It’s that time of the year already …
AWS re-Invent is back but in an all-new format this year, a virtual one, of course. Available as a free three-week virtual event, from Nov. 30 to Dec. 18, this mega cloud computing event has unveiled tons of new products – because if you didn’t know, AWS has a staggering number of them – and updates over the very first week itself, and we are here to walk you through the most significant ones.
Pictured above, Andy Jassy, CEO of Amazon Web Services, kicks off the virtual AWS re:Invent.
Also:
BlackBerry and AWS joins forces to create intelligent vehicle development platform [Full story]
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AWS announces a no-code mobile and web app builder [Full story]
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AWS is making moves in Canada, but so are its critics as protests disrupt summit [Full story, 2019]
Amazon DevOps Guru
What is it?
AWS has described it as a new machine learning-powered operations service that makes it easier for developers to improve application availability by automatically detecting operational issues and providing tailored recommendations and specific actions for remediation.
How does it work?
It applies machine learning informed by years of Amazon.com and AWS operations to automatically collect and analyze data like application metrics, logs, events, and traces for identifying behaviours that deviate from normal operating patterns (e.g. under-provisioned compute capacity, database I/O over-utilization, memory leaks, etc.). When Amazon DevOps Guru identifies anomalous application behaviour (e.g. increased latency, error rates, resource constraints, etc.) that could cause potential outages or service disruptions, it alerts developers with issue details (e.g. resources involved, issue timeline, related events, etc.) via Amazon Simple Notification Service (SNS) and partner integrations like Atlassian Opsgenie and PagerDuty to help them quickly understand the potential impact and likely causes of the issue. It will even spit out specific recommendations for remediation.
How does it help?
Developers can use remediation suggestions from Amazon DevOps Guru to reduce time to resolution when issues arise. There are no upfront costs or commitments with Amazon DevOps Guru, and customers pay only for the data Amazon DevOps Guru analyzes.
AWS announces Mac instances for Amazon EC2
AWS announced new Mac instances (EC2 Mac instances) for Amazon Elastic Compute Cloud (Amazon EC2). Built on Mac mini computers, EC2 Mac instances allow customers to run on-demand macOS workloads in the AWS cloud for the first time ever. With EC2 Mac instances, developers creating apps for iPhone, iPad, Mac, Apple Watch, Apple TV, and Safari can now provision and access macOS environments within seconds, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing.
This brings additional choice to developers so they can use Mac as their trusted platform, on-premises or in the cloud. Customers can also consolidate the development of cross-platform Apple, Windows, and Android apps onto AWS, leading to increased developer productivity and accelerated time to market. Similar to other Amazon EC2 instances, customers can easily use EC2 Mac instances together with AWS services and features like Amazon Virtual Private Cloud (VPC) for network security, Amazon Elastic Block Storage (EBS) for expandable storage, and Amazon Machine Images (AMIs) for OS image orchestration. The availability of EC2 Mac instances also offloads the heavy lifting that comes with managing infrastructure to AWS.
EC2 Mac instances are available to be purchased on-demand or with Savings Plans in the US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Singapore) regions, with other regions coming soon.
Pictured above, David Brown, AWS vice president, EC2 introducing Amazon EC2 Mac instances.
Five new industrial machine learning services
Amazon Monitron, Amazon Lookout for Equipment, the AWS Panorama Appliance, the AWS Panorama SDK, and Amazon Lookout for Vision are the five new industrial machine learning services that the company announced earlier this week.
Together, these five new machine learning services aim 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 provides customers with an end-to-end machine monitoring solution composed 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 behavior and enable predictive maintenance.
AWS Panorama Appliance enables customers with existing cameras in their industrial facilities to improve quality control and workplace safety with the use of computer vision.
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.
New analytics capabilities
AWS announced AQUA (Advanced Query Accelerator) for Amazon Redshift, AWS Glue Elastic Views and Amazon QuickSight Q, three new analytics capabilities that the company says improve the performance of Amazon Redshift data warehouses, make it easier for customers 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.
How do these capabilities help?
AQUA for Amazon Redshift accelerates querying with a new hardware-accelerated cache that brings the compute to the storage and delivers up to 10x better query performance than any other cloud data warehouse, with general availability coming in January 2021.
AWS Glue Elastic Views helps developers build applications that use data from multiple data stores with materialized views that automatically combine and replicate data across storage, data warehouses, and databases.
Amazon QuickSight Q delivers a machine learning-powered capability for Amazon QuickSight that gives users the ability to use natural language expressions to ask business questions in the Amazon QuickSight Q search bar and receive highly accurate answers in seconds.
Pictured above, Amazon QuickSight Q in action. Source: AWS
Four new container capabilities
The company announced four new container innovations to help customers develop, deploy, and scale modern applications. These include:
- Amazon Elastic Container Service (ECS) Anywhere enables customers to run Amazon ECS in their own data centers. AWS says it will be available in the first half of 2021.
- Amazon Elastic Kubernetes Service (EKS) Anywhere provides customers the ability to run Amazon EKS in their own data centres.
- AWS Proton provides customers with a new service to automate container and serverless application development and deployment. It was available in preview Dec. 1.
Containers provide a standard way for developers to package and run applications quickly and reliably in any environment, while also improving resource utilization and reducing cost. But now customers can run Amazon ECS or Amazon EKS in their own data centres, adding a new service for automated container and serverless application development and deployment while providing a new container registry that gives developers another way to share and deploy container software publicly.
The future of Amazon Aurora serverless
How does it work?
Instead of doubling capacity every time a workload needs to scale, Amazon Aurora Serverless v2 adjusts capacity in increments to provide just the right amount of database resources for an application’s needs. With this new version, customers only pay for the capacity they consume, which can save them up to 90 per cent of their database costs when compared to the cost of provisioning for peak capacity. AWS says Amazon Aurora Serverless v2 also provides the full breadth of Amazon Aurora’s capabilities, including Multi-AZ support for high availability, Global Database for low latency, and Backtrack for high resiliency.
Amazon Aurora Serverless is now ideal for a much broader set of applications, for example, it can support enterprises that have hundreds of thousands of applications and want to manage database capacity across the entire fleet, or for Software as a Service (SaaS) vendors that have a multi-tenant environment with hundreds or thousands of databases that each support a different customer. It is available in preview today for the MySQL 5.7-compatible edition of Amazon Aurora. AWS says this new version of Amazon Aurora Serverless, Aurora Serverless v2 is capable of scaling to hundreds of thousands of transactions in a fraction of a second, delivering up to 90 per cent cost savings compared to provisioning for peak capacity.
A new capability that makes it easier to migrate from SQL server to Amazon Aurora
AWS also launched Babelfish for Aurora PostgreSQL that gives customers the ability to run SQL Server applications directly on Amazon Aurora PostgreSQL with little to no code changes, saving customers from the punitive business practices common with old-guard database vendors
How does it work?
Babelfish for Aurora PostgreSQL provides a new translation layer for Amazon Aurora PostgreSQL that enables Amazon Aurora to understand commands from applications written for Microsoft SQL Server. Babelfish for Aurora PostgreSQL understands T-SQL (Microsoft SQL Server’s proprietary SQL dialect), so customers don’t have to rewrite all of their application’s database requests. It also understands SQL Server’s network protocol, so customers can continue using their existing SQL Server database drivers, says the company.
AWS also announced that coming in 2021 under the permissive Apache 2.0 license in GitHub, open-source Babelfish for PostgreSQL will extend the benefits of the Babelfish for Amazon Aurora PostgreSQL translation layer to even more organizations. The company says organizations will be able to use it for any purpose, distribute it, modify it, and distribute modified versions of the software under the terms of the license. Moreover, since all of the work and planning for Babelfish will happen on GitHub, AWS says organizations will have complete transparency about the features the company is working on next.
Five new capabilities for Amazon Connect
AWS announced five new capabilities for its contact centre service, Amazon Connect. The capabilities that launched Dec. 1 target AWS customers’ key asks: Improving their agents’ productivity and providing even better customer experiences. These new capabilities include:
- Amazon Connect Wisdom provides contact centre agents with the information they need to solve issues in real-time.
- Amazon Connect Customer Profiles gives agents a unified profile of each customer they can use to provide more personalized service.
- Real-Time Contact Lens for Amazon Connect offers a new capability for contact centre managers to impact customer interactions during a call.
- Amazon Connect Tasks automates, tracks, and manages tasks for contact centre agents, improving agent productivity by up to 30 per cent, according to AWS.
- Amazon Connect Voice ID delivers real-time caller authentication using machine learning-powered voice analysis.
Four storage innovations
AWS announced four storage innovations:
- Amazon EBS io2 Block Express volumes: Next-generation storage server architecture delivers the first SAN built for the cloud, with up to 256,000 IOPS, 4,000 MB/second throughput, and 64 TB of capacity (a 4x increase across all metrics compared to standard io2 volumes), to meet the performance requirements of the most I/O intensive business-critical applications (available in preview).
- Amazon EBS Gp3 volumes: Next-generation general purpose SSD volumes for Amazon EBS give customers the flexibility to provide additional IOPS and throughput without needing to add additional storage, while also offering higher baseline performance of 3,000 IOPS and 125 MB/second of throughput with the ability to provision up to 16,000 IOPS and 1,000 MB/second peak throughput (a 4x increase over Gp2 volumes) at a 20 per cent lower price per GB of storage than existing Gp2 volumes (available today).
- Amazon S3 Intelligent-Tiering automatic data archiving: Two new tiers (Archive Access and Deep Archive Access) help customers further reduce their storage costs by up to 95 per cent for objects rarely accessed by automatically moving unused objects into archive access tiers (available today).
- Amazon S3 Replication (multi-destination): New capability gives customers the ability to replicate data to multiple S3 buckets in the same or different AWS Regions, in order to better manage content distribution, compliance, and data-sharing needs across Regions (available today).
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