Recap of key AWS re:Invent 2021 announcements

Aws

Amazon Web Services held its 10th re:Invent conference from November 29th to December 3rd in Las Vegas, as a simultaneous in-person and virtual event. The first re:Invent for new AWS CEO Adam Selipsky saw a host of product and customer announcements targeted at fulfilling customer requirements and educating more IT developers and customers on new AWS services and features.

In his keynote, Adam Selipsky reinforced the fact that, “the cloud has become not just another tech revolution, but an enabler of a fundamental shift in the way that business functions. Analysts estimate that 5% to 15% of IT spending has moved to the cloud and despite what feels like a massive adoption, we are just getting started”.

The AWS re:Invent recap briefing to Indian reporters on December 14th, 2021, was led by Mr. Santanu Dutt, Director of Technology for South East Asia with Amazon Web Services (AWS) and Mr. Anupam Mishra, Head of AWS Technology and Solutions Architecture – India, Amazon Internet Services Pvt. Ltd. Several key AWS re:Invent 2021 announcements, new services, use cases, and applicability for customers in India were outlined.

Key announcements from re:Invent 2021:

Local Zone Expansion

Local Zones are types of infrastructure deployment that places compute, storage, database, and other select AWS services close to large population and industry centers that help deliver innovative applications requiring single-digit millisecond latency closer to end users and on-premises installations. AWS announced expansion of Local Zones, with over 30 new AWS Zones to be made available starting 2022 in over 21 countries around the world in North and South America, Europe, Africa, Asia (including India), and Australia.

  • The AWS Global Cloud Infrastructure is the most secure, extensive, and reliable cloud platform, offering over 200 fully featured services from data centers globally.
  • Whether you need to deploy your application workloads across the globe in a single click, or you want to build and deploy specific applications closer to your end-users with single-digit millisecond latency, AWS provides you the cloud infrastructure where and when you need it.
  • Customers across virtually every industry and of every size, including start-ups, enterprises, and public sector organizations, are running every imaginable use case on AWS. AWS has 84 Availability Zones across 26 geographic regions globally, with announced plans to launch 24 more Availability Zones and eight more AWS Regions in Australia, Canada, India, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates.
  • AWS Local Zones is another way we get AWS services closer to customers. We currently have 14 Local Zones in the US with a subset of AWS services like Amazon EC2, Amazon EBS, Amazon ECS, Amazon EKS and Amazon VPC 

Three Amazon EC2 instances

These are virtual servers that mimic the functionality of physical servers, powered by three new AWS-designed chips—AWS Graviton 3, AWS Trainium, and AWS Nitro SSD.

Benefit: To further lower costs, improve efficiency, and increase energy efficiency of EC2 instance usage for customers.

Key features:

  • In 2006—when cell phones could flip but weren’t yet smart—a team of AWS engineers set themselves an ambitious goal of making almost infinite computing power available to anyone in the world.
  • One of the first launches by AWS, Amazon Elastic Compute Cloud (EC2), revolutionized the way people build businesses, by offering on-demand access to the kind of compute power previously only available to Fortune 500 companies.
  • Fifteen years on, AWS announced three new Amazon EC2 instances (virtual servers that mimic the functionality of physical servers) powered by three new AWS-designed chips—AWS Graviton 3, AWS Trainium, and AWS Nitro SSD to help customers:

o   Significantly improve the performance, cost, and energy-efficiency of the workloads they run on EC2.

o   Speed up the time it takes to train machine learning models at lower cost.

o   Ensure optimum storage performance for data intensive workloads access to the kind of compute power previously only available to Fortune 500 companies.

  • New C7g instances powered by next-generation AWS Graviton3 processors deliver up to:

o   25% faster on average for general compute workloads than Graviton2 and they provide 2x faster processing for scientific and crypto applications.

o   3x faster processing for Machine Learning workloads, while using up to 60% less energy.

 AWS Mainframe Modernization

A mainframe, or ‘big iron’ as they are sometimes referred to, is a high-performance computer typically used by large companies for critical applications—such as storing and processing large amounts of customer data. While mainframes have been used for decades in industries including banking and healthcare, they are complex, expensive, and difficult to scale. Applications written for mainframes are increasingly hard to manage, as fewer and fewer engineers specialize in what’s essentially an outdated technology.

Benefit: Making on-premises mainframe migration to AWS Cloud easier

Key features:

  • The new managed service AWS Mainframe Modernization makes it faster and easier to move mainframe workloads to the cloud, which could prove a big benefit for enterprises that want to make the leap—and fast.
  • With AWS Mainframe Modernization, customers can refactor their mainframe workloads to run on AWS by transforming legacy applications into modern Java-based cloud services. There are no upfront costs and customers only pay for compute provisioned.
  • AWS Mainframe Modernization provides a complete development and runtime environment that makes it faster and easier for customers to migrate, modernize, and run their workloads on AWS. AWS Mainframe Modernization integrates the tools needed for migrations into a single environment to create an end-to-end migration pipeline.

Six new capabilities for its industry-leading ML service, Amazon SageMaker

As  tech industry and digital landscape evolves, companies are looking to reinvent their businesses and customer experiences using machine learning (ML). At AWS, we believe machine learning will be the most transformative technology of our generation and AWS announced six new capabilities for Amazon SageMaker at AWS re:Invent 2021.

Benefits: Making machine learning even more accessible and cost effective

Key features:

  • The powerful new capabilities will include a no-code environment for creating accurate ML predictions, more accurate data labeling using highly skilled annotators, a universal Amazon SageMaker Studio notebook experience for greater collaboration across domains, a compiler for ML training that makes code more efficient, automatic compute instance selection ML inference, and serverless compute for ML inference.

o   Amazon SageMaker Canvas no-code machine learning predictions: Amazon SageMaker Canvas expands access to machine learning by providing business analysts (line-of-business employees supporting finance, marketing, operations, and human resources teams) with a visual interface that allows them to create more accurate machine learning predictions on their own—without requiring any machine learning experience or having to write a single line of code.

o   Amazon SageMaker Ground Truth Plus expert data labeling: Amazon SageMaker Ground Truth Plus is a fully managed data labelling service that uses an expert workforce with built-in annotation workflows to deliver high-quality data for training machine learning models faster and at lower cost with no coding required. Customers need increasingly larger datasets that are correctly labelled to train ever more accurate models and scale their machine learning deployments

o   Amazon SageMaker Studio universal notebooks: Today, teams across different data domains want to collaborate using a range of data engineering, analytics, and machine learning workflows. A universal notebook for Amazon SageMaker Studio (the first complete Integrated Development Environment (IDE) for machine learning) provides a single, integrated environment to perform data engineering, analytics, and machine learning.

o   Amazon SageMaker Training Compiler for machine learning models: Amazon SageMaker Training Compiler is a new machine learning model compiler that automatically optimizes code to use compute resources more effectively and reduce the time it takes to train models by up to 50%.

o   Amazon SageMaker Inference Recommender automatic instance selection: Amazon SageMaker Inference Recommender helps customers automatically select the best compute instance and configuration (e.g., instance count, container parameters, and model optimizations) to power a particular machine learning model.

o   Amazon SageMaker Serverless Inference for machine learning models: Amazon SageMaker Serverless Inference offers pay-as-you-go pricing inference for machine learning models deployed in production. Customers are always looking to optimize costs when using machine learning, and this becomes increasingly important for applications that have intermittent traffic patterns with long idle times.

AWS AI & ML Scholarship Program

AWS announced two new initiatives designed to make machine learning more accessible for anyone interested in learning and experimenting with the technology.

Benefit: Preparing under-represented and underserved students globally for careers in machine learning.

  • The AWS AI & ML Scholarship is a new US$10 million education and scholarship program, aimed at preparing under-represented and under-served students globally for careers in machine learning.
  • The program uses AWS DeepRacer and the new AWS DeepRacer Student League to teach students foundational ML concepts by giving them hands-on experience training ML models for autonomous race cars, while providing educational content centred on ML fundamentals.

AWS Amplify Studio

Developers typically use two paths to develop a web application. They either write application code themselves or use a low-code tool to quickly build an application foregoing customizability. When they write application code, it allows them with a precise control over the web application’s design and behavior but can require months of time and effort to build. AWS Amplify Studio allows developers to quickly build a web application on AWS with minimal coding

Benefit: Low code approach that provides front-end web developers more functionality and features to create full stack web applications easily

Key features:

  • AWS Amplify Studio empowers developers to fully customize their application’s design and behavior using familiar programming languages
  • Developers use AWS Amplify Studio’s simple point-and-click visual interface to create their backend, and AWS Amplify automatically provisions the AWS services such as Amazon Cognito for authentication, Amazon DynamoDB for a database, Amazon S3 for storage and many more.
  • With Amplify Studio, developers can build their user interface (UI) using a library of prebuilt UI components, incorporate data or capabilities from AWS services into their UI, and collaborate with UX designers through an integration with Figma (a popular tool used to design and prototype UIs)—all without writing any code
  • This allows developers to deliver innovative, new capabilities to their customers faster. AWS Amplify Studio is available in preview in the Asia Pacific (Mumbai) region among others.

Doing more with IoT

With the explosion of devices and cloud infrastructure moving to the edge, IoT will be a major focus area for customers. AWS announced two news services AWS IoT TwinMaker and AWS IoT FleetWise for high-growth industry sectors such as manufacturing and automotive. 

  1. AWS IoT TwinMaker – A cloud services based digital twins capability that transforms industrial operations

Key features:

  • Digital twins are virtual representations of physical systems, regularly updated with data to generate immediate insights about the operational state of the environments they are designed to mimic.
  • Many industrial companies have the vast troves of data about their facilities required to build digital twins, but creating and managing them is hard, even for the most technically advanced organizations, so the majority are unable to use them.
  • AWS IoT TwinMaker makes it faster and easier for companies to create digital twins of buildings, factories, industrial equipment, production lines, and any other physical system, helping them to do things like optimize operations, increase production output, improve equipment performance, as well as react more quickly and accurately when issues occur.
  • This service is available to preview in the AWS Asia Pacific (Singapore) Region with availability in additional AWS Regions coming soon.
  1. AWS IoT FleetWise- Helping car manufacturers make better, safer vehicles

Key features:

  • Car makers will benefit from AWS IoT FleetWise, a new service designed to make it easier and more cost effective to collect and transfer vehicle data to the cloud in near-real time.
  • Manufacturers have been collecting data from standard vehicle sensors for years to improve vehicle quality and safety, but as these sensors get more advanced, they also generate a lot more data. Today’s sensors can produce up to two terabytes of data an hour per vehicle (roughly equivalent to 1,000 hours worth of movies) making the cost of transferring it to the cloud hugely expensive.
  • With AWS IoT FleetWise, manufacturers will get the advantage to collect and organize data from vehicles, regardless of make or model, and standardize it for analysis in the cloud.
  • This will help them to diagnose issues in individual vehicles, analyze vehicle fleet health to help reduce potential recalls or safety issues, and use analytics and machine learning to improve advanced technologies such as autonomous driving.

About Neel Achary 19292 Articles
Neel Achary is the editor of Business News This Week. He has been covering all the business stories, economy, and corporate stories.