
				<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
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		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Expert (400)]]></category>
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					<description><![CDATA[In Part 1 of this series, we discussed fundamental operations to control the lifecycle of your Amazon Managed Service for Apache Flink application. In this post, we explore failure scenarios that can happen during normal operations or when you deploy a change or scale the application, and how to monitor operations to detect and recover when something goes wrong.]]></description>
		
		
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		<title>Deep dive into the Amazon Managed Service for Apache Fink application lifecycle – Part 1</title>
		<link>https://noise.getoto.net/2025/09/04/deep-dive-into-the-amazon-managed-service-for-apache-fink-application-lifecycle-part-1/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Wed, 03 Sep 2025 21:21:23 +0000</pubDate>
				<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Expert (400)]]></category>
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					<description><![CDATA[In this two-part series, we explore what happens during an application’s lifecycle. This post covers core concepts and the application workflow during normal operations. In Part 2, we look at potential failures, how to detect them through monitoring, and ways to quickly resolve issues when they occur.]]></description>
		
		
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		<title>Unlock self-serve streaming SQL with Amazon Managed Service for Apache Flink</title>
		<link>https://noise.getoto.net/2025/05/28/unlock-self-serve-streaming-sql-with-amazon-managed-service-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Sofie Zilberman]]></dc:creator>
		<pubDate>Wed, 28 May 2025 10:58:29 +0000</pubDate>
				<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Experience-Based Acceleration]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we present Riskified’s journey toward enabling self-service streaming SQL pipelines. We walk through the motivations behind the shift from Confluent ksqlDB to Apache Flink, the architecture Riskified built using Amazon Managed Service for Apache Flink, the technical challenges they faced, and the solutions that helped them make streaming accessible, scalable, and production-ready.]]></description>
		
		
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		<title>Process millions of observability events with Apache Flink and write directly to Prometheus</title>
		<link>https://noise.getoto.net/2025/04/09/process-millions-of-observability-events-with-apache-flink-and-write-directly-to-prometheus/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Wed, 09 Apr 2025 19:54:00 +0000</pubDate>
				<category><![CDATA[Amazon Managed Grafana]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Amazon Managed Service for Prometheus]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Internet of Things]]></category>
		<category><![CDATA[open source]]></category>
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					<description><![CDATA[In this post, we explain how the new connector works. We also show how you can manage your Prometheus metrics data cardinality by preprocessing raw data with Flink to build real-time observability with Amazon Managed Service for Prometheus and Amazon Managed Grafana.]]></description>
		
		
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		<title>How PostNL processes billions of IoT events with Amazon Managed Service for Apache Flink</title>
		<link>https://noise.getoto.net/2024/07/15/how-postnl-processes-billions-of-iot-events-with-amazon-managed-service-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Çağrı Çakır]]></dc:creator>
		<pubDate>Mon, 15 Jul 2024 16:55:39 +0000</pubDate>
				<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Internet of Things]]></category>
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		<category><![CDATA[Kinesis Data Analytics]]></category>
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					<description><![CDATA[This post is co-written with Çağrı Çakır and Özge Kavalcı from PostNL. PostNL is the designated universal postal service provider for the Netherlands and has three main business units offering postal delivery, parcel delivery, and logistics solutions for ecommerce and cross-border solutions. With 5,800 retail points, 11,000 mailboxes, and over 900 automated parcel lockers, the […]]]></description>
		
		
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		<title>Krones real-time production line monitoring with Amazon Managed Service for Apache Flink</title>
		<link>https://noise.getoto.net/2024/03/28/krones-real-time-production-line-monitoring-with-amazon-managed-service-for-apache-flink/</link>
		
		<dc:creator><![CDATA[Florian Mair]]></dc:creator>
		<pubDate>Thu, 28 Mar 2024 16:21:06 +0000</pubDate>
				<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Amazon Kinesis Streams]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Kinesis Data Streams]]></category>
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					<description><![CDATA[Krones provides breweries, beverage bottlers, and food producers all over the world with individual machines and complete production lines. This post shows how Krones built a streaming solution to monitor their lines, based on Amazon Kinesis and Amazon Managed Service for Apache Flink. These fully managed services reduce the complexity of building streaming applications with Apache Flink. Managed Service for Apache Flink manages the underlying Apache Flink components that provide durable application state, metrics, logs, and more, and Kinesis enables you to cost-effectively process streaming data at any scale.]]></description>
		
		
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		<title>Amazon Managed Service for Apache Flink now supports Apache Flink version 1.18</title>
		<link>https://noise.getoto.net/2024/03/18/amazon-managed-service-for-apache-flink-now-supports-apache-flink-version-1-18/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Mon, 18 Mar 2024 21:03:18 +0000</pubDate>
				<category><![CDATA[Amazon Kinesis Analytics]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Apache Flink is an open source distributed processing engine, offering powerful programming interfaces for both stream and batch processing, with first-class support for stateful processing and event time semantics. Apache Flink supports multiple programming languages, Java, Python, Scala, SQL, and multiple APIs with different level of abstraction, which can be used interchangeably in the same […]]]></description>
		
		
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		<title>Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 2</title>
		<link>https://noise.getoto.net/2023/09/14/optimize-checkpointing-in-your-amazon-managed-service-for-apache-flink-applications-with-buffer-debloating-and-unaligned-checkpoints-part-2/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Thu, 14 Sep 2023 18:36:37 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Kinesis Data Analyltics]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
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					<description><![CDATA[This post is a continuation of a two-part series. In the first part, we delved into Apache Flink‘s internal mechanisms for checkpointing, in-flight data buffering, and handling backpressure. We covered these concepts in order to understand how buffer debloating and unaligned checkpoints allow us to enhance performance for specific conditions in Apache Flink applications. In […]]]></description>
		
		
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		<title>Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 1</title>
		<link>https://noise.getoto.net/2023/09/14/optimize-checkpointing-in-your-amazon-managed-service-for-apache-flink-applications-with-buffer-debloating-and-unaligned-checkpoints-part-1/</link>
		
		<dc:creator><![CDATA[Lorenzo Nicora]]></dc:creator>
		<pubDate>Thu, 14 Sep 2023 18:36:05 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Kinesis Data Analyltics]]></category>
		<category><![CDATA[Amazon Managed Service for Apache Flink]]></category>
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					<description><![CDATA[This post is the first of a two-part series regarding checkpointing mechanisms and in-flight data buffering. In this first part, we explain some of the fundamental Apache Flink internals and cover the buffer debloating feature. In the second part, we focus on unaligned checkpoints. Apache Flink is an open-source distributed engine for stateful processing over […]]]></description>
		
		
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		<title>Build a data lake with Apache Flink on Amazon EMR</title>
		<link>https://noise.getoto.net/2023/01/27/build-a-data-lake-with-apache-flink-on-amazon-emr/</link>
		
		<dc:creator><![CDATA[Jianwei Li]]></dc:creator>
		<pubDate>Fri, 27 Jan 2023 21:05:02 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Apache Hudi]]></category>
		<category><![CDATA[Apache Iceberg]]></category>
		<category><![CDATA[AWS Glue]]></category>
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					<description><![CDATA[To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep […]]]></description>
		
		
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		<title>Optimizing Apache Flink on Amazon EKS using Amazon EC2 Spot Instances</title>
		<link>https://noise.getoto.net/2021/11/11/optimizing-apache-flink-on-amazon-eks-using-amazon-ec2-spot-instances/</link>
		
		<dc:creator><![CDATA[Emma White]]></dc:creator>
		<pubDate>Thu, 11 Nov 2021 19:13:13 +0000</pubDate>
				<category><![CDATA[Amazon EC2 Spot Instances]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Compute]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[This post is written by Kinnar Sen, Senior EC2 Spot Specialist Solutions Architect Apache Flink is a distributed data processing engine for stateful computations for both batch and stream data sources. Flink supports event time semantics for out-of-order events, exactly-once semantics, backpressure control, and optimized APIs. Flink has connectors for third-party data sources and AWS […]]]></description>
		
		
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		<title>Real-Time In-Stream Inference with AWS Kinesis, SageMaker &#038; Apache Flink</title>
		<link>https://noise.getoto.net/2020/11/27/real-time-in-stream-inference-with-aws-kinesis-sagemaker-apache-flink/</link>
		
		<dc:creator><![CDATA[Shawn Sachdev]]></dc:creator>
		<pubDate>Fri, 27 Nov 2020 17:50:10 +0000</pubDate>
				<category><![CDATA[Amazon API Gateway]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Data Analytics]]></category>
		<category><![CDATA[data streaming]]></category>
		<category><![CDATA[Kinesis Data Analytics]]></category>
		<category><![CDATA[Kinesis Data Streams]]></category>
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					<description><![CDATA[As businesses race to digitally transform, the challenge is to cope with the amount of data, and the value of that data diminishes over time. The challenge is to analyze, learn, and infer from real-time data to predict future states, as well as to detect anomalies and get accurate results. In this blog post, we&#8217;ll [&#8230;]]]></description>
		
		
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