AWS Architecture Blog

DR implementation architecture on multi-Region active-passive workloads

Implementing Multi-Region Disaster Recovery Using Event-Driven Architecture

In this blog post, we share a reference architecture that uses a multi-Region active/passive strategy to implement a hot standby strategy for disaster recovery (DR). We highlight the benefits of performing DR failover using event-driven, serverless architecture, which provides high reliability, one of the pillars of AWS Well Architected Framework. With the multi-Region active/passive strategy, your workloads […]

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Figure 1. Notional architecture for improving forecasting accuracy solution and SAP integration

Improving Retail Forecast Accuracy with Machine Learning

The global retail market continues to grow larger and the influx of consumer data increases daily. The rise in volume, variety, and velocity of data poses challenges with demand forecasting and inventory planning. Outdated systems generate inaccurate demand forecasts. This results in multiple challenges for retailers. They are faced with over-stocking and lost sales, and […]

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How to redact confidential information in your ML pipeline

Integrating Redaction of FinServ Data into a Machine Learning Pipeline

Financial companies process hundreds of thousands of documents every day. These include loan and mortgage statements that contain large amounts of confidential customer information. Data privacy requires that sensitive data be redacted to protect the customer and the institution. Redacting digital and physical documents is time-consuming and labor-intensive. The accidental or inadvertent release of personal information […]

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Figure 2. Fraud detection using machine learning architecture on AWS

Analyze Fraud Transactions using Amazon Fraud Detector and Amazon Athena

Organizations with online businesses have to be on guard constantly for fraudulent activity, such as fake accounts or payments made with stolen credit cards. One way they try to identify fraudsters is by using fraud detection applications. Some of these applications use machine learning (ML). A common challenge with ML is the need for a […]

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Figure 1. VPC endpoint architecture

Choosing Your VPC Endpoint Strategy for Amazon S3

This post was co-written with Anusha Dharmalingam, former AWS Solutions Architect. Must your Amazon Web Services (AWS) application connect to Amazon Simple Storage Service (S3) buckets, but not traverse the internet to reach public endpoints? Must the connection scale to accommodate bandwidth demands? AWS offers a mechanism called VPC endpoint to meet these requirements. This […]

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Architecture diagram

CohnReznick Automates Claim Validation Workflow Using AWS AI Services

This post was co-written by Winn Oo and Brendan Byam of CohnReznick and Rajeswari Malladi and Shanthan Kesharaju CohnReznick is a leading advisory, assurance, and tax firm serving clients around the world. CohnReznick’s government and public sector practice provides claims audit and verification services for state agencies. This process begins with recipients submitting documentation as […]

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Fitness functions provide feedback to engineers via metrics

Using Cloud Fitness Functions to Drive Evolutionary Architecture

“It is not the strongest of the species that survives, nor the most intelligent. It is the one that is most adaptable to change.” – often attributed to Charles Darwin One common strategy for businesses that operate in dynamic market conditions (and thus need to continuously correct their course) is to aim for smaller, independent […]

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Reference Architecture to Launch a Fully Configured AWS Deep Learning Desktop with NICE DCV

Field Notes: Launch a Fully Configured AWS Deep Learning Desktop with NICE DCV

You want to start quickly when doing deep learning using GPU-activated Elastic Compute Cloud (Amazon EC2) instances in the AWS Cloud. Although AWS provides end-to-end machine learning (ML) in Amazon SageMaker, working at the deep learning frameworks level, the quickest way to start is with AWS Deep Learning AMIs (DLAMIs), which provide preconfigured Conda environments for […]

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Reducing latency by caching frequently accessed data on demand

Data Caching Across Microservices in a Serverless Architecture

Organizations are re-architecting their traditional monolithic applications to incorporate microservices. This helps them gain agility and scalability and accelerate time-to-market for new features. Each microservice performs a single function. However, a microservice might need to retrieve and process data from multiple disparate sources. These can include data stores, legacy systems, or other shared services deployed […]

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Figure 6. Amazon Virtual Andon deployment architecture

Digitally Optimize your Factory Issue Resolution with Amazon Virtual Andon

As a manufacturing enterprise, maximizing your operational efficiency and optimizing output are critical in a competitive global market. Global black swan events such as COVID-19 have necessitated the ability to monitor remotely and respond to issues actively, on the factory floor. Amazon Virtual Andon (AVA) is a digital notification system that helps factory personnel raise, […]

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