Amazon Web Services has unveiled a new set of capabilities and innovations across its product portfolio.
Announced at the AWS Re:Invent 2020 conference, the new capabilities were announced for call centre platform Amazon Connect, relational database platform Amazon Aurora Serverless, containers and analytics.
AWS also unveiled five new services for industrial machine learning, as well as a number of innovations in both storage and compute power.
Amazon Connect’s new capabilities focus around more personalised, efficient and effective customer experiences through the help of machine learning.
- Amazon Connect Wisdom: provides contact centre agents with real-time information to help solve customer issues
- Amazon Connect Customer Profiles: gives agents a unified profile of each customer they can use to provide a more personalised service
- Real-Time Contact Lens: allows contact centre managers impact customer interactions
- Amazon Connect Tasks: automates, tracks and manages tasks for contact centre agents
- Amazon Connect Voice ID: real-time caller authentication using machine learning-powered voice analysis
AWS launched a new version of Amazon Aurora Serverless, now scaling to “hundreds of thousands of transactions in a fraction of a second”. AWS now also has a new capability to migrate from SQL server to Amazon Aurora PostgreSQL, with the open-source Babelfish for PostgreSQL project.
Four new container capabilities were launched to help customers develop, deploy, and scale modern applications:
- Amazon ECS Anywhere: Allows running Amazon ECS in a customer’s own data centres
- Amazon EKS Anywhere: the ability to run Amazon EKS in their own data centres
- AWS Proton: automates container and serverless application development and deployment
- Amazon Elastic Container Registry (Amazon ECR) Public: an easy and highly-available way to share and deploy container software publicly
The new analytics capabilities aimed to improve the performance of Amazon Redshift data warehouses, make it easier to move and combine data across data stores and make it simpler for end-users to get more value from their business data using machine learning.
- AQUA (Advanced Query Accelerator) for Amazon Redshift: hardware-accelerated cache claiming 10x better query performance than any other cloud data warehouse
- AWS Glue Elastic Views: lets developers easily build materialised views that automatically combine and replicate data across multiple data stores
- Amazon QuickSight Q: machine learning-powered capability to let users type questions about their business data in natural language and receive “highly accurate” answers in seconds
Industrial machine learning now has five additional services to help industrial and manufacturing customers embed intelligence in their production processes in order to improve operational efficiency, quality control, security, and workplace safety.
- Amazon Monitron: end-to-end machine monitoring solution comprised of sensors, gateway, and machine learning service to detect abnormal equipment conditions that may require maintenance
- Amazon Lookout for Equipment: gives customers with existing equipment sensors the ability to use AWS machine learning models to detect abnormal equipment behaviour and enable predictive maintenance
- AWS Panorama Appliance: enables customers with existing cameras in their industrial facilities with the ability to use computer vision to improve quality control and workplace safety
- AWS Panorama Software Development Kit (SDK): allows industrial camera manufacturers to embed computer vision capabilities in new cameras
- Amazon Lookout for Vision: uses AWS-trained computer vision models on images and video streams to find anomalies and flaws in products or processes
AWS sought to deliver improved storage performance, resiliency and value to customers in four new storage solutions:
- Amazon EBS io2 Block Express volumes: the first storage area network (SAN) built for the cloud, with up to 256,000 IOPS, 4,000 MB/second throughput, and 64 TB of capacity
- Next-generation Amazon EBS Gp3 volumes: give customers the ability to provision additional IOPS and throughput performance independent of storage capacity, provide up to 4x peak throughput, and are priced 20% lower per GB than previous generation volumes
- Amazon S3 Intelligent-Tiering: adds S3 Glacier Archive and Deep Archive access to existing Frequent and Infrequent access tiers to automatically reduce customers’ storage costs by up to 95 percent for objects that are rarely accessed
- Amazon S3 Replication (multi-destination): provides the ability to replicate data to multiple S3 buckets simultaneously in the same AWS Region or any number of AWS Regions to meet customers’ global content distribution, storage compliance, and data-sharing needs.
AWS bolstered its portfolio of compute solutions, with five new Elastic Compute Cloud ( EC2) instances and two new AWS Outposts form factors.
- AWS Graviton2-powered C6gn instances: delivers 100 Gbps networking performance and provide 40 percent better price performance over comparable current generation x86-based instances
- AMD-powered G4ad Graphics Processing Unit (GPU) instances: industry-best price performance for graphics-intensive applications
- M5zn instances: offers the fastest Intel Xeon Scalable processors in the cloud with an all-core turbo frequency of up to 4.5 GHz and up to 45% better compute performance per core than current M5 instances
- Next-gen Intel-powered D3/D3en instances: highest storage capacity for local HDD storage available in the cloud
- Memory-optimized R5b instances deliver 3x higher performance compared to same size R5 instances for Amazon Elastic Block Store (EBS), providing the fastest block storage performance available for Amazon EC2
- Two smaller AWS Outposts form factors, 1U and 2U servers: give customers access to AWS on-prem in space-constrained locations