Category: Messaging

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. In the last blog, Maximizing System Throughput, we talked about design patterns you can adopt to address immediate scaling challenges to provide a better customer experience. In this blog, we talk about architecture patterns to improve system resiliency, why observability […]

Recently, we have had customers express the desire to build “omni-channels.” These omni-channels provide a centralized overview of digital engagement channels that help you better understand your customers and offer a more personalized experience. Many companies have tried or are trying to implement an omni-channel strategy. However, because most existing channels are built on different platforms and […]

The adoption of the ISO 20022 messaging standard by the financial industry will benefit all participants across the payments chain: banks, market infrastructures, corporate, and consumers. By moving the SWIFT messaging and communications infrastructure stack onto AWS, customers can speed their adoption of ISO 20022. At the same time, they can reduce costs, and improve […]

Scaling based on Amazon Simple Queue Service (SQS) is a commonly used design pattern. At AWS Professional Services, we have recently used a variant of this pattern to achieve highly parallel computation for larger customers. In fact, any use case with a tree-like set of entities can use this pattern. It’s useful in a workflow […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Summary Finserv MARKETS enables customers to buy financial services products such as credit cards, loans, insurance, and investments from various partners. Finserv MARKETS integrates with a large number of partners in real time to provide services to customers. Each partner […]

This post was co-written by Abdullah Sahin, senior technology architect at Accenture, and Muhammad Qasim, software engineer at Accenture.  Organizations deploying call-center chat bots are interested in evolving their solutions continuously, in response to changing customer demands. When developing a smart chat bot, some requests can be predicted (for example following a new product launch […]

This post was co-written by Andrew Alaniz , Director of Technology Infrastructure, and Brady Pratt, Cloud Security Engineer, both at BBVA USA. Introduction Data Loss Prevention (DLP) is a common topic among companies that work with any type of sensitive data. One of the challenges is that many people either don’t fully understand what DLP […]

In a recent customer engagement, Quantiphi, Inc., a member of the Amazon Web Services Partner Network, built a solution capable of pre-processing tens of millions of PDF documents before sending them for inference by a machine learning (ML) model. While the customer’s use case—and hence the ML model—was very specific to their needs, the pipeline that does […]

This post was co-written with Lucas Ceballos, CTO of Smadex Introduction Showing ads may seem to be a simple task, but it’s not. Showing the right ad to the right user is an incredibly complex challenge that involves multiple disciplines such as artificial intelligence, data science, and software engineering. Doing it one million times per […]

In previous blog posts in this messaging series, we provided an overview of messaging and we also explained the common characteristics to consider when  evaluating messaging channel technologies. In this post, we will explain some of the semantics of queue-based processing, its use in designing flexible systems, and how to apply it to your use […]