AWS CEO Adam Selipsky has reinforced Amazon’s commitment to sustainability and announced a raft of new services designed to improve data collection and analysis, help customers respond to security risks quicker, and support industries with purpose-built solutions.
Highlights at AWS re:Invent 2022 include:
Delivering new solutions to drive industry transformation
Improving supply chain visibility
AWS Supply Chain is a new application that helps businesses increase supply chain visibility to make faster, more informed decisions that mitigate risks, lower costs, and improve customer experiences. AWS Supply Chain automatically combines and analyses data across multiple supply chain systems so businesses can observe their operations in real-time, find trends more quickly, and generate more accurate demand forecasts so that the business can ensure adequate inventory to meet customer expectations. AWS Supply Chain improves supply chain resiliency by providing a unified data lake, machine-learning-powered insights, recommended actions, and in-application collaboration capabilities.
Better data collaboration
AWS Clean Rooms is a new analytics service that helps companies across industries easily and securely analyse and collaborate on their combined datasets—without sharing or revealing underlying data. With AWS Clean Rooms, customers can create a secure data clean room in minutes and collaborate with any other company in the AWS Cloud to generate unique insights about advertising campaigns, investment decisions, clinical research, and more.
AWS Clean Rooms provides a broad set of built-in data access controls that protect sensitive data, including query controls, query output restrictions, query logging, and cryptographic computing tools. AWS Clean Rooms will be available in early 2023 in the Asia Pacific Regions for Seoul, Singapore, Sydney, and Tokyo.
Easier large-scale spatial simulations
AWS SimSpace Weaver is a fully-managed compute service that helps customers build, operate, and run large-scale spatial simulations. With AWS SimSpace Weaver, customers can deploy spatial simulations to model dynamic systems with many data points (e.g., traffic patterns across an entire city, crowd flows in a venue, or factory-floor layouts), and then use the simulations to visualise physical spaces, perform immersive training, and garner insights on different scenarios.
AWS SimSpace Weaver allows customers to run a simulation that has more than a million entities interacting in real time and create more sophisticated environments than previously possible, while reducing the time to simulation deployment from years to months. AWS SimSpace Weaver is generally available today in the Asia Pacific Regions for Singapore and Sydney, with availability in additional AWS Regions coming soon.
Advancing scientific discoveries
Amazon Omics is a managed service to help bioinformaticians, researchers, and scientists store, query, and analyse genomic, transcriptomic, and other 'omics' data and generate insights to improve health and advance scientific discoveries. This is the newest addition to AWS’s AWS for Health suite of purpose-built services. Amazon Omics supports large-scale analysis and collaborative research, so healthcare and life sciences organisations can store, and together with other AWS services, analyse genome data for entire populations. Amazon Omics is now available in the Asia Pacific (Singapore) Region.
Unlocking the value of data
Simplifying data management
Amazon DataZone is a new data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on-premises, and third-party sources. With Amazon DataZone, administrators and data stewards who oversee an organisation’s data assets can manage and govern access to data using fine-grained controls to ensure it is accessed with the right level of privileges and in the right context.
Centralising security data
Security activity is typically based on log and event data from different sources (e.g., applications, firewalls, and identity systems) running in the cloud and on premises, each using a unique and often incompatible data format. Amazon Security Lake is a service that automatically centralises an organisation’s security data from cloud and on-premises sources into a purpose-built data lake in a customer’s AWS account so customers can act on security data faster.
Amazon Security Lake manages data throughout its lifecycle with customisable data retention settings, converts incoming security data to the efficient Apache Parquet format, and conforms it to the Open Cybersecurity Schema Framework (OCSF) open standard to make it easier to automatically normalise security data from AWS and combine it with dozens of pre-integrated third-party enterprise security data sources.
Updates to Amazon QuickSight
AWS has announced five new capabilities to help customers streamline business intelligence (BI) operations using Amazon QuickSight, the serverless BI service built for the cloud. QuickSight Q, a natural language querying capability, has been expanded to support forecast and “why” questions and automate data preparation, making it easier and faster to start asking questions in natural language. Additionally, customers can now create and share paginated reports alongside interactive dashboards, quickly analyse and visualise billion-row datasets directly in QuickSight, and programmatically create and manage BI assets to accelerate migration from legacy systems.
“As we scale the use of dashboards and reports to share data-driven insights on connected car data across our organisation, it is becoming increasingly difficult to rely on the time-consuming and error-prone process of manually deploying BI assets,” said Daisuke Hyodo, Deputy GM of Research and Development, Data Science, and Global IT at NISSAN, an international automotive company which sells vehicles under the Nissan, Infiniti, and Datsun brands.
“As an agile data and analytics team, we are excited to use QuickSight’s expanded API capabilities to programmatically manage analyses and dashboard assets in our DevOps pipeline. This will allow us to promote changes faster and quickly share valuable insights with our end users.”
Moving toward a zero-ETL future
AWS has announced two new integrations that make it easier for customers to connect and analyse data across data stores without having to move data between services. Customers will be able to analyse Amazon Aurora data with Amazon Redshift in near real time, eliminating the need to extract, transform, and load (ETL) data between services. Customers can also now run Apache Spark applications easily on Amazon Redshift data using AWS analytics and machine learning (ML) services (e.g., Amazon EMR, AWS Glue, and Amazon SageMaker).
Delivering innovation in the public sector
AWS compute and machine learning services run on an orbiting satellite
AWS successfully ran a suite of compute and machine learning software on an orbiting satellite, in a first-of-its-kind space experiment. The experiment, conducted over the past 10 months in low Earth orbit, was designed to test a faster, more efficient method for customers to collect and analyse valuable space data directly on their orbiting satellites using the cloud.
Providing AWS edge capabilities onboard an orbiting satellite for the first time lets customers automatically analyse massive volumes of raw satellite data in orbit and only downlink the most useful images for storage and further analysis, driving down cost and enabling timely decision making.
Protect critical services
AWS announced the launch of Continuity of Government IT on AWS (CGIT) to help governments protect their digital assets and services in the face of disruption or interference. This solution guide enables governments to retain the integrity of critical datasets, backup applications, and transfer services to run in the cloud and reduces the risk of compromise for continuity of operations.
Thinking bigger
Max Peterson, VP of AWS worldwide public sector, spoke about how the transformative power of the cloud is enabling organisations to move with speed and agility while making sure mission-critical workloads stay secure and protected.
Continued innovation with AWS-designed chips
Three Amazon EC2 Instances powered by new AWS-designed chips
Peter DeSantis, Senior VP of Utility Computing at AWS, announced three new Amazon EC2 instances powered by three new AWS-designed chips that offer customers even greater compute performance at a lower cost for a broad range of workloads, including:
- Hpc7g instances, powered by new AWS Graviton3E chips, offer up to 2x better floating-point performance compared to current generation C6gn instances and up to 20% higher performance compared to current generation Hpc6a instances, delivering the best price performance for high performance computing (HPC) workloads on AWS.
- C7gn instances, featuring new AWS Nitro Cards, offer up to 2x the network bandwidth and 2x the packet-per second performance on a per-CPU basis compared to current generation networking-optimised instances, delivering the highest network bandwidth, the highest packet rate performance, and the best price performance for network-intensive workloads.
- Inf2 instances, powered by new AWS Inferentia2 chips, are purpose built to run the largest deep learning models with up to 175 billion parameters and offer up to 4x the throughput and up to 10x lower latency compared to current-generation Inf1 instances, delivering the lowest latency at the lowest cost for machine learning inference on Amazon EC2.
Ben Cabanas, Director of Solutions Architecture at AWS in Asia Pacific and Japan said: “We’re pleased to bring more services that are designed make it even easier for organisations in Asia Pacific to derive insights from their data to drive efficiency, improve security, personalise customer experiences, and optimise business performance. Our industry-focused approach continues to enable digital transformation for industries, organisations, and communities across the region with purpose-built solutions.
"From leveraging data to increase supply chain resiliency, running large scale spatial simulations to design smarter cities, or helping healthcare organisations to process and analyse genomic data to advance scientific discoveries, these solutions will transform how organisations in Asia Pacific collaborate, make business decisions, and deliver citizen services.”
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