# AWS Cloud Storage Published articles for AWS Cloud Storage. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Connect workloads to Amazon S3 Files across VPCs and accounts DevFeed: [Connect workloads to Amazon S3 Files across VPCs and accounts]() Original publisher: [Read original article]() Author: Salman Ahmed Published: 2026-09-14T17:10:24Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [Filesystems](), [VPC](), [Amazon EC2](), [Amazon Elastic Kubernetes Service](), [Amazon Elastic Container Service](), [Availability](), [Latency]() Tags: [account](), [amazon](), [amazon-ec2](), [amazon-eks](), [amazon-s3](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [amazon-vpc](), [amazon-vpc-lattice](), [aws](), [aws-cloud-storage](), [aws-fargate](), [aws-transit-gateway](), [expert-400](), [files](), [network](), [permissions](), [posix](), [s3](), [storage](), [technical-how-to]() ### AI overview This article explains how to connect workloads running across VPCs and AWS accounts to Amazon S3 Files. It compares VPC peering, AWS Transit Gateway, and Amazon VPC Lattice, and covers mounting from Amazon EC2, Amazon ECS on AWS Fargate, and Amazon EKS, including networking and permission considerations. ### Source excerpt Organizations store vast amounts of data in Amazon S3 for machine learning, data analytics, media processing, and generative AI workloads. Many of the applications, agents, and teams that work with that data are file-based: they read and write on a mounted path using the file and directory operations and POSIX tools they already depend on. [...] ## Enable zero-copy access to AWS services on Amazon FSx for NetApp ONTAP with Amazon S3 Access Points DevFeed: [Enable zero-copy access to AWS services on Amazon FSx for NetApp ONTAP with Amazon S3 Access Points]() Original publisher: [Read original article]() Author: Vinayak Datar Published: 2026-09-11T14:27:23Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [Amazon Web Services](), [Amazon Bedrock AgentCore](), [Artificial Intelligence](), [Filesystems](), [API]() Tags: [ai](), [amazon-bedrock-agentcore](), [amazon-fsx-for-netapp-ontap](), [amazon-quick-suite](), [amazon-s3](), [amazon-s3-access-points](), [amazon-simple-storage-service-s3](), [aws](), [aws-cloud-storage](), [eda](), [intermediate-200](), [netapp](), [ontap](), [s3](), [semiconductor](), [technical-how-to](), [zero-copy]() ### AI overview This AWS architecture post explains how semiconductor verification teams can use Amazon S3 Access Points for FSx for NetApp ONTAP to expose simulation and regression logs to AWS services without copying the data. It combines Amazon Bedrock AgentCore and Amazon Quick to support natural-language summaries and multi-file investigation of failures. ### Source excerpt Semiconductor verification teams run thousands of simulation jobs every night using Electronic Design Automation (EDA) tools. A large verification environment can generate logs from 100,000 or more test executions per night. A single regression cycle produces simulation logs, compilation logs, and scheduler logs. For a regression with dozens of failures, manual triage typically takes 45-60 [...] ## Flexibly control Amazon S3 Object Lock retention based on real business events DevFeed: [Flexibly control Amazon S3 Object Lock retention based on real business events]() Original publisher: [Read original article]() Author: Ed Gummett Published: 2026-09-08T21:14:31Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [Protection](), [data](), [ransomware]() Tags: [amazon-s3](), [amazon-s3-inventory](), [amazon-s3-lifecycle](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [aws-cli](), [aws-cloud-storage](), [aws-cloudtrail](), [aws-command-line-interface-aws-cli](), [compliance](), [data-protection](), [immutability](), [intermediate-200](), [ransomware](), [recovery](), [s3](), [technical-how-to]() ### AI overview This post explains how Amazon S3 Object Lock's variable retention can protect objects until business events occur, such as contract completion or ransomware recovery. It covers event holds, retention dates, deletion separation, monitoring, and automated hold release. ### Source excerpt Immutability is a foundational data protection control, protecting data in place against unintended changes and deletions by authorized users, and changes by unauthorized users. In many cases, however, it isn't clear at the time data is written how long it needs to stay immutable, or when that period should begin. A signed contract might need [...] ## Run Spark 31% faster and optimize compute costs with Amazon S3 Express One Zone on Amazon EMR DevFeed: [Run Spark 31% faster and optimize compute costs with Amazon S3 Express One Zone on Amazon EMR]() Original publisher: [Read original article]() Author: Suthan Phillips Published: 2026-09-03T16:16:55Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Apache Spark](), [Amazon S3](), [Benchmark](), [Latency](), [parquet](), [Amazon Web Services](), [cloud-infrastructure]() Tags: [advanced-300](), [amazon-cloudwatch](), [amazon-ec2](), [amazon-emr](), [amazon-s3](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [aws](), [aws-cli](), [aws-cloud-storage](), [aws-cloudtrail](), [aws-glue](), [benchmark](), [latency](), [parquet](), [performance](), [spark](), [technical-how-to]() ### AI overview This AWS post benchmarks Apache Spark workloads on Amazon EMR using Amazon S3 Express One Zone. It reports 31 percent lower runtime at 3 TB and 47 percent at 10 TB, attributing the gains to lower-latency storage, compute co-location, and optimized reads without application code changes. ### Source excerpt As your Spark datasets grow, storage latency often becomes the constraint, impeding application performance. Query runtimes stretch, and the bottleneck shifts from compute to how fast each node can read from Amazon Simple Storage Service (Amazon S3). We benchmarked this directly on Amazon EMR with TPC-DS at 3 TB scale. On an 8-node Graviton4 cluster [...] ## Detect stalled Amazon S3 live replication to prevent unexpected storage costs DevFeed: [Detect stalled Amazon S3 live replication to prevent unexpected storage costs]() Original publisher: [Read original article]() Author: Abhishek Shukla Published: 2026-08-28T19:12:07Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [Replication](), [Monitoring](), [Amazon CloudWatch](), [Disaster Recovery](), [cloud-infrastructure]() Tags: [advanced-300](), [amazon-cloudwatch](), [amazon-s3](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [aws-cloud-storage](), [compliance](), [cost-optimization](), [disaster-recovery](), [encryption](), [monitoring](), [replication](), [storage](), [technical-how-to]() ### AI overview This AWS post explains how to detect stalled Amazon S3 live replication before unreplicated objects increase storage costs. It describes protection for objects with failed replication status, CloudWatch replication metrics and alarms, and S3 Batch Replication for recovery. ### Source excerpt Organizations that replicate data across storage locations for disaster recovery, compliance, or analytics need a way to detect when replication stalls, because without early warning, unreplicated objects accumulate silently and drive unexpected storage costs. Most teams rely on automated retention policies to clean up the source copy after a defined period, but when replication breaks [...] ## Transfer Amazon S3 data from commercial AWS Regions to AWS European Sovereign Cloud using AWS DataSync Enhanced mode DevFeed: [Transfer Amazon S3 data from commercial AWS Regions to AWS European Sovereign Cloud using AWS DataSync Enhanced mode]() Original publisher: [Read original article]() Author: Pablo Colazurdo Published: 2026-08-18T22:47:14Z Content type: tutorial Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [data migrations](), [Cloud](), [cloud-infrastructure](), [Amazon Web Services](), [Encryption](), [IAM](), [Monitoring]() Tags: [advanced-300](), [amazon-s3](), [amazon-simple-storage-service-s3](), [aws](), [aws-cloud-storage](), [aws-datasync](), [aws-secrets-manager](), [cloud](), [cloud-infrastructure](), [data-migrations](), [encryption](), [eu](), [european-union](), [iam](), [infrastructure](), [migration-transfer-services](), [monitoring](), [regions](), [sovereignty](), [storage](), [technical-how-to]() ### AI overview This tutorial explains how to transfer Amazon S3 data between commercial AWS Regions and the AWS European Sovereign Cloud using AWS DataSync Enhanced mode. It covers partition isolation, encryption in transit, data validation, monitoring, auditing, scheduling, and secure IAM credential management with AWS Secrets Manager. ### Source excerpt With the introduction of AWS European Sovereign Cloud, organizations across Europe are adopting this dedicated partition to meet stringent data sovereignty requirements. However, organizations face significant operational challenges because they must maintain their existing AWS commercial partition deployments for global customers while simultaneously establishing AWS European Sovereign Cloud infrastructure. This dual-partition reality can cause data [...] ## How WeatherBug reduced storage costs by 80% using Amazon S3 Storage Lens and Kiro CLI DevFeed: [How WeatherBug reduced storage costs by 80% using Amazon S3 Storage Lens and Kiro CLI]() Original publisher: [Read original article]() Author: Dan Friedman Published: 2026-08-13T14:39:19Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [Amazon Web Services](), [Kiro](), [Optimization](), [cloud-infrastructure](), [datasets](), [Replication]() Tags: [advanced-300](), [amazon-cloudwatch](), [amazon-s3](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [aws](), [aws-cli](), [aws-cloud-storage](), [aws-cloudformation](), [aws-command-line-interface-aws-cli](), [aws-cost-explorer](), [aws-identity-and-access-management-iam](), [cli](), [customer-solutions](), [data](), [kiro](), [metrics](), [replication](), [s3](), [storage]() ### AI overview This case study explains how WeatherBug reduced Amazon S3 storage costs by 80% in six months. It describes reviewing hundreds of buckets across a multi-account AWS environment, identifying missing lifecycle policies, inefficient storage tiers, stale data, and unnecessary replication, then applying a systematic optimization approach using S3 Storage Lens, Kiro CLI, and lifecycle management. ### Source excerpt WeatherBug is the third largest weather intelligence company in the US, delivering real-time forecasts, radar, lightning alerts, and interactive maps to over 10 million users. As their data footprint has grown across hundreds of Amazon Simple Storage Service (Amazon S3) buckets in a multi-account AWS environment, their storage costs rose steadily with no clear visibility [...] ## Securing backup data against modern threats with AWS Backup DevFeed: [Securing backup data against modern threats with AWS Backup]() Original publisher: [Read original article]() Author: Brian M. Slater Published: 2026-08-12T23:50:24Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [Security](), [ransomware](), [Risk](), [systems](), [Encryption](), [Automation](), [API](), [Command-line interface]() Tags: [account](), [authentication](), [availability](), [aws](), [aws-backup](), [aws-cloud-storage](), [backup](), [best-practices](), [data](), [data-protection](), [data-resiliency](), [encryption](), [infrastructure](), [intermediate-200](), [protection](), [ransomware](), [ransomware-attacks](), [recovery](), [resilience](), [security](), [storage](), [threats]() ### AI overview This AWS Backup post explains how enterprises can protect backup data from ransomware, accidental deletion, account compromise, and infrastructure or availability threats. It describes layered safeguards including Vault Lock, logically air-gapped vaults, and multi-party approval workflows, and maps protection mechanisms to different risks. ### Source excerpt Enterprises face an evolving spectrum of threats to their backup data. From ransomware attacks that encrypt production systems and target recovery points, to accidental deletions by well-meaning administrators, to full account compromises that put every resource at risk, organizations can no longer assume that traditional backup approaches will keep their data recoverable. When backup infrastructure [...] ## Hybrid ML inferencing on Amazon EKS with Amazon FSx for NetApp ONTAP and on-premises NetApp DevFeed: [Hybrid ML inferencing on Amazon EKS with Amazon FSx for NetApp ONTAP and on-premises NetApp]() Original publisher: [Read original article]() Author: Ananta Khanal Published: 2026-08-12T18:31:46Z Content type: tutorial Language: en Sources: [AWS Storage Blog]() Topics: [Amazon Elastic Kubernetes Service](), [Inference](), [Machine Learning & Artificial Intelligence](), [model-deployment](), [container images](), [GPU](), [Terraform](), [Provisioning](), [AWS Identity and Access Management (IAM)](), [CUDA]() Tags: [amazon-eks](), [amazon-elastic-kubernetes-service](), [amazon-elastic-kubernetes-service-amazon-eks](), [amazon-fsx](), [amazon-fsx-for-netapp-ontap](), [amazon-simple-storage-service-amazon-s3](), [aws-cloud-storage](), [aws-identity-and-access-management-iam](), [cluster](), [cuda](), [expert-400](), [generative-ai](), [github](), [gpu](), [inference](), [inferencing](), [infrastructure](), [kubernetes](), [machine-learning](), [netapp](), [ontap](), [provisioning](), [technical-how-to]() ### AI overview This tutorial explains how to run stateful machine-learning inference on Amazon EKS using shared Amazon FSx for NetApp ONTAP storage and on-premises NetApp replication. It covers persistent model artifacts, Trident-based volume provisioning, Terraform infrastructure, and cold-start versus warm-start benchmarking. ### Source excerpt Machine learning (ML) models used for inference on Kubernetes are often several gigabytes in size. When these models are embedded in container images, images become oversized and pod scheduling slows. More critically, inference pods are inherently stateful. Model weights, tokenizer files, compiled GPU kernels, and runtime caches must persist across pod restarts, node failures, and [...] ## Optimize your self-managed PostgreSQL data warehouse with Amazon FSx for OpenZFS DevFeed: [Optimize your self-managed PostgreSQL data warehouse with Amazon FSx for OpenZFS]() Original publisher: [Read original article]() Author: Sandeep Aggarwal Published: 2026-08-11T16:36:11Z Content type: article Language: en Sources: [AWS Storage Blog]() Topics: [PostgreSQL](), [Database](), [Amazon Web Services](), [cloud-infrastructure](), [Amazon Redshift](), [Amazon RDS](), [Amazon EC2](), [scaling](), [Disaster Recovery]() Tags: [advanced-300](), [amazon-ec2](), [amazon-fsx-for-openzfs](), [amazon-rds](), [amazon-redshift](), [amazon-web-services](), [aws-backup](), [aws-cloud-storage](), [aws-database-migration-service](), [aws-well-architected-framework](), [cloud](), [database](), [databases](), [disaster-recovery](), [high-availability](), [postgresql](), [storage](), [technical-how-to]() ### AI overview An advanced AWS post explains how teams running self-managed PostgreSQL data warehouses can address growing storage footprints and full-reload times. It discusses storage architecture requirements such as scalability, performance, resilience, and cost-effectiveness, and compares self-managed EC2 deployments with managed options including Amazon Redshift and Amazon RDS. ### Source excerpt A data warehouse is the analytical backbone of a modern enterprise, consolidating data from disparate sources into a single, authoritative view that enables complex queries, trend analysis, and confident decision-making. In financial services, this means sharper regulatory reporting, faster fraud detection, and deeper customer understanding. The operational reality is demanding. Enterprises juggle multiple source databases [...] ## Access Amazon S3 backup data directly using S3 Access Points in AWS Backup DevFeed: [Access Amazon S3 backup data directly using S3 Access Points in AWS Backup]() Original publisher: [Read original article]() Author: Shaguna Awasthi Published: 2026-08-06T21:16:10Z Content type: tutorial Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [AWS Lake Formation](), [backups](), [cloud-infrastructure](), [Amazon SageMaker](), [AI, ML & Data Engineering]() Tags: [advanced-300](), [amazon-s3](), [amazon-s3-access-points](), [amazon-sagemaker](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [aws](), [aws-backup](), [aws-cli](), [aws-cloud-storage](), [aws-sdk](), [backup](), [cli](), [data-protection](), [data-resiliency](), [machine-learning](), [recovery](), [resilience](), [restore](), [s3-access-points](), [snapshot](), [storage](), [technical-how-to](), [uncategorized]() ### AI overview AWS Backup for Amazon S3 supports direct read access to backup data through S3 Access Points, allowing teams to use standard S3 APIs without first restoring the data. The post explains access-point creation and demonstrates uses including machine learning workflows, forensic investigations, and compliance audits. ### Source excerpt AWS Backup for Amazon S3 now lets you access your backup data through Amazon S3 Access Points. You create an access point for a recovery point, and AWS Backup provisions an S3 endpoint with an alias that works anywhere you would use a bucket name. You can then read backup data using standard S3 APIs, [...] ## Track healthcare data lineage in real time with Amazon S3 annotations DevFeed: [Track healthcare data lineage in real time with Amazon S3 annotations]() Original publisher: [Read original article]() Author: Omprasad Hedde Published: 2026-08-06T15:13:47Z Content type: tutorial Language: en Sources: [AWS Storage Blog]() Topics: [Amazon S3](), [AWS Glue](), [AWS Lambda](), [etl](), [data lake](), [SQL](), [AWS IAM](), [Amazon Redshift]() Tags: [advanced-300](), [amazon-athena](), [amazon-eventbridge](), [amazon-s3](), [amazon-simple-notification-service-sns](), [amazon-simple-queue-service-sqs](), [amazon-simple-storage-service-amazon-s3](), [amazon-simple-storage-service-s3](), [amazon-sns](), [amazon-sqs](), [aws-cloud-storage](), [aws-cloudformation](), [aws-cloudtrail](), [aws-glue](), [aws-identity-and-access-management-iam](), [aws-lambda](), [aws-step-functions](), [data](), [data-lake](), [data-lineage](), [etl](), [gdpr](), [healthcare](), [hipaa](), [parquet](), [technical-how-to]() ### AI overview A tutorial presents a real-time healthcare data-lineage solution using Amazon S3 annotations, AWS Lambda, AWS Glue, and Amazon Athena. Lineage and consent metadata travel with data objects through ingestion, standardization, and analytics stages, supporting HIPAA compliance audits and GDPR right-to-erasure queries. ### Source excerpt Organizations that store sensitive data need to answer a simple question: where did this data come from, and what happened to it? In healthcare, this isn't optional. Regulations like HIPAA, GDPR, and SOX require organizations to produce this information on demand. When an auditor asks, for example, "Show me every transformation that touched patient record [...]