AWS Architecture Blog

Category: Analytics

Figure 1. OR optimization options

Emerging Solutions for Operations Research on AWS

Operations research (OR) uses mathematical and analytical tools to arrive at optimal solutions for complex business problems like workforce scheduling. The mathematical techniques used to solve these problems, such as linear programming and mixed-integer programming, require the use of optimization software (solvers).  There are several popular and powerful solvers available, ranging from commercial options like […]

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Figure 2. Architecture to view Security Hub findings using AWS serverless analytics services

Visualize AWS Security Hub Findings using Analytics and Business Intelligence Tools

To improve the security posture in your organization, you first must have a comprehensive view of your security, operations, and compliance data. AWS Security Hub gives you a thorough view of your security alerts and security posture across all your AWS accounts. This is shown as Security Hub findings, which are generated from different AWS […]

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Figure 1. Synchronous container applications diagram

Scaling Data Analytics Containers with Event-based Lambda Functions

The marketing industry collects and uses data from various stages of the customer journey. When they analyze this data, they establish metrics and develop actionable insights that are then used to invest in customers and generate revenue. If you’re a data scientist or developer in the marketing industry, you likely often use containers for services […]

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Final architecture

Toyota Connected and AWS Design and Deliver Collision Assistance Application

This post was cowritten by Srikanth Kodali, Sr. IoT Data Architect at AWS, and Will Dombrowski, Sr. Data Engineer at Toyota Connected Toyota Connected North America (TC) is a technology/big data company that partners with Toyota Motor Corporation and Toyota Motor North America to develop products that aim to improve the driving experience for Toyota […]

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How to Scale OpenTravel Messaging Architecture with Amazon Kinesis Data Streams

Field Notes: How to Scale OpenTravel Messaging Architecture with Amazon Kinesis Data Streams

The travel industry relies on OpenTravel messaging systems to collect and distribute travel data—like hotel inventory and pricing—to many independent ecommerce travel sites. These travel sites need immediate access to the most current hotel inventory and pricing data. This allows shoppers access to the available rooms at the right prices. Each time a room is […]

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Figure 2. Building Lake House architectures with AWS Glue

How to Accelerate Building a Lake House Architecture with AWS Glue

Customers are building databases, data warehouses, and data lake solutions in isolation from each other, each having its own separate data ingestion, storage, management, and governance layers. Often these disjointed efforts to build separate data stores end up creating data silos, data integration complexities, excessive data movement, and data consistency issues. These issues are preventing […]

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Figure 1. Data pipeline architecture using AWS Services

Building a Data Pipeline for Tracking Sporting Events Using AWS Services

In an evolving world that is increasingly connected, data-centric, and fast-paced, the sports industry is no exception. Amazon Web Services (AWS) has been helping customers in the sports industry gain real-time insights through analytics. You can re-invent and reimagine the fan experience by tracking sports actions and activities. In this blog post, we will highlight […]

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Field Notes: Creating Custom Analytics Dashboards with FireEye Helix and Amazon QuickSight

FireEye Helix is a security operations platform that allows organizations to take control of any incident from detection to response. FireEye Helix detects security incidents by correlating logs and configuration settings from sources like VPC Flow Logs, AWS CloudTrail, and Security groups. In this blog post, we will discuss an architecture that allows you to […]

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Figure 5. Amazon Redshift federated query with Amazon Redshift ML

Address Modernization Tradeoffs with Lake House Architecture

Many organizations are modernizing their applications to reduce costs and become more efficient. They must adapt to modern application requirements that provide 24×7 global access. The ability to scale up or down quickly to meet demand and process a large volume of data is critical. This is challenging while maintaining strict performance and availability. For […]

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reference architecture - build automated scene detection pipeline - Autonomous Driving

Field Notes: Building an automated scene detection pipeline for Autonomous Driving – ADAS Workflow

This Field Notes blog post in 2020 explains how to build an Autonomous Driving Data Lake using this Reference Architecture. Many organizations face the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems. In this re:Invent session, we explored an architecture to solve this problem using Amazon EMR, Amazon […]

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