Category: AWS Well-Architected

For many years, Chaos Engineering was viewed as a mechanism to help surface the “known-unknowns” (things that we are aware of, but do not fully understand) in our environments or “unknown-unknowns” (things we are neither aware of, nor fully understand). Using Chaos Engineering, chaos experiments have been conducted on infrastructure, applications, and business processes that […]

Facteus Inc. is a leading provider of actionable insights from sensitive transaction data. Facteus safely transforms raw financial transaction data from legacy technologies into actionable information, without compromising data privacy, through its innovative synthetic data process. Quantamatics is one of Facteus’ core product offering. Quantamatics accelerates the time it takes a user to go from […]

Amazon’s CTO Werner Vogels says, “Everything fails, all the time”. This means we should design with failure in mind and assume that something unpredictable could happen. The AWS Well-Architected Framework is designed to help you prepare your workload for failure. It describes key concepts, design principles, and architectural best practices for designing and running workloads […]

In this blog post, we present a lifecycle that helps you build, validate, and improve your own AWS Well-Architected Custom Lens, in order to roll it out across your whole organization. The AWS Well-Architected Custom Lens is a new feature of the AWS Well-Architected Tool that lets you bring your own best practices to complement the existing […]

For larger customers, performing AWS Well-Architected (AWS WA) Framework reviews often involves a combination of different teams. Coordinating participants from each team in order to perform a review increases the time taken and is expensive. In a large organization, there are often hundreds of AWS accounts where teams can store review documents, which means there […]

At AWS re:Invent 2021, we announced the AWS Well-Architected Sustainability Pillar, which marks sustainability as a key pillar of building workloads to best deliver on business need. In session ARC325 – Architecting for Sustainability, Adrian Cockcroft, Steffen Grunwald, and Drew Engelson (Director of Engineering at Starbucks) gave a detailed explanation of what to expect from the […]

We’re celebrating Earth Day 2022 from 4/22 through 4/29 with posts that highlight how to build, maintain, and refine your workloads for sustainability. AWS estimates that inference (the process of using a trained machine learning [ML] algorithm to make a prediction) makes up 90 percent of the cost of an ML model. Given with AWS you […]

More complexity often means using more energy, and machine learning (ML) models are becoming bigger and more complex. And though ML hardware is getting more efficient, the energy required to train these ML models is increasing sharply. In this series, we’re following the phases of the Well-Architected machine learning lifecycle (Figure 1) to optimize your […]

by Subrahmanyam Madduru – Global Partner Solutions Architect Leader, AWS, Sandipan Chakraborti – Senior AWS Architect, Wipro Limited, Abhishek Gautam – AWS Developer and Solutions Architect, Wipro Limited, Arati Deshmukh – AWS Architect, Infosys As more and more enterprises adopt serverless technologies to deliver their business capabilities in a more agile manner, it is imperative […]

Training artificial intelligence (AI) services and machine learning (ML) workloads uses a lot of energy—and they are becoming bigger and more complex. As an example, the Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models study estimates that a single training session for a language model like GPT-3 can have a carbon footprint […]