re:Invent 2017 – AWS Launches a Bare-Metal ECC2 Hypervisor with a New I3 Instance Amazon Web Services has officially launched its new bare metal hypervisor. During the Tuesday night keynote at the 2017 re-Invent conference in Las Vegas, Peter DeSantis (Vice President of AWS Global Infrastructure) announced the EC2 Bare Metal Instances. The EC2 bare metal technology is now available for public preview, as well as the new i3.metal instance. This technology is the result of many years of work at AWS under the “Nitro” effort. DeSantis stated that the goal of that effort was to make the EC2 instance “indistinguishable” from bare metal. According to DeSantis, the C3 was the first EC2 instance that was created under Nitro. The C3 was launched at the 2013 re-Invent conference. It offloaded the network processing part to the Nitro system hardware. The C4 was next and offloaded storage. The C5 instance, which was released this month, was the first to offload the entire EC2 stack, from networking and storage to management and security to monitoring, onto dedicated hardware. The C5 was developed using technology AWS acquired when it bought Annapurna Labs in 2015. It marked the debut of the “new EC2 Hypervisor”, DeSantis stated. The new hypervisor technology is also used in the VMware Cloud on AWS hybrid offering. It was launched in August and updated this week. AWS evangelist Jeff Barr explained that VMware wanted to run its virtualization stack directly on the AWS Cloud. This would allow their customers to access the reliability, security, and reliability that AWS offers. AWS now makes its bare-metal technology available to all its customers. Barr says that the new i3.metal instance is available for public preview starting Tuesday. It uses EC2 bare metal technology to “allow the operating system to directly run on the underlying hardware while still giving access to all the benefits of cloud computing.” The i3.metal instance is powered by two Intel Xeon E5-2686 v4 processors. It has 512GiB memory and 15.2TB storage. To preview the i3.metal in-progress instance, sign up here. More information from AWS Re:Invent 2017:

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Sumerian: AWS Helps Developers Build VR and 3-D Apps AWS Launches Cloud-Based Video Processing Service VMware and AWS Announce Updates […]

re:Invent 2017 – AWS Brings its Digital Assistant to Work With Alexa for Business. Amazon Web Services (AWS), this week launched “Alexa for Business” for office conference environments in an effort to increase the reach of its Alexa voice activated AI. During Thursday’s AWS reInvent conference keynote, Werner Vogels, Amazon.com’s Chief Technology Officer, introduced Alexa for Business. Vogels stressed the importance of natural voice interfaces during his presentation, especially as deep learning and AI technologies become more commonplace. Vogels stated that voice is the first disruption to be caused by deep learning tools. AWS plans to bring its AI platform’s natural language capabilities into workplaces using Alexa for Business, which is now available. Vogels described Alexa for Business “a fully managed service for having multiple Alexa devices at work.” Alexa for Business can be used for both shared Alexa-enabled devices (such as those in conference rooms or break rooms) and for employees’ Alexa devices that are registered in their company’s account. Alexa for Business can be used by companies to start meetings in conference rooms. Vogels says it integrates with conferencing systems such as Polycom and Cisco. He said that you don’t need to enter a conference ID. “All you have to do is say “Alexa, start the conference.” It can also be integrated with “smart rooms” systems to allow conference leaders voice control of things like temperature and blinds. Employees can link their Alexa device to their company account to gain access to productivity apps such as their Outlook Calendar and contacts. They can also use it for conference calls or hands-free messaging. IT can configure Alexa for Business using custom skills and distribute them on certain shared and personal devices. They can also distinguish between public and private skills and create skill groups. The Alexa for Business console allows for the provisioning and management of shared devices. Individual users can also be invited to join the Alexa for Business account. This FAQ provides information on supported devices, and pricing information can be found here. More information from AWS reInvent 2017:

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Sumerian: AWS Helps Developers Build VR and 3-D Apps AWS Launches Cloud-Based Video Processing Service VMware and AWS Announce Updates […]

re:Invent 2016 – AWS Gives Developers In-Depth Debugging With X-Ray Amazon Web Services (AWS), this week revealed a preview of a new service that provides developers with a detailed map to their applications’ internals, allowing them to better troubleshoot. Amazon.com’s Chief Technology Officer Werner Vogels unveiled AWS X-Ray at his re-Invent keynote in Las Vegas. He called it “one the coolest releases I could think of.” X-Ray provides developers with a visual interface that allows them to debug and analyze distributed applications. Developers can perform request-by-request analysis of their applications. Data is compiled into a visual “service diagram” that allows them to easily see the connections between their components and identify any errors. Vogels says it provides a deeper look into an application’s process than traditional metrics. X-Ray allows developers to “dive into the application to see how the components are working together,” he explained. “You can visualize call graphs and see where performance bottlenecks are. You can also pinpoint specific services that might be causing you problems.” Amazon’s CTO Werner Vogels announced the AWS X-Ray service during re:Invent on Wednesday. AWS evangelist Jeff Barr explained that X-Ray captures trace data from code running in EC2 instances (including ECS container), AWS Elastic Beanstalk and Amazon API Gateway. It implements follow the thread tracing by adding an HTTP Header (including a unique ID), to requests that don’t already have one. The header is then passed along to additional request handler tiers. Each point’s data is stored as a chunk in JSON data. Segments are units of work. They include request and response timings, as well as optional sub-segments which represent smaller work units (down down to lines of code, if the appropriate instrumentation is used). A statistically meaningful portion of the segments is routed to XRay (a daemon process that handles this on EC2 instances, inside of containers), where it is assembled into traces (groups or segments that share a common ID). The segments are then processed to create service graphs which visually show the relationship between services. X-Ray previews are available for those who wish to try it. More information from reInvent 2016.

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What AWS Offers to Mobile Developers at Re:Invent 2016 AWS Provides In-Depth Debugging for Developers with X-Ray AWS Intros Visual […]

re:Invent 2016, New AWS Tool Helps Find Expert Partners A new tool was introduced at the Amazon Web Services Inc.’s (AWS) re-Invent 2016 conference to help cloud users find AWS Partners to assist with specific projects. The AWS Partner Network is a program where the cloud provider assists curated partners to provide technical solutions or consulting to customers. It also helps customers find third-party services that meet their business needs. Yesterday’s AWS Global Partner Summit was held at reInvent 2016. It was a conference within a conference. Several new APN-related competencies and programs were announced. The new AWS Partner Solutions Finder, (PSF) allows customers to search for, find and connect with the right partners. Yesterday’s blog post by Kate Miller, AWS executive, provided more details. Miller stated that the PSF was built on feedback from customers and partners and is a new way to connect customers with partners. “Suppose you are a Consulting Partner who focuses on the Financial Services sector and hold the AWS Financial Services Competency. Customers can filter their search results by financial services, so your firm may be higher than other AWS Competency holders. Customers can filter by location, use case, and products to find exactly what you need. Miller summarized all the tools’ capabilities in a blog post on another section of AWS.

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You can search by topic, such as location, industry, use case, and products. You can easily identify AWS Resellers authorized […]

re:Invent 2016 – New Amazon AI Services to Help Developers Build Smarter Apps Amazon Web Services revealed three new offerings Wednesday that will enable developers to create apps that leverage artificial intelligence (AI) and were available for purchase on Wednesday. During Wednesday’s keynote at the reInvent conference in Las Vegas, CEO Andy Jassy gave an overview of the Amazon Rekognition and Amazon Polly products. These products are part of the Amazon AI product group, along with the previously released Amazon Machine Learning. Amazon Rekognition, a sophisticated image recognition service, is now generally available. It can identify faces, objects, and scenes using labels (e.g. “car,” woman,” steering wheel), and can also identify people. It can detect certain attributes such as gender expression and distinguishing characteristics. Jassy said that it can face-match, which is a useful option to security app developers. Amazon Polly is also available. It is basically a text-to speech “parroting” service. The service responds to users by recording a.MP3 of the text. Polly can interpret real-like dialogue accurately. It can distinguish between homographs, and understand abbreviations. It can also “speak”, in 47 voices and in 24 languages. Amazon Lex is currently in preview of the three new AI services. Jassy stated that Lex is the technology behind AWS’ Alexa, Echo and other services and described it as a way developers can build natural language and conversational capabilities in their apps. Amazon Lex can be used to create chatbots and other types web [and] mobile apps that support engaging, real-life interactions. Jeff Barr, AWS evangelist, explained how bots can help you provide information, power your app, streamline work activities, or provide a control mechanism to robots, drones and toys in a blog post on Wednesday. This post coincides with the re-Invent announcement. You start by creating a conversation in the Lex Console and providing Lex with some examples phrases that will be used to build a natural-language model. Next, publish your Amazon Lexbot and let it process voice or text conversations with your users. “AI is becoming a reality because of the combination of better algorithms, broad access to large amounts of data, and cost-effective computing power offered by the cloud. Raju Gulabani, AWS’ vice-president of Databases, Analytics and AI, stated in a prepared statement that AWS hosts some of the most creative and innovative AI applications currently in use. Amazon has thousands of machine learning and deep-learning experts who have been working on AI technologies for years. These technologies are used to predict what customers may like to read, drive efficiency in our fulfillment centers using robotics and computer vision technologies, as well as to provide customers with our AI-powered virtual assistant Alexa. We now make the technology behind these innovations available to developers in the form three fully managed Amazon AI Services that are simple to use, powerful, cost-effective, and affordable. More information at re:Invent 2016.

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What AWS Offers to Mobile Developers at Re:Invent 2016 AWS Provides Devs In-Depth Debugging with X-Ray AWS Intros Visual Workflows […]

Databricks Launches Apache Spark-Based Cloud Platform For Data Engineers Big Data company Databricks Inc. has launched a new version of its Apache Spark platform, which is specifically tuned for data engineers on Amazon Web Services Inc.’s (AWS). The platform, Databricks for Data Engineering is designed to assist data and machine learning engineers in creating and deploying highly optimized infrastructure for data processing on the cloud. These people are responsible for addressing business use cases like fraud detection and real-time dashboards. They also perform mission-critical operations such cleansing, transforming, and manipulating data. Databricks added that data engineering is essential for processing data to make business decisions or automate business processes using intelligent algorithms. Apache Spark is the open-source data processing engine that powers the Databricks platform. Its capabilities are greatly improved upon the MapReduce component that was introduced with Apache Hadoop. The company released a statement today stating that the new offering allows for more cost-effective data engineering with Spark and empowers data engineers to quickly and securely deploy data pipelines into production using Spark. Databricks for Data Engineering will be a complement to the company’s cloud platform and provide all enterprises with a unified platform for data analytics that facilitates seamless collaboration to accelerate data driven decisions across the organization. The company stated that the optimized platform offers:

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Performance optimization: Databricks I/O technology, (DBIO), improves processing speed with a tuned and optimized Spark version for a wide range […]

Databricks Now on AWS Databricks is the data analytics provider that created the Apache Spark analytics engine. It announced a partnership with Google Cloud to allow the deployment of its data engineering solution on another cloud platform. The San Francisco-based company is said to have “scored a trick” or won the “triple crown” by launching its solution on Amazon Web Services (AWS), Google Cloud, and Microsoft Azure. Databricks describes its solution as the “only unified data platform across all three cloud platforms.” Amazon Marketplace now offers the AWS implementation. This announcement comes after the company raised $1 billion in Series G funding. Franklin Templeton, a new investor, led the round. He joins strategic investors AWS CapitalG, Salesforce Ventures, and Salesforce Ventures. Microsoft was the lead investor in the round. Databricks users can create a “lakehouse” on Google Cloud’s elastic network, which is capable of data engineering and machine learning (ML), and analytics. Databricks now integrates to Google BigQuery’s open platform, and leverages Google Kubernetes Engine(GKE), the companies stated in a statement. This will allow its users to deploy Databricks into a fully containerized cloud environment. Databricks is built on a modern lakehouse architecture, which is cloud-based, and helps organizations eliminate the complexity and cost that are inherent in legacy data architectures,” Ali Ghodsi (CEO and co-founder of Databricks), said in a statement. “Data teams can collaborate and innovate more quickly.” This lakehouse paradigm is the driving force behind our growth and it’s exciting to see how excited our investors are about being a part. Databricks and Google Cloud have new integrations:

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Databricks is tightly integrated with Google Cloud’s analytics tools, making it easier to extend “AI driven insights” across data lakes […]