AWS Architecture Blog

Tag: Field Notes

Figure 1 - Architecture Showing how to build an automated Image Processing and Model Training pipeline

Field Notes: Building an Automated Image Processing and Model Training Pipeline for Autonomous Driving

In this blog post, we demonstrate how to build an automated and scalable data pipeline for autonomous driving. This solution was built with the goal of accelerating the process of analyzing recorded footage and training a model to improve the experience of autonomous driving. We will demonstrate the extraction of images from ROS bag file […]

Figure 1 - Architecture representing an IoT ingestion pipeline

Field Notes: Deliver Messages Using an IoT Rule Action to Amazon Managed Streaming for Apache Kafka

With IoT devices scaling up rapidly, real-time data integration and data processing has become a major challenge. This is why customers often choose Message Queuing Telemetry Transport (MQTT) for message ingestion, and Apache Kafka to build a real-time streaming data pipeline. AWS IoT Core now supports a new IoT rule action to deliver messages from […]

Architecture showing how to build a Scalable Real-Time Newsfeed Watchlist Using Amazon Comprehend

Field Notes: Building a Scalable Real-Time Newsfeed Watchlist Using Amazon Comprehend

One of the challenges businesses have is to constantly monitor information via media outlets and be alerted when a key interest is picked up, such as individual, product, or company information. One way to do this is to scan media and news feeds against a company watchlist. The list may contain personal names, organizations or […]

Figure 3 - IVR flow leveraging dynamically generated menu options.

Field Notes: Build Dynamic IVR Menus with Amazon Connect and AWS Lambda

This post was co-written by Marius Cealera, Senior Partner Solutions Architect at AWS, and Zdenko Estok, Cloud Architect and DevOps Engineer at Accenture.  Modern interactive voice response (IVR) systems help customers find answers to their questions through a series of menus, usually relying on the customer to filter and select the right options. Adding more […]

Figure 1 - Architecture overview of the solution 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 […]

Reference Architecture Diagram showing Automated Deployment Flow

Field Notes: How Sportradar Accelerated Data Recovery Using AWS Services

This post was co-written by Mithil Prasad, AWS Senior Customer Solutions Manager, Patrick Gryczka, AWS Solutions Architect, Ben Burdsall, CTO at Sportradar and Justin Shreve, Director of Engineering at Sportradar.  Ransomware is a type of malware which encrypts data, effectively locking those affected by it out of their own data and requesting a payment to […]

a custom solution for Cross-Account, Cross-Region database replication with configurable Recovery Time

Field Notes: How to Set Up Your Cross-Account and Cross-Region Database for Amazon Aurora

This post was co-written by Ashutosh Pateriya, Solution Architect at AWS and Nirmal Tomar, Principal Consultant at Infosys Technologies Ltd.  Various organizations have stringent regulatory compliance obligations or business requirements that require an effective cross-account and cross-region database setup. We recommend to establish a Disaster Recovery (DR) environment in different AWS accounts and Regions for […]

Initial Orchestration Architecture

Field Notes: Orchestrating and Monitoring Complex, Long-running Workflows Using AWS Step Functions

Situation: S&P Global Market Intelligence’s WSO solution offers financial reports to hundreds of clients worldwide. When S&P Global Market Intelligence completed the migration of WSO’s SaaS software to AWS, it unlocked the power and agility to deliver new product features monthly, as opposed to a multi-year release cycle. This migration also presented a great opportunity […]

Figure 1 - Architecture for Automating Data Ingestion and Labeling for Autonomous Vehicle Development

Field Notes: Automating Data Ingestion and Labeling for Autonomous Vehicle Development

This post was co-written by Amr Ragab, AWS Sr. Solutions Architect, EC2 Engineering and Anant Nawalgaria, former AWS Professional Services EMEA. One of the most common needs we have heard from customers in Autonomous Vehicle (AV) development, is to launch a hybrid deployment environment at scale. As vehicle fleets are deployed across the globe, they […]