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	<title>AIOps &#8211; Noise</title>
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		<title>Automate SageMaker HyperPod incident triage and root-cause-analysis with AWS DevOps Agent</title>
		<link>https://noise.getoto.net/2026/08/10/automate-sagemaker-hyperpod-incident-triage-and-root-cause-analysis-with-aws-devops-agent/</link>
		
		<dc:creator><![CDATA[Tomonori Shimomura]]></dc:creator>
		<pubDate>Mon, 10 Aug 2026 11:29:17 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon SageMaker HyperPod]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Developer Tools]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[Expert (400)]]></category>
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					<description><![CDATA[Introduction Large-scale machine learning workloads: training, fine-tuning, and inference run on clusters of hundreds to thousands of GPU instances for days or weeks at a stretch. Keeping operational visibility across a fleet of this size is a constant challenge: hardware health events, node lifecycle transitions, capacity fluctuations, and workload-level issues appear in the event stream around […]]]></description>
		
		
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		<title>Diagnose EKS Node Issues Faster with AWS DevOps Agent and Custom MCP</title>
		<link>https://noise.getoto.net/2026/06/11/diagnose-eks-node-issues-faster-with-aws-devops-agent-and-custom-mcp/</link>
		
		<dc:creator><![CDATA[Shyam Kulkarni]]></dc:creator>
		<pubDate>Thu, 11 Jun 2026 20:43:08 +0000</pubDate>
				<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon EKS]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[EKS]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[SSM Agent Systems Manager]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[AWS DevOps Agent can investigate a growing range of production incidents autonomously. It diagnoses CrashLoopBackOff failures, traces ConfigMap deletions through audit logs, and correlates Amazon CloudWatch metrics with cluster events — all without human intervention. But AWS DevOps Agent has a visibility boundary. When the data it needs lives outside its native integrations — on […]]]></description>
		
		
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		<title>Directing ML-powered Operational Insights from Amazon DevOps Guru to your Datadog event stream</title>
		<link>https://noise.getoto.net/2023/07/13/directing-ml-powered-operational-insights-from-amazon-devops-guru-to-your-datadog-event-stream/</link>
		
		<dc:creator><![CDATA[Bineesh Ravindran]]></dc:creator>
		<pubDate>Thu, 13 Jul 2023 11:43:36 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon DevOps Guru]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS CLI]]></category>
		<category><![CDATA[AWS Serverless Application Model (SAM)]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[Integration & Automation]]></category>
		<category><![CDATA[observability]]></category>
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					<description><![CDATA[Amazon DevOps Guru is a fully managed AIOps service that uses machine learning (ML) to quickly identify when applications are behaving outside of their normal operating patterns and generates insights from its findings. These insights generated by DevOps Guru can be used to alert on-call teams to react to anomalies for business mission critical workloads. […]]]></description>
		
		
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		<title>DevSecOps with Amazon CodeGuru Reviewer CLI and Bitbucket Pipelines</title>
		<link>https://noise.getoto.net/2023/04/28/devsecops-with-amazon-codeguru-reviewer-cli-and-bitbucket-pipelines/</link>
		
		<dc:creator><![CDATA[Bineesh Ravindran]]></dc:creator>
		<pubDate>Fri, 28 Apr 2023 15:25:37 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon CodeGuru]]></category>
		<category><![CDATA[Amazon CodeGuru Reviewer]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[automation]]></category>
		<category><![CDATA[AWS CLI]]></category>
		<category><![CDATA[Bitbucket]]></category>
		<category><![CDATA[Code Review]]></category>
		<category><![CDATA[Developer Tools]]></category>
		<category><![CDATA[devops]]></category>
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					<description><![CDATA[DevSecOps refers to a set of best practices that integrate security controls into the continuous integration and delivery (CI/CD) workflow. One of the first controls is Static Application Security Testing (SAST). SAST tools run on every code change and search for potential security vulnerabilities before the code is executed for the first time. Catching security […]]]></description>
		
		
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		<title>Monitoring Amazon DevOps Guru insights using Amazon Managed Grafana</title>
		<link>https://noise.getoto.net/2023/04/19/monitoring-amazon-devops-guru-insights-using-amazon-managed-grafana/</link>
		
		<dc:creator><![CDATA[MJ Kubba]]></dc:creator>
		<pubDate>Wed, 19 Apr 2023 19:27:40 +0000</pubDate>
				<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon DevOps Guru]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Managed Grafana]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[DevOps Guru]]></category>
		<category><![CDATA[monitoring]]></category>
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					<description><![CDATA[As organizations operate day-to-day, having insights into their cloud infrastructure state can be crucial for the durability and availability of their systems. Industry research estimates[1] that downtime costs small businesses around $427 per minute of downtime, and medium to large businesses an average of $9,000 per minute of downtime. Amazon DevOps Guru customers want to […]]]></description>
		
		
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		<title>Publish Amazon DevOps Guru Insights to ServiceNow for Incident Management</title>
		<link>https://noise.getoto.net/2023/03/29/publish-amazon-devops-guru-insights-to-servicenow-for-incident-management/</link>
		
		<dc:creator><![CDATA[Abdullahi Olaoye]]></dc:creator>
		<pubDate>Tue, 28 Mar 2023 22:06:12 +0000</pubDate>
				<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon DevOps Guru]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[automation]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=8f38e8368700badc3a5ce01c9d9bba33</guid>

					<description><![CDATA[Amazon DevOps Guru is a fully managed AIOps service that uses machine learning (ML) to quickly identify when applications are behaving outside of their normal operating patterns and generates insights from its findings. These insights generated by Amazon DevOps Guru can be used to alert on-call teams to react to anomalies for mission critical workloads. […]]]></description>
		
		
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		<title>Gaining operational insights with AIOps using Amazon DevOps Guru</title>
		<link>https://noise.getoto.net/2021/02/26/gaining-operational-insights-with-aiops-using-amazon-devops-guru/</link>
		
		<dc:creator><![CDATA[Nikunj Vaidya]]></dc:creator>
		<pubDate>Fri, 26 Feb 2021 00:40:55 +0000</pubDate>
				<category><![CDATA[AIOps]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[DevOps Guru]]></category>
		<category><![CDATA[observability]]></category>
		<category><![CDATA[Operations]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon DevOps Guru offers a fully managed AIOps platform service that enables developers and operators to improve application availability and resolve operational issues faster. It minimizes manual effort by leveraging machine learning (ML) powered recommendations. Its ML models take advantage of AWS’s expertise in operating highly available applications for the world’s largest e-commerce business for […]]]></description>
		
		
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