Five new features and updated pricing for AWS IoT SiteWise
Also announced by AWS are five new features and updated pricing for AWS IoT SiteWise (preview).
The updated pricing for AWS IoT SiteWise sees users charged for data ingest and egress from AWS IoT SiteWise based on number of messages, instead of amount of data ingested or scanned.
As for the updates, users can now collect data in AWS IoT SiteWise using MQTT or a REST API and store it in a time-series data store.
Additionally, users can now create virtual representations, or models, of your industrial facilities which can span a hierarchy of hundreds of thousands of assets.
The third update sees users able to create transforms and compute metrics over your equipment data using a built-in library of mathematical and statistical operators.
Fourth, users can now publish a live data stream from within AWS IoT SiteWise that contains measurements and computed metrics linked to your equipment.
And for the fifth update, users can utilise the new SiteWise Monitor feature to create a fully-managed web application that provides enterprise users visibility into equipment data stored in AWS IoT SiteWise.
Amazon EC2 Inf1 Instances
Amazon EC2 Inf1 instances have reached general availability. Built from the ground up to support machine learning inference applications, the Inf1 instances feature up to 16 AWS Inferentia chips, high-performance machine learning inference chips designed and built by AWS.
“In addition, we’ve coupled the Inferentia chips with the latest custom 2nd Gen Intel Xeon Scalable processors and up to 100 Gbps networking to enable high throughput inference,” Amazon said.
“This powerful configuration enables Inf1 instances to deliver up to 3x higher throughput and up to 40 per cent lower cost per inference than Amazon EC2 G4 instances, which were already the lowest cost instance for machine learning inference available in the cloud.”
Amazon EC2 Inf1 instances offer high performance and the lowest cost machine learning inference in the cloud, the company claims.
With Inf1 instances, users can run large scale machine learning inference applications like image recognition, speech recognition, natural language processing, personalisation and fraud detection, at the lowest cost in the cloud.
Amazon EC2 Inf1 instances come in four sizes and are currently available in the US East (N. Virginia) and US West (Oregon) AWS Regions as On-Demand, Reserved, and Spot Instances or as part of a Savings Plan.
EC2 Image Builder
EC2 Image Builder, a service that makes it easier and faster to build and maintain secure images, is now available. Image Builder simplifies the creation, patching, testing, distribution, and sharing of Linux or Windows Server images, according to Amazon.
“Keeping server images up-to-date can be time consuming, resource intensive, and error-prone. Currently, customers either manually update and snapshot VMs or have teams that build automation scripts to maintain images,” the company said.
Amazon claims that Image Builder significantly reduces the effort of keeping images up-to-date and secure by providing a simple graphical interface, built-in automation, and AWS-provided security settings.
“With Image Builder, you can easily build your automated pipeline that customises, tests, and distributes your images in addition to keeping them secure and up-to-date,” it said.
Image Builder is available in all AWS regions and offered at no cost, other than the cost of the underlying AWS resources used to create, store, and share the images.
Amazon Fraud Detector
The new Amazon Fraud Detector offers a fully managed service for detecting potential online identity and payment fraud in real time, based on the same technology used by Amazon’s consumer business.
According to Amazon, the new service uses historical data of both fraudulent and legitimate transactions to build, train, and deploy machine learning models that provide real-time, low-latency fraud risk predictions.
“To get started, customers upload transaction data to Amazon Simple Storage Service (S3) to customize the model’s training. Customers only need to provide the email address and IP address associated with a transaction, and can optionally add other data (e.g. billing address, or phone number),” the company said.
“Based upon the type of fraud customers want to predict (new account or online payment fraud), Amazon Fraud Detector will pre-process the data, select an algorithm, and train a model – using the decades of experience running fraud detection risk analysis at scale at Amazon,” it said.
Arm-based instances powered by new AWS Graviton2 processors
Also announced are new Arm-based versions of Amazon EC2 M, R, and C instance families, powered by new AWS-designed Graviton2 processors, which the company claims deliver up to 40 per cent better price and performance than current x86 processor-based M5, R5, and C5 instances for a broad spectrum of workloads.
“These new Arm-based instances are powered by the AWS Nitro System, a collection of custom AWS hardware and software innovations that enable the delivery of efficient, flexible, and secure cloud services with isolated multi-tenancy, private networking, and fast local storage, to reduce customer spend and effort when using AWS,” Amazon said.
“AWS Graviton2 processors introduce several new performance optimizations versus the first generation. AWS Graviton2 processors use 64-bit Arm Neoverse cores and custom silicon designed by AWS, built using advanced 7 nanometer manufacturing technology,” it said.
According to Amazon, AWS Graviton2 processors provide two times faster floating point performance per core for scientific and high performance computing workloads, optimised instructions for faster machine learning inference, and custom hardware acceleration for compression workloads.
Contact Lens for Amazon Connect
AWS Contact Lens is a set of capabilities for Amazon Connect enabled by machine learning, which is designed to give contact centers the ability to understand the sentiment, trends, and compliance of customer conversations to improve customer experience and identify crucial customer feedback.
“Amazon Connect is a fully managed cloud contact center service, based on the same technology that powers Amazon’s award-winning customer service,” Amazon said. “Companies like Intuit, GE Appliances, and Dow Jones use Amazon Connect to run their contact centers at lower cost, while easily scaling to thousands of agents.
“With AWS Contact Lens, customer service supervisors can discover emerging themes and trends from customer conversations, conduct fast, full-text search on call and chat transcripts to troubleshoot customer issues, and improve customer service agents’ performance with call and chat-specific analytics – all from within the Amazon Connect console,” it said.
Coming mid-2020, Contact Lens will also provide the ability for supervisors to be alerted to issues during in-progress calls, giving them the ability to intervene earlier when a customer is having a poor experience.