AWS Architecture Blog

Category: AWS Step Functions

Figure 1 – Architecture showing the AWS Step Functions Workflow to stop services

Optimize Cost by Automating the Start/Stop of Resources in Non-Production Environments

Co-authored with Nirmal Tomar, Principal Consultant, Infosys Technologies Ltd. Ease of creating on-demand resources on AWS can sometimes lead to over-provisioning or under-utilization of AWS resources like Amazon EC2 and Amazon RDS. This can lead to higher costs that can often be avoided with proper planning and monitoring.  Non-critical environments, like development and test are […]

Read More
Figure 3. Choreography monitoring with AWS Step Functions

Use AWS Step Functions to Monitor Services Choreography

Organizations frequently need access to quick visual insight on the status of complex workflows. This involves collaboration across different systems. If your customer requires assistance on an order, you need an overview of the fulfillment process, including payment, inventory, dispatching, packaging, and delivery. If your products are expensive assets such as cars, you must track […]

Read More
Figure 6. Using Step Functions as workflow state manager

Migrating a Database Workflow to Modernized AWS Workflow Services

The relational database is a critical resource in application architecture. Enterprise organizations often use relational database management systems (RDBMS) to provide embedded workflow state management. But this can present problems, such as inefficient use of data storage and compute resources, performance issues, and decreased agility. Add to this the responsibility of managing workflow states through […]

Read More
Figure 3. FL prototype deployed on Amazon ECS Fargate containers and AWS IoT Greengrass cores.

Applying Federated Learning for ML at the Edge

Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the training data between multiple CPUs, multiple GPUs, or a […]

Read More
Figure 6. IoT Device Simulator architecture

Optimize your IoT Services for Scale with IoT Device Simulator

The IoT (Internet of Things) has accelerated digital transformation for many industries. Companies can now offer smarter home devices, remote patient monitoring, connected and autonomous vehicles, smart consumer devices, and many more products. The enormous volume of data emitted from IoT devices can be used to improve performance, efficiency, and develop new service and business […]

Read More
Figure 1. Step Functions Express workflow solution

Running a Cost-effective NLP Pipeline on Serverless Infrastructure at Scale

Amenity Analytics develops enterprise natural language processing (NLP) platforms for the finance, insurance, and media industries that extract critical insights from mountains of documents. We provide a scalable way for businesses to get a human-level understanding of information from text. In this blog post, we will show how Amenity Analytics improved the continuous integration (CI) […]

Read More
Figure 1. Audit Surveillance data lake architecture diagram

How Parametric Built Audit Surveillance using AWS Data Lake Architecture

Parametric Portfolio Associates (Parametric), a wholly owned subsidiary of Morgan Stanley, is a registered investment adviser. Parametric provides investment advisory services to individual and institutional investors around the world. Parametric manages over 100,000 client portfolios with assets under management exceeding $400B (as of 9/30/21). As a registered investment adviser, Parametric is subject to numerous regulatory […]

Read More
Figure 8. Architecture diagram of entire data collection and classification process

Serverless Architecture for a Structured Data Mining Solution

Many businesses have an essential need for structured data stored in their own database for business operations and offerings. For example, a company that produces electronics may want to store a structured dataset of parts. This requires the following properties: color, weight, connector type, and more. This data may already be available from external sources. […]

Read More
Figure 2: Automated batch ACT translation solution architecture

Speed Up Translation Jobs with a Fully Automated Translation System Assistant

Like other industries, translation and localization companies face the challenge of providing fast delivery at a low cost. To address this challenge, organizations use Machine Translation (MT) to complement their translator teams. MT is the use of automated software that translates text without the need of human involvement. One of the most recent advancements is […]

Read More
Figure 1. Architecture of document processing workflow

Automate Document Processing in Logistics using AI

Multi-modal transportation is one of the biggest developments in the logistics industry. There has been a successful collaboration across different transportation partners in supply chain freight forwarding for many decades. But there’s still a considerable overhead of paperwork processing for each leg of the trip. Tens of billions of documents are processed in ocean freight […]

Read More