Home Industry Verticals Artificial Intelligence 6 new developments at AWS re:invent 2016

6 new developments at AWS re:invent 2016

11 MIN READ

Amazon Web Services’ weeklong annual consumer and partner conference at Las Vegas came to an end last Friday. According to the company the conference expected cloud-technology providers and consultants, over 24,000 attendees and expert Amazon Web Services engineers, and product leaders. Announcements ranging from AI, machine learning and IoT to partner programs, competencies and service extensions, below are the six interesting developments of AWS re:invent 2016.

Three new AWS Partner Network (APN) programs, two new AWS Competencies, and an APN Partner Solutions Finder

The three new APN Programs will support and differentiate APN partners who provide solutions and expertise for specific services, workloads, and industry verticals. According to the company, AWS Service Delivery Program, the APN Public Sector Partner Program, and the VMware CloudTM on AWS Partner Program will provide tools, training, and benefits to support and distinguish partners in Service Delivery, Public Sector, and VMware CloudTM on AWS.

The two new AWS Competencies claim to enable and promote partners who have demonstrated proven success in Financial Services and Internet of Things (IoT). According to AWS, the Competency Program highlights APN Partners who have demonstrated technical proficiency and proven customer success in specialized solution areas. The company claims that with the new additions, the program now covers 16 different workloads and verticals.

To help customers more easily find the right partner and solution for their specific business needs, AWS launched the APN Partner Solutions Finder, a new website where customers can search for, discover, and connect with APN Partners. AWS states that customers often ask where to go when looking for a partner that can help design, migrate, manage, and optimize their workloads on AWS, or for partner-built tools that can help them achieve their goals.

Seven new compute services and capabilities

The company plans to offer the next generation of Amazon Elastic Compute Cloud (EC2) Memory Optimized, Compute Optimized, and High input/output (I/O) instances, and added two new hardware acceleration options to its range of compute services.

AWS claims the new F1 instance is the cloud’s first customer-programmable, hardware-accelerated compute instance with Field Programmable Gate Arrays (FPGAs).

Amazon EC2 Elastic GPUs allow customers to easily attach low-cost, professional grade graphics acceleration to Amazon EC2 instances.

AWS also announced Amazon Lightsail, a new way to get started with AWS that makes it easy to spin up powerful virtual private servers (VPS) that have bundled storage and networking with simple, monthly pricing. It includes everything customers need for projects such as web sites, blogs, custom applications, or development servers.

Amazon Athena

According to the company, Athena is a serverless query service that makes it easy to analyze data directly in Amazon Simple Storage Service (Amazon S3) using standard SQL. AWS claims that with a few clicks in the AWS Management Console, customers can point Amazon Athena at their data stored in Amazon S3 and begin using standard SQL to run queries and get results in seconds.

The company states, with Amazon Athena there are no clusters to manage and tune, no infrastructure to setup or manage, and customers pay only for the queries they run. Amazon Athena scales automatically, executing queries in parallel, so results are fast, even with large datasets and complex queries.

The company said that customers can start using Amazon Athena using the AWS Management Console. It is currently available in the N. Virginia and Oregon in the US and will expand to additional regions in the coming months.

Amazon Aurora extension with PostgreSQL compatibility

Amazon announced that it has added full PostgreSQL compatibility to Amazon Aurora, the AWS database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases.

With Amazon Aurora’s new PostgreSQL support, customers can get up to several times better performance than the typical PostgreSQL database and take advantage of the scalability, durability, and security capabilities of Amazon Aurora – all for one-tenth the cost of commercial grade databases.

According to the company, the support requires no upfront costs or commitments, customers are required to pay a simple hourly charge for each Amazon Aurora database instance they use and can automatically scale storage capacity with no downtime or performance degradation.

Three New Amazon AI Services

Three Artificial Intelligence (AI) services have also been announced by AWS. The company states that these services will make it easy for any developer to build apps that can understand natural language, turn text into lifelike speech, have conversations using voice or text, analyze images, and recognize faces, objects, and scenes.

AWS claims that Amazon Lex, Amazon Polly, and Amazon Rekognition do not require any deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments. This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact.

Amazon Lex is a new service for building conversational interfaces using voice and text that is built on the same automatic speech recognition (ASR) technology and natural language understanding (NLU) that powers Amazon Alexa. Amazon Lex makes it easy to bring sophisticated, natural language capabilities to virtually any app.

Amazon Polly makes it easy for developers to add natural-sounding speech capabilities to existing applications like newsreaders and e-learning platforms, or create entirely new categories of speech-enabled products – from mobile apps to devices and appliances.

Amazon Rekognition enables developers to quickly and easily build applications that analyze images, and recognize faces, objects, and scenes. Amazon Rekognition uses deep learning technologies to automatically identify objects and scenes, such as vehicles, pets, or furniture, and provides a confidence score that lets developers tag images so that application users can search for specific images using key words.

Two New Hybrid Services extend Cloud to Connected Devices

Amazon also announced AWS Greengrass, which allows customers to run AWS compute, messaging, data caching, and sync capabilities on connected devices. With AWS Greengrass, devices can run AWS Lambda functions to perform tasks locally, keep device data in sync, and communicate with other devices while leveraging the full processing, analytics, and storage power of the AWS Cloud.

The company also announced a new Snowball data transfer appliance, the AWS Snowball Edge, that can transport two times more data than the original AWS Snowball (up to 100 TB), and includes AWS Greengrass, making it a purpose-built hybrid edge device that can transfer data to and from Amazon Simple Storage Service (Amazon S3), cluster with other Snowball Edge devices to form an on-premises storage pool, and run AWS Lambda to process and analyze data.

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