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	<title>Rostislav Markov &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/author/rostislav-markov/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
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		<title>Empower your teams with modern architecture governance</title>
		<link>https://noise.getoto.net/2025/04/21/empower-your-teams-with-modern-architecture-governance/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Mon, 21 Apr 2025 17:08:07 +0000</pubDate>
				<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Well-Architected]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Industries]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[Modern cloud architectures demand a new governance approach. In this post, we show how collaborative architecture oversight can transform team performance through automation, self-service platforms, and distributed decision-making.]]></description>
		
		
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			</item>
		<item>
		<title>Balance deployment speed and stability with DORA metrics</title>
		<link>https://noise.getoto.net/2024/07/31/balance-deployment-speed-and-stability-with-dora-metrics/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 31 Jul 2024 10:49:29 +0000</pubDate>
				<category><![CDATA[AWS Cloud Development Kit]]></category>
		<category><![CDATA[AWS CodePipeline]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[Development teams adopt DevOps practices to increase the speed and quality of their software delivery. The DevOps Research and Assessment (DORA) metrics provide a popular method to measure progress towards that outcome. Using four key metrics, senior leaders can assess the current state of team maturity and address areas of optimization. This blog post shows […]]]></description>
		
		
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		<item>
		<title>Genomics workflows, Part 7: analyze public RNA sequencing data using AWS HealthOmics</title>
		<link>https://noise.getoto.net/2024/06/05/genomics-workflows-part-7-analyze-public-rna-sequencing-data-using-aws-healthomics/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 05 Jun 2024 15:46:19 +0000</pubDate>
				<category><![CDATA[AWS HealthOmics]]></category>
		<category><![CDATA[genomics]]></category>
		<category><![CDATA[Life Sciences]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=17f7875bea5f71c3acabe8a2342865a9</guid>

					<description><![CDATA[Genomics workflows process petabyte-scale datasets on large pools of compute resources. In this blog post, we discuss how life science organizations can use Amazon Web Services (AWS) to run transcriptomic sequencing data analysis using public datasets. This allows users to quickly test research hypotheses against larger datasets in support of clinical diagnostics. We use AWS […]]]></description>
		
		
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			</item>
		<item>
		<title>Genomics workflows, Part 6: cost prediction</title>
		<link>https://noise.getoto.net/2024/04/24/genomics-workflows-part-6-cost-prediction/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 24 Apr 2024 16:43:35 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[genomics]]></category>
		<category><![CDATA[Industries]]></category>
		<category><![CDATA[Life Sciences]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Genomics workflows run on large pools of compute resources and take petabyte-scale datasets as inputs. Workflow runs can cost as much as hundreds of thousands of US dollars. Given this large scale, scientists want to estimate the projected cost of their genomics workflow runs before deciding to launch them. In Part 6 of this series, […]]]></description>
		
		
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			</item>
		<item>
		<title>Simplify document search at scale with intelligent search bot on AWS</title>
		<link>https://noise.getoto.net/2024/03/21/simplify-document-search-at-scale-with-intelligent-search-bot-on-aws/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Thu, 21 Mar 2024 16:32:28 +0000</pubDate>
				<category><![CDATA[Amazon Kendra]]></category>
		<category><![CDATA[Amazon Lex]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[Enterprise document management systems (EDMS) manage the lifecycle and distribution of documents. They often rely on keyword-based search functionality. However, it increasingly becomes hard to discover documents as such repositories grow to tens of thousands of items. In this blog, we discuss how Amazon Web Services (AWS) built an intelligent search bot on top of […]]]></description>
		
		
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		<item>
		<title>Reduce archive cost with serverless data archiving</title>
		<link>https://noise.getoto.net/2023/07/07/reduce-archive-cost-with-serverless-data-archiving/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Fri, 07 Jul 2023 14:57:21 +0000</pubDate>
				<category><![CDATA[Amazon API Gateway]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Database Migration Service]]></category>
		<category><![CDATA[AWS DataSync]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Snowball]]></category>
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					<description><![CDATA[For regulatory reasons, decommissioning core business systems in financial services and insurance (FSI) markets requires data to remain accessible years after the application is retired. Traditionally, FSI companies either outsourced data archiving to third-party service providers, which maintained application replicas, or purchased vendor software to query and visualize archival data. In this blog post, we […]]]></description>
		
		
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			</item>
		<item>
		<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>
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					<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>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Genomics workflows, Part 4: processing archival data</title>
		<link>https://noise.getoto.net/2023/01/04/genomics-workflows-part-4-processing-archival-data/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 04 Jan 2023 16:49:26 +0000</pubDate>
				<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon S3 Glacier]]></category>
		<category><![CDATA[Amazon S3 Glacier Deep Archive]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Fargate]]></category>
		<category><![CDATA[AWS Lambda]]></category>
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					<description><![CDATA[Genomics workflows analyze data at petabyte scale. After processing is complete, data is often archived in cold storage classes. In some cases, like studies on the association of DNA variants against larger datasets, archived data is needed for further processing. This means manually initiating the restoration of each archived object and monitoring the progress. Scientists […]]]></description>
		
		
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			</item>
		<item>
		<title>Genomics workflows, Part 3: automated workflow manager</title>
		<link>https://noise.getoto.net/2022/12/21/genomics-workflows-part-3-automated-workflow-manager/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 21 Dec 2022 14:27:25 +0000</pubDate>
				<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Batch]]></category>
		<category><![CDATA[AWS Fargate]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=20056909f754d3b40132f3bcd8e6e79c</guid>

					<description><![CDATA[Genomics workflows are high-performance computing workloads. Life-science research teams make use of various genomics workflows. With each invocation, they specify custom sets of data and processing steps, and translate them into commands. Furthermore, team members stay to monitor progress and troubleshoot errors, which can be cumbersome, non-differentiated, administrative work. In Part 3 of this series, […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Genomics workflows, Part 2: simplify Snakemake launches</title>
		<link>https://noise.getoto.net/2022/12/09/genomics-workflows-part-2-simplify-snakemake-launches/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Fri, 09 Dec 2022 14:20:29 +0000</pubDate>
				<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Elastic Container Registry]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
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					<description><![CDATA[Genomics workflows are high-performance computing workloads. In Part 1 of this series, we demonstrated how life-science research teams can focus on scientific discovery without the associated heavy lifting. We used regenie for large genome-wide association studies. Our design pattern built on AWS Step Functions with AWS Batch and Amazon FSx for Lustre. In Part 2, […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Automated launch of genomics workflows</title>
		<link>https://noise.getoto.net/2022/11/16/automated-launch-of-genomics-workflows/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 16 Nov 2022 15:13:50 +0000</pubDate>
				<category><![CDATA[Amazon Elastic Container Registry]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Batch]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
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					<description><![CDATA[Genomics workflows are high-performance computing workloads. Traditionally, they run on-premises with a collection of scripts. Scientists run and manage these workflows manually, which slows down the product development lifecycle. Scientists spend time to administer workflows and handle errors on a day-to-day basis. They also lack sufficient compute capacity on-premises. In this blog post, we demonstrate […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Maintain visibility over the use of cloud architecture patterns</title>
		<link>https://noise.getoto.net/2022/09/19/maintain-visibility-over-the-use-of-cloud-architecture-patterns/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Mon, 19 Sep 2022 15:46:53 +0000</pubDate>
				<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon QuickSight]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS CloudTrail]]></category>
		<category><![CDATA[AWS Service Catalog]]></category>
		<category><![CDATA[Kinesis Data Firehose]]></category>
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					<description><![CDATA[Cloud platform and enterprise architecture teams use architecture patterns to provide guidance for different use cases. Cloud architecture patterns are typically aggregates of multiple Amazon Web Services (AWS) resources, such as Elastic Load Balancing with Amazon Elastic Compute Cloud, or Amazon Relational Database Service with Amazon ElastiCache. In a large organization, cloud platform teams often […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Accelerate deployments on AWS with effective governance</title>
		<link>https://noise.getoto.net/2022/08/12/accelerate-deployments-on-aws-with-effective-governance/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Fri, 12 Aug 2022 15:38:23 +0000</pubDate>
				<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS CodeCommit]]></category>
		<category><![CDATA[AWS CodePipeline]]></category>
		<category><![CDATA[AWS Fargate]]></category>
		<category><![CDATA[AWS Service Catalog]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=2541d9bc600d78f7430274655e50ab7b</guid>

					<description><![CDATA[Amazon Web Services (AWS) users ask how to accelerate their teams’ deployments on AWS while maintaining compliance with security controls. In this blog post, we describe common governance models introduced in mature organizations to manage their teams’ AWS deployments. These models are best used to increase the maturity of your cloud infrastructure deployments. Governance models […]]]></description>
		
		
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			</item>
		<item>
		<title>Save time and effort in assessing your teams’ architectures with pattern-based architecture reviews</title>
		<link>https://noise.getoto.net/2022/07/21/save-time-and-effort-in-assessing-your-teams-architectures-with-pattern-based-architecture-reviews/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Wed, 20 Jul 2022 22:04:00 +0000</pubDate>
				<category><![CDATA[Architecture]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=518ee3b79f8b481905d42bb6c03f6c14</guid>

					<description><![CDATA[Enterprise architecture frameworks use architecture reviews as a key governance mechanism to review and approve architecture designs, identify quality enhancements, and align architectural decisions with enterprise-wide standards. Architecture reviews are very thorough, but it typically takes a lot of time and teamwork to prepare for them, which means developers can’t always move as quickly as […]]]></description>
		
		
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			</item>
		<item>
		<title>Queue Integration with Third-party Services on AWS</title>
		<link>https://noise.getoto.net/2021/08/23/queue-integration-with-third-party-services-on-aws/</link>
		
		<dc:creator><![CDATA[Rostislav Markov]]></dc:creator>
		<pubDate>Mon, 23 Aug 2021 17:12:26 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Elastic Container Service]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Healthcare]]></category>
		<category><![CDATA[Life Sciences]]></category>
		<category><![CDATA[Parallel processing]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=7b0f8fbc8dcce662f65ba76589c52817</guid>

					<description><![CDATA[Commercial off-the-shelf software and third-party services can present an integration challenge in event-driven workflows when they do not natively support AWS APIs. This is even more impactful when a workflow is subject to unpredicted usage spikes, and you want to increase decoupling and fault tolerance. Given the third-party nature of services, polling an Amazon Simple […]]]></description>
		
		
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